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DXP4800PLUS-B5F8
Inbox (9) - [EMAIL] - Gmail
(57) DXP4800PLUS-B5F8
Inbox (9) - [EMAIL] - Gmail
(57) Inbox | [EMAIL] | Proton Mail
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Western Digital Red Plus 3.5 6TB 5400rpm 256MB SATA3 (WD60EFPX) от 241,72 € (472,76 лв.) Вътрешен хард диск Western Digital - Pazaruvaj.com
Western Digital Red Plus 3.5 6TB 5400rpm 256MB SATA3 (WD60EFPX) от 241,72 € (472,76 лв.) Вътрешен хард диск Western Digital - Pazaruvaj.com
Today's Deals
Today's Deals
architecture - screenpipe docs
architecture - screenpipe docs
Claude Code works better when you stop treating it like a machine - [EMAIL] - Gmail
Claude Code works better when you stop treating it like a machine - [EMAIL] - Gmail
Screenpipe — Archive
Screenpipe — Archive
SQLite Web: archive.db
SQLite Web: archive.db
SQLite Web: db.sqlite
SQLite Web: db.sqlite
Claude Platform
Claude Platform
Hey @louis030195 Ill check during my - screenpipe.com
Hey @louis030195 Ill check during my - screenpipe.com
GitHub - screenpipe/screenpipe: Run agents that work for you based on what you do. AI finally knows what you are doing · GitHub
GitHub - screenpipe/screenpipe: Run agents that work for you based on what you do. AI finally knows what you are doing · GitHub
Gong Pricing in 2026: Costs, Plans & Is It Worth It?
Gong Pricing in 2026: Costs, Plans & Is It Worth It?
GLM 5.1 Thinks Strategically, Data-Center Revolt Intensifies, When Helpful LLMs Turn Unhelpful, Humanoid Robots Get to Work - [EMAIL] - Gmail
GLM 5.1 Thinks Strategically, Data-Center Revolt Intensifies, When Helpful LLMs Turn Unhelpful, Humanoid Robots Get to Work - [EMAIL] - Gmail
Gitea Official Website
Gitea Official Website
lakylak/screenpipe - screenpipe - Gitea: Git with a cup of tea
lakylak/screenpipe - screenpipe - Gitea: Git with a cup of tea
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MikroTik · CRS304-4XG-IN
MikroTik · CRS304-4XG-IN
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DXP4800PLUS-B5F8
Inbox (9) - [EMAIL] - Gmail
(57) DXP4800PLUS-B5F8
Inbox (9) - [EMAIL] - Gmail
(57) Inbox | [EMAIL] | Proton Mail
Welcome back
Welcome back
Western Digital Red Plus 3.5 6TB 5400rpm 256MB SATA3 (WD60EFPX) от 241,72 € (472,76 лв.) Вътрешен хард диск Western Digital - Pazaruvaj.com
Western Digital Red Plus 3.5 6TB 5400rpm 256MB SATA3 (WD60EFPX) от 241,72 € (472,76 лв.) Вътрешен хард диск Western Digital - Pazaruvaj.com
Today's Deals
Today's Deals
architecture - screenpipe docs
architecture - screenpipe docs
Claude Code works better when you stop treating it like a machine - [EMAIL] - Gmail
Claude Code works better when you stop treating it like a machine - [EMAIL] - Gmail
Screenpipe — Archive
Screenpipe — Archive
SQLite Web: archive.db
SQLite Web: archive.db
SQLite Web: db.sqlite
SQLite Web: db.sqlite
Claude Platform
Claude Platform
Hey @louis030195 Ill check during my - screenpipe.com
Hey @louis030195 Ill check during my - screenpipe.com
GitHub - screenpipe/screenpipe: Run agents that work for you based on what you do. AI finally knows what you are doing · GitHub
GitHub - screenpipe/screenpipe: Run agents that work for you based on what you do. AI finally knows what you are doing · GitHub
Gong Pricing in 2026: Costs, Plans & Is It Worth It?
Gong Pricing in 2026: Costs, Plans & Is It Worth It?
GLM 5.1 Thinks Strategically, Data-Center Revolt Intensifies, When Helpful LLMs Turn Unhelpful, Humanoid Robots Get to Work - [EMAIL] - Gmail
GLM 5.1 Thinks Strategically, Data-Center Revolt Intensifies, When Helpful LLMs Turn Unhelpful, Humanoid Robots Get to Work - [EMAIL] - Gmail
Gitea Official Website
Gitea Official Website
lakylak/screenpipe - screenpipe - Gitea: Git with a cup of tea
lakylak/screenpipe - screenpipe - Gitea: Git with a cup of tea
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MikroTik · CRS304-4XG-IN
MikroTik · CRS304-4XG-IN
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DXP4800PLUS-B5F8
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(57) DXP4800PLUS-B5F8
Inbox (9) - [EMAIL] - Gmail
(57) Inbox | [EMAIL] | Proton Mail
Welcome back
Welcome back
Western Digital Red Plus 3.5 6TB 5400rpm 256MB SATA3 (WD60EFPX) от 241,72 € (472,76 лв.) Вътрешен хард диск Western Digital - Pazaruvaj.com
Western Digital Red Plus 3.5 6TB 5400rpm 256MB SATA3 (WD60EFPX) от 241,72 € (472,76 лв.) Вътрешен хард диск Western Digital - Pazaruvaj.com
Today's Deals
Today's Deals
architecture - screenpipe docs
architecture - screenpipe docs
Claude Code works better when you stop treating it like a machine - [EMAIL] - Gmail
Claude Code works better when you stop treating it like a machine - [EMAIL] - Gmail
Screenpipe — Archive
Screenpipe — Archive
SQLite Web: archive.db
SQLite Web: archive.db
SQLite Web: db.sqlite
SQLite Web: db.sqlite
Claude Platform
Claude Platform
Hey @louis030195 Ill check during my - screenpipe.com
Hey @louis030195 Ill check during my - screenpipe.com
GitHub - screenpipe/screenpipe: Run agents that work for you based on what you do. AI finally knows what you are doing · GitHub
GitHub - screenpipe/screenpipe: Run agents that work for you based on what you do. AI finally knows what you are doing · GitHub
Gong Pricing in 2026: Costs, Plans & Is It Worth It?
Gong Pricing in 2026: Costs, Plans & Is It Worth It?
GLM 5.1 Thinks Strategically, Data-Center Revolt Intensifies, When Helpful LLMs Turn Unhelpful, Humanoid Robots Get to Work - [EMAIL] - Gmail
GLM 5.1 Thinks Strategically, Data-Center Revolt Intensifies, When Helpful LLMs Turn Unhelpful, Humanoid Robots Get to Work - [EMAIL] - Gmail
Gitea Official Website
Gitea Official Website
lakylak/screenpipe - screenpipe - Gitea: Git with a cup of tea
lakylak/screenpipe - screenpipe - Gitea: Git with a cup of tea
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MikroTik · CRS304-4XG-IN
MikroTik · CRS304-4XG-IN
New Tab
Customize sidebar
Open Le Chat Mistral (⌃X)
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Bitwarden
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467
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Control Panel
Storage
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Logs
Support
Task Manager
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Music
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TextEdit
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Recently modified
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Creation time
2026-04-11 16:11
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Inbox (9) - [EMAIL] - Gmail
(57) DXP4800PLUS-B5F8
Inbox (9) - [EMAIL] - Gmail
(57) Inbox | [EMAIL] | Proton Mail
Welcome back
Welcome back
Western Digital Red Plus 3.5 6TB 5400rpm 256MB SATA3 (WD60EFPX) от 241,72 € (472,76 лв.) Вътрешен хард диск Western Digital - Pazaruvaj.com
Western Digital Red Plus 3.5 6TB 5400rpm 256MB SATA3 (WD60EFPX) от 241,72 € (472,76 лв.) Вътрешен хард диск Western Digital - Pazaruvaj.com
Today's Deals
Today's Deals
architecture - screenpipe docs
architecture - screenpipe docs
Claude Code works better when you stop treating it like a machine - [EMAIL] - Gmail
Claude Code works better when you stop treating it like a machine - [EMAIL] - Gmail
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Screenpipe — Archive
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SQLite Web: archive.db
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SQLite Web: db.sqlite
Claude Platform
Claude Platform
Hey @louis030195 Ill check during my - screenpipe.com
Hey @louis030195 Ill check during my - screenpipe.com
GitHub - screenpipe/screenpipe: Run agents that work for you based on what you do. AI finally knows what you are doing · GitHub
GitHub - screenpipe/screenpipe: Run agents that work for you based on what you do. AI finally knows what you are doing · GitHub
Gong Pricing in 2026: Costs, Plans & Is It Worth It?
Gong Pricing in 2026: Costs, Plans & Is It Worth It?
GLM 5.1 Thinks Strategically, Data-Center Revolt Intensifies, When Helpful LLMs Turn Unhelpful, Humanoid Robots Get to Work - [EMAIL] - Gmail
GLM 5.1 Thinks Strategically, Data-Center Revolt Intensifies, When Helpful LLMs Turn Unhelpful, Humanoid Robots Get to Work - [EMAIL] - Gmail
Gitea Official Website
Gitea Official Website
lakylak/screenpipe - screenpipe - Gitea: Git with a cup of tea
lakylak/screenpipe - screenpipe - Gitea: Git with a cup of tea
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New Tab
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(57) DXP4800PLUS-B5F8
Inbox (9) - [EMAIL] - Gmail
(57) Inbox | [EMAIL] | Proton Mail
Welcome back
Welcome back
Western Digital Red Plus 3.5 6TB 5400rpm 256MB SATA3 (WD60EFPX) от 241,72 € (472,76 лв.) Вътрешен хард диск Western Digital - Pazaruvaj.com
Western Digital Red Plus 3.5 6TB 5400rpm 256MB SATA3 (WD60EFPX) от 241,72 € (472,76 лв.) Вътрешен хард диск Western Digital - Pazaruvaj.com
Today's Deals
Today's Deals
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architecture - screenpipe docs
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Claude Code works better when you stop treating it like a machine - [EMAIL] - Gmail
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Screenpipe — Archive
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SQLite Web: archive.db
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SQLite Web: db.sqlite
Claude Platform
Claude Platform
Hey @louis030195 Ill check during my - screenpipe.com
Hey @louis030195 Ill check during my - screenpipe.com
GitHub - screenpipe/screenpipe: Run agents that work for you based on what you do. AI finally knows what you are doing · GitHub
GitHub - screenpipe/screenpipe: Run agents that work for you based on what you do. AI finally knows what you are doing · GitHub
Gong Pricing in 2026: Costs, Plans & Is It Worth It?
Gong Pricing in 2026: Costs, Plans & Is It Worth It?
GLM 5.1 Thinks Strategically, Data-Center Revolt Intensifies, When Helpful LLMs Turn Unhelpful, Humanoid Robots Get to Work - [EMAIL] - Gmail
GLM 5.1 Thinks Strategically, Data-Center Revolt Intensifies, When Helpful LLMs Turn Unhelpful, Humanoid Robots Get to Work - [EMAIL] - Gmail
Gitea Official Website
Gitea Official Website
lakylak/screenpipe - screenpipe - Gitea: Git with a cup of tea
lakylak/screenpipe - screenpipe - Gitea: Git with a cup of tea
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New Tab
MikroTik · CRS304-4XG-IN
MikroTik · CRS304-4XG-IN
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DXP4800PLUS-B5F8
Inbox (9) - [EMAIL] - Gmail
(57) DXP4800PLUS-B5F8
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Western Digital Red Plus 3.5 6TB 5400rpm 256MB SATA3 (WD60EFPX) от 241,72 € (472,76 лв.) Вътрешен хард диск Western Digital - Pazaruvaj.com
Western Digital Red Plus 3.5 6TB 5400rpm 256MB SATA3 (WD60EFPX) от 241,72 € (472,76 лв.) Вътрешен хард диск Western Digital - Pazaruvaj.com
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architecture - screenpipe docs
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Claude Code works better when you stop treating it like a machine - [EMAIL] - Gmail
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SQLite Web: archive.db
SQLite Web: archive.db
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SQLite Web: db.sqlite
Claude Platform
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Hey @louis030195 Ill check during my - screenpipe.com
Hey @louis030195 Ill check during my - screenpipe.com
GitHub - screenpipe/screenpipe: Run agents that work for you based on what you do. AI finally knows what you are doing · GitHub
GitHub - screenpipe/screenpipe: Run agents that work for you based on what you do. AI finally knows what you are doing · GitHub
Gong Pricing in 2026: Costs, Plans & Is It Worth It?
Gong Pricing in 2026: Costs, Plans & Is It Worth It?
GLM 5.1 Thinks Strategically, Data-Center Revolt Intensifies, When Helpful LLMs Turn Unhelpful, Humanoid Robots Get to Work - [EMAIL] - Gmail
GLM 5.1 Thinks Strategically, Data-Center Revolt Intensifies, When Helpful LLMs Turn Unhelpful, Humanoid Robots Get to Work - [EMAIL] - Gmail
Gitea Official Website
Gitea Official Website
lakylak/screenpipe - screenpipe - Gitea: Git with a cup of tea
lakylak/screenpipe - screenpipe - Gitea: Git with a cup of tea
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NULL
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Western Digital Red Plus 3.5 6TB 5400rpm 256MB SATA3 (WD60EFPX) от 241,72 € (472,76 лв.) Вътрешен хард диск Western Digital - Pazaruvaj.com
Western Digital Red Plus 3.5 6TB 5400rpm 256MB SATA3 (WD60EFPX) от 241,72 € (472,76 лв.) Вътрешен хард диск Western Digital - Pazaruvaj.com
Today's Deals
Today's Deals
architecture - screenpipe docs
architecture - screenpipe docs
Claude Code works better when you stop treating it like a machine - [EMAIL] - Gmail
Claude Code works better when you stop treating it like a machine - [EMAIL] - Gmail
Screenpipe — Archive
Screenpipe — Archive
SQLite Web: archive.db
SQLite Web: archive.db
SQLite Web: db.sqlite
SQLite Web: db.sqlite
Claude Platform
Claude Platform
Hey @louis030195 Ill check during my - screenpipe.com
Hey @louis030195 Ill check during my - screenpipe.com
GitHub - screenpipe/screenpipe: Run agents that work for you based on what you do. AI finally knows what you are doing · GitHub
GitHub - screenpipe/screenpipe: Run agents that work for you based on what you do. AI finally knows what you are doing · GitHub
Gong Pricing in 2026: Costs, Plans & Is It Worth It?
Gong Pricing in 2026: Costs, Plans & Is It Worth It?
GLM 5.1 Thinks Strategically, Data-Center Revolt Intensifies, When Helpful LLMs Turn Unhelpful, Humanoid Robots Get to Work - [EMAIL] - Gmail
GLM 5.1 Thinks Strategically, Data-Center Revolt Intensifies, When Helpful LLMs Turn Unhelpful, Humanoid Robots Get to Work - [EMAIL] - Gmail
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DXP4800PLUS-B5F8
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(57) DXP4800PLUS-B5F8
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Western Digital Red Plus 3.5 6TB 5400rpm 256MB SATA3 (WD60EFPX) от 241,72 € (472,76 лв.) Вътрешен хард диск Western Digital - Pazaruvaj.com
Western Digital Red Plus 3.5 6TB 5400rpm 256MB SATA3 (WD60EFPX) от 241,72 € (472,76 лв.) Вътрешен хард диск Western Digital - Pazaruvaj.com
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GitHub - screenpipe/screenpipe: Run agents that work for you based on what you do. AI finally knows what you are doing · GitHub
GitHub - screenpipe/screenpipe: Run agents that work for you based on what you do. AI finally knows what you are doing · GitHub
Gong Pricing in 2026: Costs, Plans & Is It Worth It?
Gong Pricing in 2026: Costs, Plans & Is It Worth It?
GLM 5.1 Thinks Strategically, Data-Center Revolt Intensifies, When Helpful LLMs Turn Unhelpful, Humanoid Robots Get to Work - [EMAIL] - Gmail
GLM 5.1 Thinks Strategically, Data-Center Revolt Intensifies, When Helpful LLMs Turn Unhelpful, Humanoid Robots Get to Work - [EMAIL] - Gmail
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lakylak/screenpipe - screenpipe - Gitea: Git with a cup of tea
lakylak/screenpipe - screenpipe - Gitea: Git with a cup of tea
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Western Digital Red Plus 3.5 6TB 5400rpm 256MB SATA3 (WD60EFPX) от 241,72 € (472,76 лв.) Вътрешен хард диск Western Digital - Pazaruvaj.com
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Claude Code works better when you stop treating it like a machine - [EMAIL] - Gmail
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Hey @louis030195 Ill check during my - screenpipe.com
Hey @louis030195 Ill check during my - screenpipe.com
GitHub - screenpipe/screenpipe: Run agents that work for you based on what you do. AI finally knows what you are doing · GitHub
GitHub - screenpipe/screenpipe: Run agents that work for you based on what you do. AI finally knows what you are doing · GitHub
Gong Pricing in 2026: Costs, Plans & Is It Worth It?
Gong Pricing in 2026: Costs, Plans & Is It Worth It?
GLM 5.1 Thinks Strategically, Data-Center Revolt Intensifies, When Helpful LLMs Turn Unhelpful, Humanoid Robots Get to Work - [EMAIL] - Gmail
GLM 5.1 Thinks Strategically, Data-Center Revolt Intensifies, When Helpful LLMs Turn Unhelpful, Humanoid Robots Get to Work - [EMAIL] - Gmail
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3537022199348466648
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1797417585481408271
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visual_change
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accessibility
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NULL
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DXP4800PLUS-B5F8
Inbox (9) - [EMAIL] - Gmail
(57) DXP4800PLUS-B5F8
Inbox (9) - [EMAIL] - Gmail
(57) Inbox | [EMAIL] | Proton Mail
Welcome back
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Western Digital Red Plus 3.5 6TB 5400rpm 256MB SATA3 (WD60EFPX) от 241,72 € (472,76 лв.) Вътрешен хард диск Western Digital - Pazaruvaj.com
Western Digital Red Plus 3.5 6TB 5400rpm 256MB SATA3 (WD60EFPX) от 241,72 € (472,76 лв.) Вътрешен хард диск Western Digital - Pazaruvaj.com
Today's Deals
Today's Deals
architecture - screenpipe docs
architecture - screenpipe docs
Claude Code works better when you stop treating it like a machine - [EMAIL] - Gmail
Claude Code works better when you stop treating it like a machine - [EMAIL] - Gmail
Screenpipe — Archive
Screenpipe — Archive
SQLite Web: archive.db
SQLite Web: archive.db
SQLite Web: db.sqlite
SQLite Web: db.sqlite
Claude Platform
Claude Platform
Hey @louis030195 Ill check during my - screenpipe.com
Hey @louis030195 Ill check during my - screenpipe.com
GitHub - screenpipe/screenpipe: Run agents that work for you based on what you do. AI finally knows what you are doing · GitHub
GitHub - screenpipe/screenpipe: Run agents that work for you based on what you do. AI finally knows what you are doing · GitHub
Gong Pricing in 2026: Costs, Plans & Is It Worth It?
Gong Pricing in 2026: Costs, Plans & Is It Worth It?
GLM 5.1 Thinks Strategically, Data-Center Revolt Intensifies, When Helpful LLMs Turn Unhelpful, Humanoid Robots Get to Work - [EMAIL] - Gmail
GLM 5.1 Thinks Strategically, Data-Center Revolt Intensifies, When Helpful LLMs Turn Unhelpful, Humanoid Robots Get to Work - [EMAIL] - Gmail
Gitea Official Website
Gitea Official Website
lakylak/screenpipe - screenpipe - Gitea: Git with a cup of tea
lakylak/screenpipe - screenpipe - Gitea: Git with a cup of tea
New Tab
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MikroTik · CRS304-4XG-IN
MikroTik · CRS304-4XG-IN
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Open Le Chat Mistral (⌃X)
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Bitwarden
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Youtube
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Folder
2026-01-15 17:57
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Folder
2026-04-24 13:44
screenpipe
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2026-04-25 20:16
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Folder
2025-10-24 22:41
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2026-02-09 20:06
Media
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Folder
2026-04-06 19:44
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2026-02-10 10:22
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2025-08-10 22:58
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Total items: 19
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NULL
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81824
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NULL
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0
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2026-04-26T13:35:38.988038+00:00
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/Users/lukas/.screenpipe/data/data/2026-04-26/1777 /Users/lukas/.screenpipe/data/data/2026-04-26/1777210538988_m1.jpg...
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Firefox
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DXP4800PLUS-B5F8 — Personal
|
True
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nas.lakylak.xyz/desktop/#/
|
monitor_1
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NULL
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NULL
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NULL
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/Users/lukas/.screenpipe/data/data/2026-04-26/1777 /Users/lukas/.screenpipe/data/data/2026-04-26/1777210538988_m1.jpg...
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DXP4800PLUS-B5F8
Inbox (9) - [EMAIL] - Gmail
(57) DXP4800PLUS-B5F8
Inbox (9) - [EMAIL] - Gmail
(57) Inbox | [EMAIL] | Proton Mail
Welcome back
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Western Digital Red Plus 3.5 6TB 5400rpm 256MB SATA3 (WD60EFPX) от 241,72 € (472,76 лв.) Вътрешен хард диск Western Digital - Pazaruvaj.com
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Gong Pricing in 2026: Costs, Plans & Is It Worth It?
Gong Pricing in 2026: Costs, Plans & Is It Worth It?
GLM 5.1 Thinks Strategically, Data-Center Revolt Intensifies, When Helpful LLMs Turn Unhelpful, Humanoid Robots Get to Work - [EMAIL] - Gmail
GLM 5.1 Thinks Strategically, Data-Center Revolt Intensifies, When Helpful LLMs Turn Unhelpful, Humanoid Robots Get to Work - [EMAIL] - Gmail
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lakylak/screenpipe - screenpipe - Gitea: Git with a cup of tea
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DXP4800PLUS-B5F8
Inbox (9) - [EMAIL] - Gmail
(57) DXP4800PLUS-B5F8
Inbox (9) - [EMAIL] - Gmail
(57) Inbox | [EMAIL] | Proton Mail
Welcome back
Welcome back
Western Digital Red Plus 3.5 6TB 5400rpm 256MB SATA3 (WD60EFPX) от 241,72 € (472,76 лв.) Вътрешен хард диск Western Digital - Pazaruvaj.com
Western Digital Red Plus 3.5 6TB 5400rpm 256MB SATA3 (WD60EFPX) от 241,72 € (472,76 лв.) Вътрешен хард диск Western Digital - Pazaruvaj.com
Today's Deals
Today's Deals
architecture - screenpipe docs
architecture - screenpipe docs
Claude Code works better when you stop treating it like a machine - [EMAIL] - Gmail
Claude Code works better when you stop treating it like a machine - [EMAIL] - Gmail
Screenpipe — Archive
Screenpipe — Archive
SQLite Web: archive.db
SQLite Web: archive.db
SQLite Web: db.sqlite
SQLite Web: db.sqlite
Claude Platform
Claude Platform
Hey @louis030195 Ill check during my - screenpipe.com
Hey @louis030195 Ill check during my - screenpipe.com
GitHub - screenpipe/screenpipe: Run agents that work for you based on what you do. AI finally knows what you are doing · GitHub
GitHub - screenpipe/screenpipe: Run agents that work for you based on what you do. AI finally knows what you are doing · GitHub
Gong Pricing in 2026: Costs, Plans & Is It Worth It?
Gong Pricing in 2026: Costs, Plans & Is It Worth It?
GLM 5.1 Thinks Strategically, Data-Center Revolt Intensifies, When Helpful LLMs Turn Unhelpful, Humanoid Robots Get to Work - [EMAIL] - Gmail
GLM 5.1 Thinks Strategically, Data-Center Revolt Intensifies, When Helpful LLMs Turn Unhelpful, Humanoid Robots Get to Work - [EMAIL] - Gmail
Gitea Official Website
Gitea Official Website
lakylak/screenpipe - screenpipe - Gitea: Git with a cup of tea
lakylak/screenpipe - screenpipe - Gitea: Git with a cup of tea
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DXP4800PLUS-B5F8
Inbox (9) - [EMAIL] - Gmail
(57) DXP4800PLUS-B5F8
Inbox (9) - [EMAIL] - Gmail
(57) Inbox | [EMAIL] | Proton Mail
Welcome back
Welcome back
Western Digital Red Plus 3.5 6TB 5400rpm 256MB SATA3 (WD60EFPX) от 241,72 € (472,76 лв.) Вътрешен хард диск Western Digital - Pazaruvaj.com
Western Digital Red Plus 3.5 6TB 5400rpm 256MB SATA3 (WD60EFPX) от 241,72 € (472,76 лв.) Вътрешен хард диск Western Digital - Pazaruvaj.com
Today's Deals
Today's Deals
architecture - screenpipe docs
architecture - screenpipe docs
Claude Code works better when you stop treating it like a machine - [EMAIL] - Gmail
Claude Code works better when you stop treating it like a machine - [EMAIL] - Gmail
Screenpipe — Archive
Screenpipe — Archive
SQLite Web: archive.db
SQLite Web: archive.db
SQLite Web: db.sqlite
SQLite Web: db.sqlite
Claude Platform
Claude Platform
Hey @louis030195 Ill check during my - screenpipe.com
Hey @louis030195 Ill check during my - screenpipe.com
GitHub - screenpipe/screenpipe: Run agents that work for you based on what you do. AI finally knows what you are doing · GitHub
GitHub - screenpipe/screenpipe: Run agents that work for you based on what you do. AI finally knows what you are doing · GitHub
Gong Pricing in 2026: Costs, Plans & Is It Worth It?
Gong Pricing in 2026: Costs, Plans & Is It Worth It?
GLM 5.1 Thinks Strategically, Data-Center Revolt Intensifies, When Helpful LLMs Turn Unhelpful, Humanoid Robots Get to Work - [EMAIL] - Gmail
GLM 5.1 Thinks Strategically, Data-Center Revolt Intensifies, When Helpful LLMs Turn Unhelpful, Humanoid Robots Get to Work - [EMAIL] - Gmail
Gitea Official Website
Gitea Official Website
lakylak/screenpipe - screenpipe - Gitea: Git with a cup of tea
lakylak/screenpipe - screenpipe - Gitea: Git with a cup of tea
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MikroTik · CRS304-4XG-IN
MikroTik · CRS304-4XG-IN
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DXP4800PLUS-B5F8
Inbox (9) - [EMAIL] - Gmail
(57) DXP4800PLUS-B5F8
Inbox (9) - [EMAIL] - Gmail
(57) Inbox | [EMAIL] | Proton Mail
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Western Digital Red Plus 3.5 6TB 5400rpm 256MB SATA3 (WD60EFPX) от 241,72 € (472,76 лв.) Вътрешен хард диск Western Digital - Pazaruvaj.com
Western Digital Red Plus 3.5 6TB 5400rpm 256MB SATA3 (WD60EFPX) от 241,72 € (472,76 лв.) Вътрешен хард диск Western Digital - Pazaruvaj.com
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architecture - screenpipe docs
architecture - screenpipe docs
Claude Code works better when you stop treating it like a machine - [EMAIL] - Gmail
Claude Code works better when you stop treating it like a machine - [EMAIL] - Gmail
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Claude Platform
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Hey @louis030195 Ill check during my - screenpipe.com
Hey @louis030195 Ill check during my - screenpipe.com
GitHub - screenpipe/screenpipe: Run agents that work for you based on what you do. AI finally knows what you are doing · GitHub
GitHub - screenpipe/screenpipe: Run agents that work for you based on what you do. AI finally knows what you are doing · GitHub
Gong Pricing in 2026: Costs, Plans & Is It Worth It?
Gong Pricing in 2026: Costs, Plans & Is It Worth It?
GLM 5.1 Thinks Strategically, Data-Center Revolt Intensifies, When Helpful LLMs Turn Unhelpful, Humanoid Robots Get to Work - [EMAIL] - Gmail
GLM 5.1 Thinks Strategically, Data-Center Revolt Intensifies, When Helpful LLMs Turn Unhelpful, Humanoid Robots Get to Work - [EMAIL] - Gmail
Gitea Official Website
Gitea Official Website
lakylak/screenpipe - screenpipe - Gitea: Git with a cup of tea
lakylak/screenpipe - screenpipe - Gitea: Git with a cup of tea
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(57) DXP4800PLUS-B5F8
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(57) Inbox | [EMAIL] | Proton Mail
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Western Digital Red Plus 3.5 6TB 5400rpm 256MB SATA3 (WD60EFPX) от 241,72 € (472,76 лв.) Вътрешен хард диск Western Digital - Pazaruvaj.com
Western Digital Red Plus 3.5 6TB 5400rpm 256MB SATA3 (WD60EFPX) от 241,72 € (472,76 лв.) Вътрешен хард диск Western Digital - Pazaruvaj.com
Today's Deals
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architecture - screenpipe docs
architecture - screenpipe docs
Claude Code works better when you stop treating it like a machine - [EMAIL] - Gmail
Claude Code works better when you stop treating it like a machine - [EMAIL] - Gmail
Screenpipe — Archive
Screenpipe — Archive
SQLite Web: archive.db
SQLite Web: archive.db
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SQLite Web: db.sqlite
Claude Platform
Claude Platform
Hey @louis030195 Ill check during my - screenpipe.com
Hey @louis030195 Ill check during my - screenpipe.com
GitHub - screenpipe/screenpipe: Run agents that work for you based on what you do. AI finally knows what you are doing · GitHub
GitHub - screenpipe/screenpipe: Run agents that work for you based on what you do. AI finally knows what you are doing · GitHub
Gong Pricing in 2026: Costs, Plans & Is It Worth It?
Gong Pricing in 2026: Costs, Plans & Is It Worth It?
GLM 5.1 Thinks Strategically, Data-Center Revolt Intensifies, When Helpful LLMs Turn Unhelpful, Humanoid Robots Get to Work - [EMAIL] - Gmail
GLM 5.1 Thinks Strategically, Data-Center Revolt Intensifies, When Helpful LLMs Turn Unhelpful, Humanoid Robots Get to Work - [EMAIL] - Gmail
Gitea Official Website
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lakylak/screenpipe - screenpipe - Gitea: Git with a cup of tea
lakylak/screenpipe - screenpipe - Gitea: Git with a cup of tea
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DXP4800PLUS-B5F8
Inbox (9) - [EMAIL] - Gmail
(57) DXP4800PLUS-B5F8
Inbox (9) - [EMAIL] - Gmail
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Western Digital Red Plus 3.5 6TB 5400rpm 256MB SATA3 (WD60EFPX) от 241,72 € (472,76 лв.) Вътрешен хард диск Western Digital - Pazaruvaj.com
Western Digital Red Plus 3.5 6TB 5400rpm 256MB SATA3 (WD60EFPX) от 241,72 € (472,76 лв.) Вътрешен хард диск Western Digital - Pazaruvaj.com
Today's Deals
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architecture - screenpipe docs
architecture - screenpipe docs
Claude Code works better when you stop treating it like a machine - [EMAIL] - Gmail
Claude Code works better when you stop treating it like a machine - [EMAIL] - Gmail
Screenpipe — Archive
Screenpipe — Archive
SQLite Web: archive.db
SQLite Web: archive.db
SQLite Web: db.sqlite
SQLite Web: db.sqlite
Claude Platform
Claude Platform
Hey @louis030195 Ill check during my - screenpipe.com
Hey @louis030195 Ill check during my - screenpipe.com
GitHub - screenpipe/screenpipe: Run agents that work for you based on what you do. AI finally knows what you are doing · GitHub
GitHub - screenpipe/screenpipe: Run agents that work for you based on what you do. AI finally knows what you are doing · GitHub
Gong Pricing in 2026: Costs, Plans & Is It Worth It?
Gong Pricing in 2026: Costs, Plans & Is It Worth It?
GLM 5.1 Thinks Strategically, Data-Center Revolt Intensifies, When Helpful LLMs Turn Unhelpful, Humanoid Robots Get to Work - [EMAIL] - Gmail
GLM 5.1 Thinks Strategically, Data-Center Revolt Intensifies, When Helpful LLMs Turn Unhelpful, Humanoid Robots Get to Work - [EMAIL] - Gmail
Gitea Official Website
Gitea Official Website
lakylak/screenpipe - screenpipe - Gitea: Git with a cup of tea
lakylak/screenpipe - screenpipe - Gitea: Git with a cup of tea
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2026-02-10 10:22
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NULL
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81827
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0
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2026-04-26T13:35:47.864447+00:00
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/Users/lukas/.screenpipe/data/data/2026-04-26/1777 /Users/lukas/.screenpipe/data/data/2026-04-26/1777210547864_m2.jpg...
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Firefox
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DXP4800PLUS-B5F8 — Personal
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True
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nas.lakylak.xyz/desktop/#/
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monitor_2
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NULL
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NULL
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NULL
|
/Users/lukas/.screenpipe/data/data/2026-04-26/1777 /Users/lukas/.screenpipe/data/data/2026-04-26/1777210547864_m2.jpg...
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DXP4800PLUS-B5F8
Inbox (9) - [EMAIL] - Gmail
(57) DXP4800PLUS-B5F8
Inbox (9) - [EMAIL] - Gmail
(57) Inbox | [EMAIL] | Proton Mail
Welcome back
Welcome back
Western Digital Red Plus 3.5 6TB 5400rpm 256MB SATA3 (WD60EFPX) от 241,72 € (472,76 лв.) Вътрешен хард диск Western Digital - Pazaruvaj.com
Western Digital Red Plus 3.5 6TB 5400rpm 256MB SATA3 (WD60EFPX) от 241,72 € (472,76 лв.) Вътрешен хард диск Western Digital - Pazaruvaj.com
Today's Deals
Today's Deals
architecture - screenpipe docs
architecture - screenpipe docs
Claude Code works better when you stop treating it like a machine - [EMAIL] - Gmail
Claude Code works better when you stop treating it like a machine - [EMAIL] - Gmail
Screenpipe — Archive
Screenpipe — Archive
SQLite Web: archive.db
SQLite Web: archive.db
SQLite Web: db.sqlite
SQLite Web: db.sqlite
Claude Platform
Claude Platform
Hey @louis030195 Ill check during my - screenpipe.com
Hey @louis030195 Ill check during my - screenpipe.com
GitHub - screenpipe/screenpipe: Run agents that work for you based on what you do. AI finally knows what you are doing · GitHub
GitHub - screenpipe/screenpipe: Run agents that work for you based on what you do. AI finally knows what you are doing · GitHub
Gong Pricing in 2026: Costs, Plans & Is It Worth It?
Gong Pricing in 2026: Costs, Plans & Is It Worth It?
GLM 5.1 Thinks Strategically, Data-Center Revolt Intensifies, When Helpful LLMs Turn Unhelpful, Humanoid Robots Get to Work - [EMAIL] - Gmail
GLM 5.1 Thinks Strategically, Data-Center Revolt Intensifies, When Helpful LLMs Turn Unhelpful, Humanoid Robots Get to Work - [EMAIL] - Gmail
Gitea Official Website
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lakylak/screenpipe - screenpipe - Gitea: Git with a cup of tea
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DXP4800PLUS-B5F8
Inbox (9) - [EMAIL] - Gmail
(57) DXP4800PLUS-B5F8
Inbox (9) - [EMAIL] - Gmail
(57) Inbox | [EMAIL] | Proton Mail
Welcome back
Welcome back
Western Digital Red Plus 3.5 6TB 5400rpm 256MB SATA3 (WD60EFPX) от 241,72 € (472,76 лв.) Вътрешен хард диск Western Digital - Pazaruvaj.com
Western Digital Red Plus 3.5 6TB 5400rpm 256MB SATA3 (WD60EFPX) от 241,72 € (472,76 лв.) Вътрешен хард диск Western Digital - Pazaruvaj.com
Today's Deals
Today's Deals
architecture - screenpipe docs
architecture - screenpipe docs
Claude Code works better when you stop treating it like a machine - [EMAIL] - Gmail
Claude Code works better when you stop treating it like a machine - [EMAIL] - Gmail
Screenpipe — Archive
Screenpipe — Archive
SQLite Web: archive.db
SQLite Web: archive.db
SQLite Web: db.sqlite
SQLite Web: db.sqlite
Claude Platform
Claude Platform
Hey @louis030195 Ill check during my - screenpipe.com
Hey @louis030195 Ill check during my - screenpipe.com
GitHub - screenpipe/screenpipe: Run agents that work for you based on what you do. AI finally knows what you are doing · GitHub
GitHub - screenpipe/screenpipe: Run agents that work for you based on what you do. AI finally knows what you are doing · GitHub
Gong Pricing in 2026: Costs, Plans & Is It Worth It?
Gong Pricing in 2026: Costs, Plans & Is It Worth It?
GLM 5.1 Thinks Strategically, Data-Center Revolt Intensifies, When Helpful LLMs Turn Unhelpful, Humanoid Robots Get to Work - [EMAIL] - Gmail
GLM 5.1 Thinks Strategically, Data-Center Revolt Intensifies, When Helpful LLMs Turn Unhelpful, Humanoid Robots Get to Work - [EMAIL] - Gmail
Gitea Official Website
Gitea Official Website
lakylak/screenpipe - screenpipe - Gitea: Git with a cup of tea
lakylak/screenpipe - screenpipe - Gitea: Git with a cup of tea
New Tab
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MikroTik · CRS304-4XG-IN
MikroTik · CRS304-4XG-IN
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2026-01-15 17:57
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2026-02-10 10:22
Apps
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Folder
2025-08-10 22:58
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NULL
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81828
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NULL
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0
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2026-04-26T13:35:49.640701+00:00
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/Users/lukas/.screenpipe/data/data/2026-04-26/1777 /Users/lukas/.screenpipe/data/data/2026-04-26/1777210549640_m2.jpg...
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Firefox
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DXP4800PLUS-B5F8 — Personal
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monitor_2
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NULL
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NULL
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NULL
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/Users/lukas/.screenpipe/data/data/2026-04-26/1777 /Users/lukas/.screenpipe/data/data/2026-04-26/1777210549640_m2.jpg...
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DXP4800PLUS-B5F8
Inbox (9) - [EMAIL] - Gmail
(57) DXP4800PLUS-B5F8
Inbox (9) - [EMAIL] - Gmail
(57) Inbox | [EMAIL] | Proton Mail
Welcome back
Welcome back
Western Digital Red Plus 3.5 6TB 5400rpm 256MB SATA3 (WD60EFPX) от 241,72 € (472,76 лв.) Вътрешен хард диск Western Digital - Pazaruvaj.com
Western Digital Red Plus 3.5 6TB 5400rpm 256MB SATA3 (WD60EFPX) от 241,72 € (472,76 лв.) Вътрешен хард диск Western Digital - Pazaruvaj.com
Today's Deals
Today's Deals
architecture - screenpipe docs
architecture - screenpipe docs
Claude Code works better when you stop treating it like a machine - [EMAIL] - Gmail
Claude Code works better when you stop treating it like a machine - [EMAIL] - Gmail
Screenpipe — Archive
Screenpipe — Archive
SQLite Web: archive.db
SQLite Web: archive.db
SQLite Web: db.sqlite
SQLite Web: db.sqlite
Claude Platform
Claude Platform
Hey @louis030195 Ill check during my - screenpipe.com
Hey @louis030195 Ill check during my - screenpipe.com
GitHub - screenpipe/screenpipe: Run agents that work for you based on what you do. AI finally knows what you are doing · GitHub
GitHub - screenpipe/screenpipe: Run agents that work for you based on what you do. AI finally knows what you are doing · GitHub
Gong Pricing in 2026: Costs, Plans & Is It Worth It?
Gong Pricing in 2026: Costs, Plans & Is It Worth It?
GLM 5.1 Thinks Strategically, Data-Center Revolt Intensifies, When Helpful LLMs Turn Unhelpful, Humanoid Robots Get to Work - [EMAIL] - Gmail
GLM 5.1 Thinks Strategically, Data-Center Revolt Intensifies, When Helpful LLMs Turn Unhelpful, Humanoid Robots Get to Work - [EMAIL] - Gmail
Gitea Official Website
Gitea Official Website
lakylak/screenpipe - screenpipe - Gitea: Git with a cup of tea
lakylak/screenpipe - screenpipe - Gitea: Git with a cup of tea
New Tab
New Tab
MikroTik · CRS304-4XG-IN
MikroTik · CRS304-4XG-IN
New Tab
Customize sidebar
Open Le Chat Mistral (⌃X)
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Open bookmarks (⌘B)
Bitwarden
851
B/s
230
B/s
Files
Control Panel
Storage
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Logs
Support
Task Manager
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Photos
Online Office
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Virtual Machine
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DLNA
File Version Explorer
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Vault
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Please enter
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Youtube
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Folder
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Folder
2026-04-25 20:37
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Folder
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2026-01-01 15:39
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2026-01-25 17:51
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2025-10-14 12:21
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2026-03-30 19:14
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2026-04-24 13:44
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2025-12-26 18:16
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Folder
2026-04-06 19:44
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2026-02-10 10:22
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Folder
2025-08-10 22:58
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Operation successful...
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DXP4800PLUS-B5F8
Inbox (9) - [EMAIL] - Gmail
(57) DXP4800PLUS-B5F8
Inbox (9) - [EMAIL] - Gmail
(57) Inbox | [EMAIL] | Proton Mail
Welcome back
Welcome back
Western Digital Red Plus 3.5 6TB 5400rpm 256MB SATA3 (WD60EFPX) от 241,72 € (472,76 лв.) Вътрешен хард диск Western Digital - Pazaruvaj.com
Western Digital Red Plus 3.5 6TB 5400rpm 256MB SATA3 (WD60EFPX) от 241,72 € (472,76 лв.) Вътрешен хард диск Western Digital - Pazaruvaj.com
Today's Deals
Today's Deals
architecture - screenpipe docs
architecture - screenpipe docs
Claude Code works better when you stop treating it like a machine - [EMAIL] - Gmail
Claude Code works better when you stop treating it like a machine - [EMAIL] - Gmail
Screenpipe — Archive
Screenpipe — Archive
SQLite Web: archive.db
SQLite Web: archive.db
SQLite Web: db.sqlite
SQLite Web: db.sqlite
Claude Platform
Claude Platform
Hey @louis030195 Ill check during my - screenpipe.com
Hey @louis030195 Ill check during my - screenpipe.com
GitHub - screenpipe/screenpipe: Run agents that work for you based on what you do. AI finally knows what you are doing · GitHub
GitHub - screenpipe/screenpipe: Run agents that work for you based on what you do. AI finally knows what you are doing · GitHub
Gong Pricing in 2026: Costs, Plans & Is It Worth It?
Gong Pricing in 2026: Costs, Plans & Is It Worth It?
GLM 5.1 Thinks Strategically, Data-Center Revolt Intensifies, When Helpful LLMs Turn Unhelpful, Humanoid Robots Get to Work - [EMAIL] - Gmail
GLM 5.1 Thinks Strategically, Data-Center Revolt Intensifies, When Helpful LLMs Turn Unhelpful, Humanoid Robots Get to Work - [EMAIL] - Gmail
Gitea Official Website
Gitea Official Website
lakylak/screenpipe - screenpipe - Gitea: Git with a cup of tea
lakylak/screenpipe - screenpipe - Gitea: Git with a cup of tea
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MikroTik · CRS304-4XG-IN
MikroTik · CRS304-4XG-IN
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NULL
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0
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2026-04-26T13:36:30.137575+00:00
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/Users/lukas/.screenpipe/data/data/2026-04-26/1777 /Users/lukas/.screenpipe/data/data/2026-04-26/1777210590137_m1.jpg...
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Firefox
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DXP4800PLUS-B5F8 — Personal
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True
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nas.lakylak.xyz/desktop/#/
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monitor_1
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NULL
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NULL
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NULL
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/Users/lukas/.screenpipe/data/data/2026-04-26/1777 /Users/lukas/.screenpipe/data/data/2026-04-26/1777210590137_m1.jpg...
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DXP4800PLUS-B5F8
Inbox (9) - [EMAIL] - Gmail
(57) DXP4800PLUS-B5F8
Inbox (9) - [EMAIL] - Gmail
(57) Inbox | [EMAIL] | Proton Mail
Welcome back
Welcome back
Western Digital Red Plus 3.5 6TB 5400rpm 256MB SATA3 (WD60EFPX) от 241,72 € (472,76 лв.) Вътрешен хард диск Western Digital - Pazaruvaj.com
Western Digital Red Plus 3.5 6TB 5400rpm 256MB SATA3 (WD60EFPX) от 241,72 € (472,76 лв.) Вътрешен хард диск Western Digital - Pazaruvaj.com
Today's Deals
Today's Deals
architecture - screenpipe docs
architecture - screenpipe docs
Claude Code works better when you stop treating it like a machine - [EMAIL] - Gmail
Claude Code works better when you stop treating it like a machine - [EMAIL] - Gmail
Screenpipe — Archive
Screenpipe — Archive
SQLite Web: archive.db
SQLite Web: archive.db
SQLite Web: db.sqlite
SQLite Web: db.sqlite
Claude Platform
Claude Platform
Hey @louis030195 Ill check during my - screenpipe.com
Hey @louis030195 Ill check during my - screenpipe.com
GitHub - screenpipe/screenpipe: Run agents that work for you based on what you do. AI finally knows what you are doing · GitHub
GitHub - screenpipe/screenpipe: Run agents that work for you based on what you do. AI finally knows what you are doing · GitHub
Gong Pricing in 2026: Costs, Plans & Is It Worth It?
Gong Pricing in 2026: Costs, Plans & Is It Worth It?
GLM 5.1 Thinks Strategically, Data-Center Revolt Intensifies, When Helpful LLMs Turn Unhelpful, Humanoid Robots Get to Work - [EMAIL] - Gmail
GLM 5.1 Thinks Strategically, Data-Center Revolt Intensifies, When Helpful LLMs Turn Unhelpful, Humanoid Robots Get to Work - [EMAIL] - Gmail
Gitea Official Website
Gitea Official Website
lakylak/screenpipe - screenpipe - Gitea: Git with a cup of tea
lakylak/screenpipe - screenpipe - Gitea: Git with a cup of tea
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MikroTik · CRS304-4XG-IN
MikroTik · CRS304-4XG-IN
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2025-09-27 17:56
Marti
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Folder
2025-10-24 20:06
Google...
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Inbox (9) - [EMAIL] - Gmail
(57) DXP4800PLUS-B5F8
Inbox (9) - [EMAIL] - Gmail
(57) Inbox | [EMAIL] | Proton Mail
Welcome back
Welcome back
Western Digital Red Plus 3.5 6TB 5400rpm 256MB SATA3 (WD60EFPX) от 241,72 € (472,76 лв.) Вътрешен хард диск Western Digital - Pazaruvaj.com
Western Digital Red Plus 3.5 6TB 5400rpm 256MB SATA3 (WD60EFPX) от 241,72 € (472,76 лв.) Вътрешен хард диск Western Digital - Pazaruvaj.com
Today's Deals
Today's Deals
architecture - screenpipe docs
architecture - screenpipe docs
Claude Code works better when you stop treating it like a machine - [EMAIL] - Gmail
Claude Code works better when you stop treating it like a machine - [EMAIL] - Gmail
Screenpipe — Archive
Screenpipe — Archive
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SQLite Web: archive.db
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SQLite Web: db.sqlite
Claude Platform
Claude Platform
Hey @louis030195 Ill check during my - screenpipe.com
Hey @louis030195 Ill check during my - screenpipe.com
GitHub - screenpipe/screenpipe: Run agents that work for you based on what you do. AI finally knows what you are doing · GitHub
GitHub - screenpipe/screenpipe: Run agents that work for you based on what you do. AI finally knows what you are doing · GitHub
Gong Pricing in 2026: Costs, Plans & Is It Worth It?
Gong Pricing in 2026: Costs, Plans & Is It Worth It?
GLM 5.1 Thinks Strategically, Data-Center Revolt Intensifies, When Helpful LLMs Turn Unhelpful, Humanoid Robots Get to Work - [EMAIL] - Gmail
GLM 5.1 Thinks Strategically, Data-Center Revolt Intensifies, When Helpful LLMs Turn Unhelpful, Humanoid Robots Get to Work - [EMAIL] - Gmail
Gitea Official Website
Gitea Official Website
lakylak/screenpipe - screenpipe - Gitea: Git with a cup of tea
lakylak/screenpipe - screenpipe - Gitea: Git with a cup of tea
New Tab
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MikroTik · CRS304-4XG-IN
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DXP4800PLUS-B5F8
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(57) DXP4800PLUS-B5F8
Inbox (9) - [EMAIL] - Gmail
(57) Inbox | [EMAIL] | Proton Mail
Welcome back
Welcome back
Western Digital Red Plus 3.5 6TB 5400rpm 256MB SATA3 (WD60EFPX) от 241,72 € (472,76 лв.) Вътрешен хард диск Western Digital - Pazaruvaj.com
Western Digital Red Plus 3.5 6TB 5400rpm 256MB SATA3 (WD60EFPX) от 241,72 € (472,76 лв.) Вътрешен хард диск Western Digital - Pazaruvaj.com
Today's Deals
Today's Deals
architecture - screenpipe docs
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Claude Code works better when you stop treating it like a machine - [EMAIL] - Gmail
Screenpipe — Archive
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SQLite Web: archive.db
SQLite Web: archive.db
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SQLite Web: db.sqlite
Claude Platform
Claude Platform
Hey @louis030195 Ill check during my - screenpipe.com
Hey @louis030195 Ill check during my - screenpipe.com
GitHub - screenpipe/screenpipe: Run agents that work for you based on what you do. AI finally knows what you are doing · GitHub
GitHub - screenpipe/screenpipe: Run agents that work for you based on what you do. AI finally knows what you are doing · GitHub
Gong Pricing in 2026: Costs, Plans & Is It Worth It?
Gong Pricing in 2026: Costs, Plans & Is It Worth It?
GLM 5.1 Thinks Strategically, Data-Center Revolt Intensifies, When Helpful LLMs Turn Unhelpful, Humanoid Robots Get to Work - [EMAIL] - Gmail
GLM 5.1 Thinks Strategically, Data-Center Revolt Intensifies, When Helpful LLMs Turn Unhelpful, Humanoid Robots Get to Work - [EMAIL] - Gmail
Gitea Official Website
Gitea Official Website
lakylak/screenpipe - screenpipe - Gitea: Git with a cup of tea
lakylak/screenpipe - screenpipe - Gitea: Git with a cup of tea
New Tab
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MikroTik · CRS304-4XG-IN
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Open Le Chat Mistral (⌃X)
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DXP4800PLUS-B5F8
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Western Digital Red Plus 3.5 6TB 5400rpm 256MB SATA3 (WD60EFPX) от 241,72 € (472,76 лв.) Вътрешен хард диск Western Digital - Pazaruvaj.com
Western Digital Red Plus 3.5 6TB 5400rpm 256MB SATA3 (WD60EFPX) от 241,72 € (472,76 лв.) Вътрешен хард диск Western Digital - Pazaruvaj.com
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SQLite Web: archive.db
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Claude Platform
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Hey @louis030195 Ill check during my - screenpipe.com
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GitHub - screenpipe/screenpipe: Run agents that work for you based on what you do. AI finally knows what you are doing · GitHub
GitHub - screenpipe/screenpipe: Run agents that work for you based on what you do. AI finally knows what you are doing · GitHub
Gong Pricing in 2026: Costs, Plans & Is It Worth It?
Gong Pricing in 2026: Costs, Plans & Is It Worth It?
GLM 5.1 Thinks Strategically, Data-Center Revolt Intensifies, When Helpful LLMs Turn Unhelpful, Humanoid Robots Get to Work - [EMAIL] - Gmail
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NULL
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81837
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NULL
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0
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2026-04-26T13:36:31.969054+00:00
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/Users/lukas/.screenpipe/data/data/2026-04-26/1777 /Users/lukas/.screenpipe/data/data/2026-04-26/1777210591969_m1.jpg...
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Firefox
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DXP4800PLUS-B5F8 — Personal
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True
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nas.lakylak.xyz/desktop/#/
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monitor_1
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NULL
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NULL
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NULL
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/Users/lukas/.screenpipe/data/data/2026-04-26/1777 /Users/lukas/.screenpipe/data/data/2026-04-26/1777210591969_m1.jpg...
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DXP4800PLUS-B5F8
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(57) DXP4800PLUS-B5F8
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Welcome back
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Western Digital Red Plus 3.5 6TB 5400rpm 256MB SATA3 (WD60EFPX) от 241,72 € (472,76 лв.) Вътрешен хард диск Western Digital - Pazaruvaj.com
Western Digital Red Plus 3.5 6TB 5400rpm 256MB SATA3 (WD60EFPX) от 241,72 € (472,76 лв.) Вътрешен хард диск Western Digital - Pazaruvaj.com
Today's Deals
Today's Deals
architecture - screenpipe docs
architecture - screenpipe docs
Claude Code works better when you stop treating it like a machine - [EMAIL] - Gmail
Claude Code works better when you stop treating it like a machine - [EMAIL] - Gmail
Screenpipe — Archive
Screenpipe — Archive
SQLite Web: archive.db
SQLite Web: archive.db
SQLite Web: db.sqlite
SQLite Web: db.sqlite
Claude Platform
Claude Platform
Hey @louis030195 Ill check during my - screenpipe.com
Hey @louis030195 Ill check during my - screenpipe.com
GitHub - screenpipe/screenpipe: Run agents that work for you based on what you do. AI finally knows what you are doing · GitHub
GitHub - screenpipe/screenpipe: Run agents that work for you based on what you do. AI finally knows what you are doing · GitHub
Gong Pricing in 2026: Costs, Plans & Is It Worth It?
Gong Pricing in 2026: Costs, Plans & Is It Worth It?
GLM 5.1 Thinks Strategically, Data-Center Revolt Intensifies, When Helpful LLMs Turn Unhelpful, Humanoid Robots Get to Work - [EMAIL] - Gmail
GLM 5.1 Thinks Strategically, Data-Center Revolt Intensifies, When Helpful LLMs Turn Unhelpful, Humanoid Robots Get to Work - [EMAIL] - Gmail
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lakylak/screenpipe - screenpipe - Gitea: Git with a cup of tea
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4467156295867826634
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627605934011096843
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visual_change
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accessibility
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NULL
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DXP4800PLUS-B5F8
Inbox (9) - [EMAIL] - Gmail
(57) DXP4800PLUS-B5F8
Inbox (9) - [EMAIL] - Gmail
(57) Inbox | [EMAIL] | Proton Mail
Welcome back
Welcome back
Western Digital Red Plus 3.5 6TB 5400rpm 256MB SATA3 (WD60EFPX) от 241,72 € (472,76 лв.) Вътрешен хард диск Western Digital - Pazaruvaj.com
Western Digital Red Plus 3.5 6TB 5400rpm 256MB SATA3 (WD60EFPX) от 241,72 € (472,76 лв.) Вътрешен хард диск Western Digital - Pazaruvaj.com
Today's Deals
Today's Deals
architecture - screenpipe docs
architecture - screenpipe docs
Claude Code works better when you stop treating it like a machine - [EMAIL] - Gmail
Claude Code works better when you stop treating it like a machine - [EMAIL] - Gmail
Screenpipe — Archive
Screenpipe — Archive
SQLite Web: archive.db
SQLite Web: archive.db
SQLite Web: db.sqlite
SQLite Web: db.sqlite
Claude Platform
Claude Platform
Hey @louis030195 Ill check during my - screenpipe.com
Hey @louis030195 Ill check during my - screenpipe.com
GitHub - screenpipe/screenpipe: Run agents that work for you based on what you do. AI finally knows what you are doing · GitHub
GitHub - screenpipe/screenpipe: Run agents that work for you based on what you do. AI finally knows what you are doing · GitHub
Gong Pricing in 2026: Costs, Plans & Is It Worth It?
Gong Pricing in 2026: Costs, Plans & Is It Worth It?
GLM 5.1 Thinks Strategically, Data-Center Revolt Intensifies, When Helpful LLMs Turn Unhelpful, Humanoid Robots Get to Work - [EMAIL] - Gmail
GLM 5.1 Thinks Strategically, Data-Center Revolt Intensifies, When Helpful LLMs Turn Unhelpful, Humanoid Robots Get to Work - [EMAIL] - Gmail
Gitea Official Website
Gitea Official Website
lakylak/screenpipe - screenpipe - Gitea: Git with a cup of tea
lakylak/screenpipe - screenpipe - Gitea: Git with a cup of tea
New Tab
New Tab
MikroTik · CRS304-4XG-IN
MikroTik · CRS304-4XG-IN
New Tab
Customize sidebar
Open Le Chat Mistral (⌃X)
Open history (⇧⌘H)
Open bookmarks (⌘B)
Bitwarden
753
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Files
Control Panel
Storage
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81835
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81859
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NULL
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0
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2026-04-26T13:38:13.449254+00:00
|
/Users/lukas/.screenpipe/data/data/2026-04-26/1777 /Users/lukas/.screenpipe/data/data/2026-04-26/1777210693449_m1.jpg...
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Firefox
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DXP4800PLUS-B5F8 — Personal
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True
|
nas.lakylak.xyz/desktop/#/
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monitor_1
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NULL
|
NULL
|
NULL
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/Users/lukas/.screenpipe/data/data/2026-04-26/1777 /Users/lukas/.screenpipe/data/data/2026-04-26/1777210693449_m1.jpg...
|
DXP4800PLUS-B5F8
Inbox (9) - [EMAIL] - Gmail
(57) DXP4800PLUS-B5F8
Inbox (9) - [EMAIL] - Gmail
(57) Inbox | [EMAIL] | Proton Mail
Welcome back
Welcome back
Western Digital Red Plus 3.5 6TB 5400rpm 256MB SATA3 (WD60EFPX) от 241,72 € (472,76 лв.) Вътрешен хард диск Western Digital - Pazaruvaj.com
Western Digital Red Plus 3.5 6TB 5400rpm 256MB SATA3 (WD60EFPX) от 241,72 € (472,76 лв.) Вътрешен хард диск Western Digital - Pazaruvaj.com
Today's Deals
Today's Deals
architecture - screenpipe docs
architecture - screenpipe docs
Claude Code works better when you stop treating it like a machine - [EMAIL] - Gmail
Claude Code works better when you stop treating it like a machine - [EMAIL] - Gmail
Screenpipe — Archive
Screenpipe — Archive
SQLite Web: archive.db
SQLite Web: archive.db
SQLite Web: db.sqlite
SQLite Web: db.sqlite
Claude Platform
Claude Platform
Hey @louis030195 Ill check during my - screenpipe.com
Hey @louis030195 Ill check during my - screenpipe.com
GitHub - screenpipe/screenpipe: Run agents that work for you based on what you do. AI finally knows what you are doing · GitHub
GitHub - screenpipe/screenpipe: Run agents that work for you based on what you do. AI finally knows what you are doing · GitHub
Gong Pricing in 2026: Costs, Plans & Is It Worth It?
Gong Pricing in 2026: Costs, Plans & Is It Worth It?
GLM 5.1 Thinks Strategically, Data-Center Revolt Intensifies, When Helpful LLMs Turn Unhelpful, Humanoid Robots Get to Work - [EMAIL] - Gmail
GLM 5.1 Thinks Strategically, Data-Center Revolt Intensifies, When Helpful LLMs Turn Unhelpful, Humanoid Robots Get to Work - [EMAIL] - Gmail
Gitea Official Website
Gitea Official Website
lakylak/screenpipe - screenpipe - Gitea: Git with a cup of tea
lakylak/screenpipe - screenpipe - Gitea: Git with a cup of tea
New Tab
New Tab
MikroTik · CRS304-4XG-IN
MikroTik · CRS304-4XG-IN
New Tab
Customize sidebar
Open Le Chat Mistral (⌃X)
Open history (⇧⌘H)
Open bookmarks (⌘B)
Bitwarden
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Folder
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645621415926079243
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DXP4800PLUS-B5F8
Inbox (9) - [EMAIL] - Gmail
(57) DXP4800PLUS-B5F8
Inbox (9) - [EMAIL] - Gmail
(57) Inbox | [EMAIL] | Proton Mail
Welcome back
Welcome back
Western Digital Red Plus 3.5 6TB 5400rpm 256MB SATA3 (WD60EFPX) от 241,72 € (472,76 лв.) Вътрешен хард диск Western Digital - Pazaruvaj.com
Western Digital Red Plus 3.5 6TB 5400rpm 256MB SATA3 (WD60EFPX) от 241,72 € (472,76 лв.) Вътрешен хард диск Western Digital - Pazaruvaj.com
Today's Deals
Today's Deals
architecture - screenpipe docs
architecture - screenpipe docs
Claude Code works better when you stop treating it like a machine - [EMAIL] - Gmail
Claude Code works better when you stop treating it like a machine - [EMAIL] - Gmail
Screenpipe — Archive
Screenpipe — Archive
SQLite Web: archive.db
SQLite Web: archive.db
SQLite Web: db.sqlite
SQLite Web: db.sqlite
Claude Platform
Claude Platform
Hey @louis030195 Ill check during my - screenpipe.com
Hey @louis030195 Ill check during my - screenpipe.com
GitHub - screenpipe/screenpipe: Run agents that work for you based on what you do. AI finally knows what you are doing · GitHub
GitHub - screenpipe/screenpipe: Run agents that work for you based on what you do. AI finally knows what you are doing · GitHub
Gong Pricing in 2026: Costs, Plans & Is It Worth It?
Gong Pricing in 2026: Costs, Plans & Is It Worth It?
GLM 5.1 Thinks Strategically, Data-Center Revolt Intensifies, When Helpful LLMs Turn Unhelpful, Humanoid Robots Get to Work - [EMAIL] - Gmail
GLM 5.1 Thinks Strategically, Data-Center Revolt Intensifies, When Helpful LLMs Turn Unhelpful, Humanoid Robots Get to Work - [EMAIL] - Gmail
Gitea Official Website
Gitea Official Website
lakylak/screenpipe - screenpipe - Gitea: Git with a cup of tea
lakylak/screenpipe - screenpipe - Gitea: Git with a cup of tea
New Tab
New Tab
MikroTik · CRS304-4XG-IN
MikroTik · CRS304-4XG-IN
New Tab
Customize sidebar
Open Le Chat Mistral (⌃X)
Open history (⇧⌘H)
Open bookmarks (⌘B)
Bitwarden
2.7
KB/s
6
KB/s
Files
Control Panel
Storage
App Center
Logs
Support
Task Manager
Universal Search
Music
Cloud Drives
Theater
Photos
Online Office
TextEdit
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Downloads
DLNA
File Version Explorer
Security
Jellyfin-HT
SAN Manager
Vault
Snapshot
Comics
Sync & Backup
Files
Personal Folder
Shared Folder
User Folder
Tag
Recycle Bin
Shared Folder
Shared Folder
Please enter
Name
Size
Type
Modification date
Youtube
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Folder
2026-01-15 17:57
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Folder
2026-04-25 20:37
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Folder
2026-04-24 13:44
screenpipe
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2026-04-25 20:16
Music
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2025-10-24 22:41
Movies
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2026-02-09 20:06
Media
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Folder
2025-09-27 17:56
Marti
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2025-10-24 20:06
Google
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2025-11-21 13:20
games
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2026-01-01 15:39
Family tree documents
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Folder
2026-01-25 17:51
ebooks
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Folder
2026-03-16 10:34
Documents
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Folder
2025-10-14 12:21
docker
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Folder
2026-03-30 19:14
BT
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Folder
2026-04-24 13:44
bookdrop
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Folder
2025-12-26 18:16
Backup
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Folder
2026-04-06 19:44
Audiobooks
-
Folder
2026-02-10 10:22
Apps
-
Folder
2025-08-10 22:58
Selected: 1
|
Total items: 19...
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81857
|
|
81860
|
NULL
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0
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2026-04-26T13:38:13.371520+00:00
|
/Users/lukas/.screenpipe/data/data/2026-04-26/1777 /Users/lukas/.screenpipe/data/data/2026-04-26/1777210693371_m2.jpg...
|
Firefox
|
DXP4800PLUS-B5F8 — Personal
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True
|
nas.lakylak.xyz/desktop/#/
|
monitor_2
|
NULL
|
NULL
|
NULL
|
/Users/lukas/.screenpipe/data/data/2026-04-26/1777 /Users/lukas/.screenpipe/data/data/2026-04-26/1777210693371_m2.jpg...
|
DXP4800PLUS-B5F8
Inbox (9) - [EMAIL] - Gmail
(57) DXP4800PLUS-B5F8
Inbox (9) - [EMAIL] - Gmail
(57) Inbox | [EMAIL] | Proton Mail
Welcome back
Welcome back
Western Digital Red Plus 3.5 6TB 5400rpm 256MB SATA3 (WD60EFPX) от 241,72 € (472,76 лв.) Вътрешен хард диск Western Digital - Pazaruvaj.com
Western Digital Red Plus 3.5 6TB 5400rpm 256MB SATA3 (WD60EFPX) от 241,72 € (472,76 лв.) Вътрешен хард диск Western Digital - Pazaruvaj.com
Today's Deals
Today's Deals
architecture - screenpipe docs
architecture - screenpipe docs
Claude Code works better when you stop treating it like a machine - [EMAIL] - Gmail
Claude Code works better when you stop treating it like a machine - [EMAIL] - Gmail
Screenpipe — Archive
Screenpipe — Archive
SQLite Web: archive.db
SQLite Web: archive.db
SQLite Web: db.sqlite
SQLite Web: db.sqlite
Claude Platform
Claude Platform
Hey @louis030195 Ill check during my - screenpipe.com
Hey @louis030195 Ill check during my - screenpipe.com
GitHub - screenpipe/screenpipe: Run agents that work for you based on what you do. AI finally knows what you are doing · GitHub
GitHub - screenpipe/screenpipe: Run agents that work for you based on what you do. AI finally knows what you are doing · GitHub
Gong Pricing in 2026: Costs, Plans & Is It Worth It?
Gong Pricing in 2026: Costs, Plans & Is It Worth It?
GLM 5.1 Thinks Strategically, Data-Center Revolt Intensifies, When Helpful LLMs Turn Unhelpful, Humanoid Robots Get to Work - [EMAIL] - Gmail
GLM 5.1 Thinks Strategically, Data-Center Revolt Intensifies, When Helpful LLMs Turn Unhelpful, Humanoid Robots Get to Work - [EMAIL] - Gmail
Gitea Official Website
Gitea Official Website
lakylak/screenpipe - screenpipe - Gitea: Git with a cup of tea
lakylak/screenpipe - screenpipe - Gitea: Git with a cup of tea
New Tab
New Tab
MikroTik · CRS304-4XG-IN
MikroTik · CRS304-4XG-IN
New Tab
Customize sidebar
Open Le Chat Mistral (⌃X)
Open history (⇧⌘H)
Open bookmarks (⌘B)
Bitwarden
2.7
KB/s
6
KB/s
Files
Control Panel
Storage
App Center
Logs
Support
Task Manager
Universal Search
Music
Cloud Drives
Theater
Photos
Online Office
TextEdit
Virtual Machine
Downloads
DLNA
File Version Explorer
Security
Jellyfin-HT
SAN Manager
Vault
Snapshot
Comics
Sync & Backup
Files
Personal Folder
Shared Folder
User Folder
Tag
Recycle Bin
Shared Folder
Shared Folder
Please enter
Name
Size
Type
Modification date
Youtube
-
Folder
2026-01-15 17:57
Work
-
Folder
2026-04-25 20:37
Test
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Folder
2026-04-24 13:44
screenpipe
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Folder
2026-04-25 20:16
Music
-
Folder
2025-10-24 22:41
Movies
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Folder
2026-02-09 20:06
Media
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Folder
2025-09-27 17:56
Marti
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Folder
2025-10-24 20:06
Google
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Folder
2025-11-21 13:20
games
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Folder
2026-01-01 15:39
Family tree documents
-
Folder
2026-01-25 17:51
ebooks
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Folder
2026-03-16 10:34
Documents
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Folder
2025-10-14 12:21
docker
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Folder
2026-03-30 19:14
BT
-
Folder
2026-04-24 13:44
bookdrop
-
Folder
2025-12-26 18:16
Backup
-
Folder
2026-04-06 19:44
Audiobooks
-
Folder
2026-02-10 10:22
Apps
-
Folder
2025-08-10 22:58
Selected: 1
|
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Western Digital Red Plus 3.5 6TB 5400rpm 256MB SATA3 (WD60EFPX) от 241,72 € (472,76 лв.) Вътрешен хард диск Western Digital - Pazaruvaj.com
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To have Vimium commands work on","depth":9,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"all","depth":10,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"new tab pages opened by the browser, a separate Vimium new tab extension is required. See the full details","depth":9,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXLink","text":"here","depth":9,"help_text":"","role_description":"link","subrole":"AXUnknown","is_enabled":true,"is_focused":false,"is_selected":false},{"role":"AXStaticText","text":"here","depth":10,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":".","depth":9,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"Advanced Options","depth":9,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXHeading","text":"Scroll step size","depth":8,"help_text":"","role_description":"heading","subrole":"AXUnknown"},{"role":"AXStaticText","text":"Scroll step 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patterns","depth":9,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXTextField","text":"prev,previous,back,older,<,‹,←,«,≪,<<","depth":9,"value":"prev,previous,back,older,<,‹,←,«,≪,<<","help_text":"","role_description":"text field","subrole":"AXUnknown","is_enabled":true,"is_focused":false,"is_selected":false},{"role":"AXLink","text":"Reset","depth":10,"bounds":{"left":0.20347223,"top":0.0,"width":0.021527778,"height":0.015555556},"help_text":"","role_description":"link","subrole":"AXUnknown","is_enabled":true,"is_focused":false,"is_selected":false},{"role":"AXStaticText","text":"Reset","depth":11,"bounds":{"left":0.20347223,"top":0.0,"width":0.021527778,"height":0.015555556},"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"The \"navigate to previous page\" command uses these patterns to find the link to follow.","depth":9,"bounds":{"left":0.23888889,"top":0.0,"width":0.19930555,"height":0.033333335},"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXHeading","text":"Next patterns","depth":8,"help_text":"","role_description":"heading","subrole":"AXUnknown"},{"role":"AXStaticText","text":"Next patterns","depth":9,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXTextField","text":"next,more,newer,>,›,→,»,≫,>>","depth":9,"value":"next,more,newer,>,›,→,»,≫,>>","help_text":"","role_description":"text 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UI","depth":9,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXTextArea","text":"div > .vimiumHintMarker {\n/* linkhint boxes */\nbackground: -webkit-gradient(linear, left top, left bottom, color-stop(0%,#FFF785),\n color-stop(100%,#FFC542));\nborder: 1px solid #E3BE23;\n}\n\ndiv > .vimiumHintMarker span {\n/* linkhint text */\ncolor: black;\nfont-weight: bold;\nfont-size: 12px;\n}\n\ndiv > .vimiumHintMarker > .matchingCharacter {\n}","depth":9,"value":"div > .vimiumHintMarker {\n/* linkhint boxes */\nbackground: -webkit-gradient(linear, left top, left bottom, color-stop(0%,#FFF785),\n color-stop(100%,#FFC542));\nborder: 1px solid #E3BE23;\n}\n\ndiv > .vimiumHintMarker span {\n/* linkhint text */\ncolor: black;\nfont-weight: bold;\nfont-size: 12px;\n}\n\ndiv > .vimiumHintMarker > .matchingCharacter {\n}","help_text":"","role_description":"text entry 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2697377210287229636
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click
|
accessibility
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NULL
|
DXP4800PLUS-B5F8
Inbox (1) - [EMAIL] - Gmail
Edit DXP4800PLUS-B5F8
Inbox (1) - [EMAIL] - Gmail
Edit profile
Edit profile
How to Get Through the Product Management Bottleneck
How to Get Through the Product Management Bottleneck
Časť 2 • HBO Max
Časť 2 • HBO Max
Settings
Settings
firefox sidebar - Google Search
firefox sidebar - Google Search
How to use AI-enhanced tab groups | Firefox Help
How to use AI-enhanced tab groups | Firefox Help
Add-ons Manager
Add-ons Manager
Vimium – Get this Extension for 🦊 Firefox (en-US)
Vimium – Get this Extension for 🦊 Firefox (en-US)
Maďarské voľby – Denník N
Maďarské voľby – Denník N
Vimium Options
Vimium Options
Close tab
Loď Orion úspešne pristála na Zemi. Desať vecí, ktoré si pamätať o misii Artemis II — Denník N
Loď Orion úspešne pristála na Zemi. Desať vecí, ktoré si pamätať o misii Artemis II — Denník N
Problem loading page
Problem loading page
Machines - Tailscale
Machines - Tailscale
New Tab
New Tab
Screenpipe Dashboard
Screenpipe Dashboard
New Tab
New Tab
New Tab
New Tab
New Tab
Customize sidebar
Open Google Gemini (⌃X)
Tabs from other devices
Open history (⇧⌘H)
Open bookmarks (⌘B)
Vimium Options
Excluded URLs and keys
Excluded URLs and keys
Patterns
Keys to exclude
https?://mail.google.com/*
All
✖
Patterns
https?://mail.google.com/*
Keys to exclude
All
✖
Add rule
Disable Vimium on URLs.
"Patterns" are URL regular expressions.
*
will match zero or more characters.
"Keys": Vimium will exclude these keys and pass them through to the page.
Custom key mappings
Custom key mappings
# Insert your preferred key mappings here.
Example syntax:
map j scrollDown
map z2 setZoom level=2
unmap j
unmapAll
" this is a comment
# this is also a comment
See all available commands
See all available commands
.
Custom search engines
Custom search engines
w: https://www.wikipedia.org/w/index.php?title=Special:Search&search=%s Wikipedia
# More examples.
#
# (Vimium supports search completion Wikipedia, as
# above, and for these.)
#
# g: https://www.google.com/search?q=%s Google
# l: https://www.google.com/search?q=%s&btnI I'm feeling lucky...
# y: https://www.youtube.com/results?search_query=%s Youtube
# gm: https://www.google.com/maps?q=%s Google maps
# b: https://www.bing.com/search?q=%s Bing
# d: https://duckduckgo.com/?q=%s DuckDuckGo
# az: https://www.amazon.com/s/?field-keywords=%s
# qw: https://www.qwant.com/?q=%s Qwant
Add search-engine shortcuts to the Vomnibar. Format:
a: http://a.com/?q=%s
b: http://b.com/?q=%s description
" this is a comment
# this is also a comment
%s is replaced with the search terms.
For search completion, see
here
here
.
New tab URL
New tab URL
Vimium blank new tab page
Vimium blank new tab page
Open the Vomnibar when the page loads
Open the Vomnibar when the page loads
Browser's default new tab page
Browser's default new tab page
Custom URL
Custom URL
The page to open when using Vimium's "create new tab" command. To have Vimium commands work on
all
new tab pages opened by the browser, a separate Vimium new tab extension is required. See the full details
here
here
.
Advanced Options
Scroll step size
Scroll step size
60
px
The size for basic movements (usually j/k/h/l).
Characters used for link hints
Characters used for link hints
sadfjklewcmpgh
Reset
Reset
The characters placed next to each link after typing "f" to enter link-hint mode.
Use smooth scrolling
Use smooth scrolling
Use the link's name and characters for link-hint filtering
Use the link's name and characters for link-hint filtering
In link-hint mode, this option lets you select a link by typing its text.
Don't let pages steal the focus on load
Don't let pages steal the focus on load
Prevent pages from focusing an input on load (e.g. Google, Bing, etc.).
Hide the Heads Up Display (HUD) in insert mode
Hide the Heads Up Display (HUD) in insert mode
When enabled, the HUD will not be displayed in insert mode.
Hide update notifications
Hide update notifications
When enabled, "Vimium has been updated" notifications will not be shown.
Treat find queries as JavaScript regular expressions
Treat find queries as JavaScript regular expressions
Switch back to plain find mode by using the
\R
escape sequence.
Ignore keyboard layout
Ignore keyboard layout
This forces the use of
en-US
QWERTY layout and can be helpful for non-Latin keyboards.
Previous patterns
Previous patterns
prev,previous,back,older,<,‹,←,«,≪,<<
Reset
Reset
The "navigate to previous page" command uses these patterns to find the link to follow.
Next patterns
Next patterns
next,more,newer,>,›,→,»,≫,>>
Reset
Reset
The "navigate to next page" command uses these patterns to find the link to follow.
CSS for Vimium UI
CSS for Vimium UI
div > .vimiumHintMarker {
/* linkhint boxes */
background: -webkit-gradient(linear, left top, left bottom, color-stop(0%,#FFF785),
color-stop(100%,#FFC542));
border: 1px solid #E3BE23;
}
div > .vimiumHintMarker span {
/* linkhint text */
color: black;
font-weight: bold;
font-size: 12px;
}
div > .vimiumHintMarker > .matchingCharacter {
}
Reset
Reset
These styles are applied to link hints, the Vomnibar, the help dialog, the exclusions pop-up and the HUD.
By default, this CSS is used to style the characters next to each link hint.
These styles are used in addition to and take precedence over Vimium's default styles.
[SEED_PHRASE].
Restore
Restore
Browse… No file selected.
Browse…
No file selected.
Choose a backup file to restore.
Type
?
to show the help dialog.
Type
Cmd-Enter
to save all options.
No changes...
|
NULL
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1353
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30
|
7
|
2026-04-11T15:34:19.938617+00:00
|
/Users/lukas/.screenpipe/data/data/2026-04-11/1775 /Users/lukas/.screenpipe/data/data/2026-04-11/1775921659938_m1.jpg...
|
Firefox
|
Vimium Options — Personal
|
True
|
moz-extension://f5e9c63e-b25b-4f15-8ba2-4813105e11 moz-extension://f5e9c63e-b25b-4f15-8ba2-4813105e11bb/pages/options.html...
|
monitor_1
|
NULL
|
NULL
|
NULL
|
NULL
|
DXP4800PLUS-B5F8
Inbox (1) - [EMAIL] - Gmail
Edit DXP4800PLUS-B5F8
Inbox (1) - [EMAIL] - Gmail
Edit profile
Edit profile
How to Get Through the Product Management Bottleneck
How to Get Through the Product Management Bottleneck
Časť 2 • HBO Max
Časť 2 • HBO Max
Settings
Settings
firefox sidebar - Google Search
firefox sidebar - Google Search
How to use AI-enhanced tab groups | Firefox Help
How to use AI-enhanced tab groups | Firefox Help
Add-ons Manager
Add-ons Manager
Vimium – Get this Extension for 🦊 Firefox (en-US)
Vimium – Get this Extension for 🦊 Firefox (en-US)
Maďarské voľby – Denník N
Maďarské voľby – Denník N
Vimium Options
Vimium Options
Close tab
Loď Orion úspešne pristála na Zemi. Desať vecí, ktoré si pamätať o misii Artemis II — Denník N
Loď Orion úspešne pristála na Zemi. Desať vecí, ktoré si pamätať o misii Artemis II — Denník N
Problem loading page
Problem loading page
Machines - Tailscale
Machines - Tailscale
New Tab
New Tab
Screenpipe Dashboard
Screenpipe Dashboard
New Tab
New Tab
New Tab
New Tab
New Tab
Customize sidebar
Open Google Gemini (⌃X)
Tabs from other devices
Open history (⇧⌘H)
Open bookmarks (⌘B)
Vimium Options
Excluded URLs and keys
Excluded URLs and keys
Patterns
Keys to exclude
https?://mail.google.com/*
All
✖
Patterns
https?://mail.google.com/*
Keys to exclude
All
✖
Add rule
Disable Vimium on URLs.
"Patterns" are URL regular expressions.
*
will match zero or more characters.
"Keys": Vimium will exclude these keys and pass them through to the page.
Custom key mappings
Custom key mappings
# Insert your preferred key mappings here.
Example syntax:
map j scrollDown
map z2 setZoom level=2
unmap j
unmapAll
" this is a comment
# this is also a comment
See all available commands
See all available commands
.
Custom search engines
Custom search engines
w: https://www.wikipedia.org/w/index.php?title=Special:Search&search=%s Wikipedia
# More examples.
#
# (Vimium supports search completion Wikipedia, as
# above, and for these.)
#
# g: https://www.google.com/search?q=%s Google
# l: https://www.google.com/search?q=%s&btnI I'm feeling lucky...
# y: https://www.youtube.com/results?search_query=%s Youtube
# gm: https://www.google.com/maps?q=%s Google maps
# b: https://www.bing.com/search?q=%s Bing
# d: https://duckduckgo.com/?q=%s DuckDuckGo
# az: https://www.amazon.com/s/?field-keywords=%s
# qw: https://www.qwant.com/?q=%s Qwant
Add search-engine shortcuts to the Vomnibar. Format:
a: http://a.com/?q=%s
b: http://b.com/?q=%s description
" this is a comment
# this is also a comment
%s is replaced with the search terms.
For search completion, see
here
here
.
New tab URL
New tab URL
Vimium blank new tab page
Vimium blank new tab page
Open the Vomnibar when the page loads
Open the Vomnibar when the page loads
Browser's default new tab page
Browser's default new tab page
Custom URL
Custom URL
The page to open when using Vimium's "create new tab" command. To have Vimium commands work on
all
new tab pages opened by the browser, a separate Vimium new tab extension is required. See the full details
here
here
.
Advanced Options
Scroll step size
Scroll step size
60
px
The size for basic movements (usually j/k/h/l).
Characters used for link hints
Characters used for link hints
sadfjklewcmpgh
Reset
Reset
The characters placed next to each link after typing "f" to enter link-hint mode.
Use smooth scrolling
Use smooth scrolling
Use the link's name and characters for link-hint filtering
Use the link's name and characters for link-hint filtering...
|
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https://www.qwant.com/?q=%s Qwant","help_text":"","role_description":"text entry area","subrole":"AXUnknown","is_enabled":true,"is_focused":false,"is_selected":false},{"role":"AXStaticText","text":"Add search-engine shortcuts to the Vomnibar. Format:","depth":9,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"a: http://a.com/?q=%s\nb: http://b.com/?q=%s description\n\" this is a comment\n# this is also a comment","depth":10,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"%s is replaced with the search terms.","depth":9,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"For search completion, see","depth":9,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXLink","text":"here","depth":9,"help_text":"","role_description":"link","subrole":"AXUnknown","is_enabled":true,"is_focused":false,"is_selected":false},{"role":"AXStaticText","text":"here","depth":10,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":".","depth":9,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXHeading","text":"New tab URL","depth":8,"help_text":"","role_description":"heading","subrole":"AXUnknown"},{"role":"AXStaticText","text":"New tab URL","depth":9,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXRadioButton","text":"Vimium blank new tab page","depth":9,"help_text":"","role_description":"radio button","subrole":"AXUnknown","is_enabled":true,"is_focused":false,"is_selected":false},{"role":"AXStaticText","text":"Vimium blank new tab page","depth":10,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXCheckBox","text":"Open the Vomnibar when the page loads","depth":10,"help_text":"","role_description":"checkbox","subrole":"AXUnknown","is_enabled":true,"is_focused":false,"is_selected":false},{"role":"AXStaticText","text":"Open the Vomnibar when the page loads","depth":11,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXRadioButton","text":"Browser's default new tab page","depth":9,"help_text":"","role_description":"radio button","subrole":"AXUnknown","is_enabled":true,"is_focused":false,"is_selected":false},{"role":"AXStaticText","text":"Browser's default new tab page","depth":10,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXRadioButton","text":"Custom URL","depth":9,"help_text":"","role_description":"radio button","subrole":"AXUnknown","is_enabled":true,"is_focused":false,"is_selected":false},{"role":"AXStaticText","text":"Custom URL","depth":10,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"The page to open when using Vimium's \"create new tab\" command. To have Vimium commands work on","depth":9,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"all","depth":10,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"new tab pages opened by the browser, a separate Vimium new tab extension is required. See the full details","depth":9,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXLink","text":"here","depth":9,"help_text":"","role_description":"link","subrole":"AXUnknown","is_enabled":true,"is_focused":false,"is_selected":false},{"role":"AXStaticText","text":"here","depth":10,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":".","depth":9,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"Advanced Options","depth":9,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXHeading","text":"Scroll step size","depth":8,"help_text":"","role_description":"heading","subrole":"AXUnknown"},{"role":"AXStaticText","text":"Scroll step size","depth":9,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"60","depth":10,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"px","depth":9,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"The size for basic movements (usually j/k/h/l).","depth":9,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXHeading","text":"Characters used for link hints","depth":9,"help_text":"","role_description":"heading","subrole":"AXUnknown"},{"role":"AXStaticText","text":"Characters used for link hints","depth":10,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXTextField","text":"sadfjklewcmpgh","depth":10,"value":"sadfjklewcmpgh","help_text":"","role_description":"text field","subrole":"AXUnknown","is_enabled":true,"is_focused":false,"is_selected":false},{"role":"AXLink","text":"Reset","depth":11,"help_text":"","role_description":"link","subrole":"AXUnknown","is_enabled":true,"is_focused":false,"is_selected":false},{"role":"AXStaticText","text":"Reset","depth":12,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"The characters placed next to each link after typing \"f\" to enter link-hint mode.","depth":10,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXCheckBox","text":"Use smooth scrolling","depth":9,"help_text":"","role_description":"checkbox","subrole":"AXUnknown","is_enabled":true,"is_focused":false,"is_selected":false},{"role":"AXStaticText","text":"Use smooth scrolling","depth":9,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXCheckBox","text":"Use the link's name and characters for link-hint filtering","depth":9,"help_text":"","role_description":"checkbox","subrole":"AXUnknown","is_enabled":true,"is_focused":false,"is_selected":false},{"role":"AXStaticText","text":"Use the link's name and characters for link-hint filtering","depth":9,"help_text":"","role_description":"text","subrole":"AXUnknown"}]...
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188198251522572350
|
4425634116888988406
|
click
|
accessibility
|
NULL
|
DXP4800PLUS-B5F8
Inbox (1) - [EMAIL] - Gmail
Edit DXP4800PLUS-B5F8
Inbox (1) - [EMAIL] - Gmail
Edit profile
Edit profile
How to Get Through the Product Management Bottleneck
How to Get Through the Product Management Bottleneck
Časť 2 • HBO Max
Časť 2 • HBO Max
Settings
Settings
firefox sidebar - Google Search
firefox sidebar - Google Search
How to use AI-enhanced tab groups | Firefox Help
How to use AI-enhanced tab groups | Firefox Help
Add-ons Manager
Add-ons Manager
Vimium – Get this Extension for 🦊 Firefox (en-US)
Vimium – Get this Extension for 🦊 Firefox (en-US)
Maďarské voľby – Denník N
Maďarské voľby – Denník N
Vimium Options
Vimium Options
Close tab
Loď Orion úspešne pristála na Zemi. Desať vecí, ktoré si pamätať o misii Artemis II — Denník N
Loď Orion úspešne pristála na Zemi. Desať vecí, ktoré si pamätať o misii Artemis II — Denník N
Problem loading page
Problem loading page
Machines - Tailscale
Machines - Tailscale
New Tab
New Tab
Screenpipe Dashboard
Screenpipe Dashboard
New Tab
New Tab
New Tab
New Tab
New Tab
Customize sidebar
Open Google Gemini (⌃X)
Tabs from other devices
Open history (⇧⌘H)
Open bookmarks (⌘B)
Vimium Options
Excluded URLs and keys
Excluded URLs and keys
Patterns
Keys to exclude
https?://mail.google.com/*
All
✖
Patterns
https?://mail.google.com/*
Keys to exclude
All
✖
Add rule
Disable Vimium on URLs.
"Patterns" are URL regular expressions.
*
will match zero or more characters.
"Keys": Vimium will exclude these keys and pass them through to the page.
Custom key mappings
Custom key mappings
# Insert your preferred key mappings here.
Example syntax:
map j scrollDown
map z2 setZoom level=2
unmap j
unmapAll
" this is a comment
# this is also a comment
See all available commands
See all available commands
.
Custom search engines
Custom search engines
w: https://www.wikipedia.org/w/index.php?title=Special:Search&search=%s Wikipedia
# More examples.
#
# (Vimium supports search completion Wikipedia, as
# above, and for these.)
#
# g: https://www.google.com/search?q=%s Google
# l: https://www.google.com/search?q=%s&btnI I'm feeling lucky...
# y: https://www.youtube.com/results?search_query=%s Youtube
# gm: https://www.google.com/maps?q=%s Google maps
# b: https://www.bing.com/search?q=%s Bing
# d: https://duckduckgo.com/?q=%s DuckDuckGo
# az: https://www.amazon.com/s/?field-keywords=%s
# qw: https://www.qwant.com/?q=%s Qwant
Add search-engine shortcuts to the Vomnibar. Format:
a: http://a.com/?q=%s
b: http://b.com/?q=%s description
" this is a comment
# this is also a comment
%s is replaced with the search terms.
For search completion, see
here
here
.
New tab URL
New tab URL
Vimium blank new tab page
Vimium blank new tab page
Open the Vomnibar when the page loads
Open the Vomnibar when the page loads
Browser's default new tab page
Browser's default new tab page
Custom URL
Custom URL
The page to open when using Vimium's "create new tab" command. To have Vimium commands work on
all
new tab pages opened by the browser, a separate Vimium new tab extension is required. See the full details
here
here
.
Advanced Options
Scroll step size
Scroll step size
60
px
The size for basic movements (usually j/k/h/l).
Characters used for link hints
Characters used for link hints
sadfjklewcmpgh
Reset
Reset
The characters placed next to each link after typing "f" to enter link-hint mode.
Use smooth scrolling
Use smooth scrolling
Use the link's name and characters for link-hint filtering
Use the link's name and characters for link-hint filtering...
|
1352
|
|
1355
|
30
|
9
|
2026-04-11T15:34:25.437106+00:00
|
/Users/lukas/.screenpipe/data/data/2026-04-11/1775 /Users/lukas/.screenpipe/data/data/2026-04-11/1775921665437_m1.jpg...
|
Firefox
|
Vimium Options — Personal
|
True
|
moz-extension://f5e9c63e-b25b-4f15-8ba2-4813105e11 moz-extension://f5e9c63e-b25b-4f15-8ba2-4813105e11bb/pages/options.html...
|
monitor_1
|
NULL
|
NULL
|
NULL
|
NULL
|
DXP4800PLUS-B5F8
Inbox (1) - [EMAIL] - Gmail
Edit DXP4800PLUS-B5F8
Inbox (1) - [EMAIL] - Gmail
Edit profile
Edit profile
How to Get Through the Product Management Bottleneck
How to Get Through the Product Management Bottleneck
Časť 2 • HBO Max
Časť 2 • HBO Max
Settings
Settings
firefox sidebar - Google Search
firefox sidebar - Google Search
How to use AI-enhanced tab groups | Firefox Help
How to use AI-enhanced tab groups | Firefox Help
Add-ons Manager
Add-ons Manager
Vimium – Get this Extension for 🦊 Firefox (en-US)
Vimium – Get this Extension for 🦊 Firefox (en-US)
Maďarské voľby – Denník N
Maďarské voľby – Denník N
Vimium Options
Vimium Options
Close tab
Loď Orion úspešne pristála na Zemi. Desať vecí, ktoré si pamätať o misii Artemis II — Denník N
Loď Orion úspešne pristála na Zemi. Desať vecí, ktoré si pamätať o misii Artemis II — Denník N
Problem loading page
Problem loading page
Machines - Tailscale
Machines - Tailscale
New Tab
New Tab
Screenpipe Dashboard
Screenpipe Dashboard
New Tab
New Tab
New Tab
New Tab
New Tab
Customize sidebar
Close Google Gemini (⌃X)
Tabs from other devices
Open history (⇧⌘H)
Open bookmarks (⌘B)
AI Chat settings
Close
Google Account: Lukáš Koválik ([EMAIL])
Main menu
New chat
Gemini
Temporary chat
PLUS
PLUS
Conversation with Gemini
Conversation with Gemini
Hi Lukáš
Where should we start?
Where should we start?
🖼️ Create image, button, tap to use tool
🖼️ Create image
🎸 Create music, button, tap to use tool
🎸 Create music
Write anything, button, tap to use tool
Write anything
Boost my day, button, tap to use tool
Boost my day
Help me learn, button, tap to use tool
Help me learn
Create a video, button, tap to use tool
Create a video
Ask Gemini
Ask Gemini
Open upload file menu
Tools
Open mode picker
Pro
Microphone
Summarize page
Summarize page
Vimium Options
Excluded URLs and keys
Excluded URLs and keys
Patterns
Keys to exclude
https?://mail.google.com/*
All
✖
Patterns
https?://mail.google.com/*
Keys to exclude
All
✖
Add rule
Disable Vimium on URLs.
"Patterns" are URL regular expressions.
*
will match zero or more characters.
"Keys": Vimium will exclude these keys and pass them through to the page.
Custom key mappings
Custom key mappings
# Insert your preferred key mappings here.
Example syntax:
map j scrollDown
map z2 setZoom level=2
unmap j
unmapAll
" this is a comment
# this is also a comment
See all available commands
See all available commands
.
Custom search engines
Custom search engines
w: https://www.wikipedia.org/w/index.php?title=Special:Search&search=%s Wikipedia
# More examples.
#
# (Vimium supports search completion Wikipedia, as
# above, and for these.)
#
# g: https://www.google.com/search?q=%s Google
# l: https://www.google.com/search?q=%s&btnI I'm feeling lucky...
# y: https://www.youtube.com/results?search_query=%s Youtube
# gm: https://www.google.com/maps?q=%s Google maps
# b: https://www.bing.com/search?q=%s Bing
# d: https://duckduckgo.com/?q=%s DuckDuckGo
# az: https://www.amazon.com/s/?field-keywords=%s
# qw: https://www.qwant.com/?q=%s Qwant
Add search-engine shortcuts to the Vomnibar. Format:
a: http://a.com/?q=%s
b: http://b.com/?q=%s description
" this is a comment
# this is also a comment
%s is replaced with the search terms.
For search completion, see
here
here
.
New tab URL
New tab URL
Vimium blank new tab page
Vimium blank new tab page
Open the Vomnibar when the page loads
Open the Vomnibar when the page loads
Browser's default new tab page
Browser's default new tab page
Custom URL
Custom URL
The page to open when using Vimium's "create new tab" command. To have Vimium commands work on
all
new tab pages opened by the browser, a separate Vimium new tab extension is required. See the full details
here
here
.
Advanced Options
Scroll step size
Scroll step size
60
px
The size for basic movements (usually j/k/h/l).
Characters used for link hints
Characters used for link hints
sadfjklewcmpgh
Reset
Reset
The characters placed next to each link after typing "f" to enter link-hint mode.
Use smooth scrolling
Use smooth scrolling
Use the link's name and characters for link-hint filtering
Use the link's name and characters for link-hint filtering
In link-hint mode, this option lets you select a link by typing its text.
Don't let pages steal the focus on load
Don't let pages steal the focus on load
Prevent pages from focusing an input on load (e.g. Google, Bing, etc.).
Hide the Heads Up Display (HUD) in insert mode
Hide the Heads Up Display (HUD) in insert mode
When enabled, the HUD will not be displayed in insert mode.
Hide update notifications
Hide update notifications
When enabled, "Vimium has been updated" notifications will not be shown.
Treat find queries as JavaScript regular expressions
Treat find queries as JavaScript regular expressions
Switch back to plain find mode by using the
\R
escape sequence.
Ignore keyboard layout
Ignore keyboard layout
This forces the use of
en-US
QWERTY layout and can be helpful for non-Latin keyboards.
Previous patterns
Previous patterns
prev,previous,back,older,<,‹,←,«,≪,<<
Reset
Reset
The "navigate to previous page" command uses these patterns to find the link to follow.
Next patterns
Next patterns
next,more,newer,>,›,→,»,≫,>>
Reset
Reset
The "navigate to next page" command uses these patterns to find the link to follow.
CSS for Vimium UI
CSS for Vimium UI
div > .vimiumHintMarker {
/* linkhint boxes */
background: -webkit-gradient(linear, left top, left bottom, color-stop(0%,#FFF785),
color-stop(100%,#FFC542));
border: 1px solid #E3BE23;
}
div > .vimiumHintMarker span {
/* linkhint text */
color: black;
font-weight: bold;
font-size: 12px;
}
div > .vimiumHintMarker > .matchingCharacter {
}
Reset
Reset
These styles are applied to link hints, the Vomnibar, the help dialog, the exclusions pop-up and the HUD.
By default, this CSS is used to style the characters next to each link hint.
These styles are used in addition to and take precedence over Vimium's default styles.
[SEED_PHRASE].
Restore
Restore
Browse… No file selected.
Browse…
No file selected.
Choose a backup file to restore.
Type
?
to show the help dialog.
Type
Cmd-Enter
to save all options.
No changes...
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etc.).","depth":9,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXCheckBox","text":"Hide the Heads Up Display (HUD) in insert mode","depth":9,"help_text":"","role_description":"checkbox","subrole":"AXUnknown","is_enabled":true,"is_focused":false,"is_selected":false},{"role":"AXStaticText","text":"Hide the Heads Up Display (HUD) in insert mode","depth":9,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"When enabled, the HUD will not be displayed in insert mode.","depth":9,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXCheckBox","text":"Hide update notifications","depth":9,"help_text":"","role_description":"checkbox","subrole":"AXUnknown","is_enabled":true,"is_focused":false,"is_selected":false},{"role":"AXStaticText","text":"Hide update notifications","depth":9,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"When enabled, \"Vimium has been 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layout","depth":9,"help_text":"","role_description":"checkbox","subrole":"AXUnknown","is_enabled":true,"is_focused":false,"is_selected":false},{"role":"AXStaticText","text":"Ignore keyboard layout","depth":9,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"This forces the use of","depth":9,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"en-US","depth":10,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"QWERTY layout and can be helpful for non-Latin keyboards.","depth":9,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXHeading","text":"Previous patterns","depth":8,"bounds":{"left":0.05277778,"top":0.0,"width":0.39375,"height":0.022222223},"help_text":"","role_description":"heading","subrole":"AXUnknown"},{"role":"AXStaticText","text":"Previous patterns","depth":9,"bounds":{"left":0.05277778,"top":0.0,"width":0.08680555,"height":0.02111111},"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXTextField","text":"prev,previous,back,older,<,‹,←,«,≪,<<","depth":9,"bounds":{"left":0.05277778,"top":0.0,"width":0.17152777,"height":0.026666667},"value":"prev,previous,back,older,<,‹,←,«,≪,<<","help_text":"","role_description":"text field","subrole":"AXUnknown","is_enabled":true,"is_focused":false,"is_selected":false},{"role":"AXLink","text":"Reset","depth":10,"bounds":{"left":0.20277777,"top":0.0,"width":0.021527778,"height":0.015555556},"help_text":"","role_description":"link","subrole":"AXUnknown","is_enabled":true,"is_focused":false,"is_selected":false},{"role":"AXStaticText","text":"Reset","depth":11,"bounds":{"left":0.20277777,"top":0.0,"width":0.021527778,"height":0.015555556},"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"The \"navigate to previous page\" command uses these patterns to find the link to follow.","depth":9,"bounds":{"left":0.23819445,"top":0.0,"width":0.19930555,"height":0.033333335},"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXHeading","text":"Next patterns","depth":8,"bounds":{"left":0.05277778,"top":0.022222223,"width":0.39375,"height":0.022222223},"help_text":"","role_description":"heading","subrole":"AXUnknown"},{"role":"AXStaticText","text":"Next patterns","depth":9,"bounds":{"left":0.05277778,"top":0.022222223,"width":0.065972224,"height":0.02111111},"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXTextField","text":"next,more,newer,>,›,→,»,≫,>>","depth":9,"bounds":{"left":0.05277778,"top":0.057777777,"width":0.17152777,"height":0.026666667},"value":"next,more,newer,>,›,→,»,≫,>>","help_text":"","role_description":"text field","subrole":"AXUnknown","is_enabled":true,"is_focused":false,"is_selected":false},{"role":"AXLink","text":"Reset","depth":10,"bounds":{"left":0.20277777,"top":0.08555555,"width":0.021527778,"height":0.015555556},"help_text":"","role_description":"link","subrole":"AXUnknown","is_enabled":true,"is_focused":false,"is_selected":false},{"role":"AXStaticText","text":"Reset","depth":11,"bounds":{"left":0.20277777,"top":0.08555555,"width":0.021527778,"height":0.015555556},"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"The \"navigate to next page\" command uses these patterns to find the link to follow.","depth":9,"bounds":{"left":0.23819445,"top":0.05888889,"width":0.18402778,"height":0.033333335},"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXHeading","text":"CSS for Vimium UI","depth":8,"bounds":{"left":0.05277778,"top":0.115555555,"width":0.39375,"height":0.022222223},"help_text":"","role_description":"heading","subrole":"AXUnknown"},{"role":"AXStaticText","text":"CSS for Vimium UI","depth":9,"bounds":{"left":0.05277778,"top":0.115555555,"width":0.093055554,"height":0.02111111},"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXTextArea","text":"div > .vimiumHintMarker {\n/* linkhint boxes */\nbackground: -webkit-gradient(linear, left top, left bottom, color-stop(0%,#FFF785),\n color-stop(100%,#FFC542));\nborder: 1px solid #E3BE23;\n}\n\ndiv > .vimiumHintMarker span {\n/* linkhint text */\ncolor: black;\nfont-weight: bold;\nfont-size: 12px;\n}\n\ndiv > .vimiumHintMarker > .matchingCharacter {\n}","depth":9,"bounds":{"left":0.05277778,"top":0.15222222,"width":0.17152777,"height":0.15555556},"value":"div > .vimiumHintMarker {\n/* linkhint boxes */\nbackground: -webkit-gradient(linear, left top, left bottom, color-stop(0%,#FFF785),\n color-stop(100%,#FFC542));\nborder: 1px solid #E3BE23;\n}\n\ndiv > .vimiumHintMarker span {\n/* linkhint text */\ncolor: black;\nfont-weight: bold;\nfont-size: 12px;\n}\n\ndiv > .vimiumHintMarker > .matchingCharacter {\n}","help_text":"","role_description":"text entry area","subrole":"AXUnknown","is_enabled":true,"is_focused":false,"is_selected":false},{"role":"AXLink","text":"Reset","depth":10,"bounds":{"left":0.20277777,"top":0.31,"width":0.021527778,"height":0.015555556},"help_text":"","role_description":"link","subrole":"AXUnknown","is_enabled":true,"is_focused":false,"is_selected":false},{"role":"AXStaticText","text":"Reset","depth":11,"bounds":{"left":0.20277777,"top":0.31,"width":0.021527778,"height":0.015555556},"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"These styles are applied to link hints, the Vomnibar, the help dialog, the exclusions pop-up and the HUD.","depth":9,"bounds":{"left":0.23819445,"top":0.15222222,"width":0.20347223,"height":0.033333335},"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"By default, this CSS is used to style the characters next to each link hint.","depth":9,"bounds":{"left":0.23819445,"top":0.18777777,"width":0.2048611,"height":0.033333335},"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"These styles are used in addition to and take precedence over Vimium's default styles.","depth":9,"bounds":{"left":0.23819445,"top":0.24111111,"width":0.16527778,"height":0.033333335},"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"Backup and Restore","depth":9,"bounds":{"left":0.05277778,"top":0.34888887,"width":0.11319444,"height":0.023333333},"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXHeading","text":"Backup","depth":8,"bounds":{"left":0.05277778,"top":0.40333334,"width":0.39375,"height":0.022222223},"help_text":"","role_description":"heading","subrole":"AXUnknown"},{"role":"AXStaticText","text":"Backup","depth":9,"bounds":{"left":0.05277778,"top":0.40444446,"width":0.036805555,"height":0.02111111},"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXLink","text":"Download backup","depth":8,"bounds":{"left":0.05277778,"top":0.43888888,"width":0.17152777,"height":0.017777778},"help_text":"","role_description":"link","subrole":"AXUnknown","is_enabled":true,"is_focused":false,"is_selected":false},{"role":"AXStaticText","text":"Download backup","depth":9,"bounds":{"left":0.05277778,"top":0.43888888,"width":0.077083334,"height":0.017777778},"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"Download a backup of your settings.","depth":9,"bounds":{"left":0.23819445,"top":0.44,"width":0.13402778,"height":0.015555556},"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXHeading","text":"Restore","depth":8,"bounds":{"left":0.05277778,"top":0.47,"width":0.39375,"height":0.022222223},"help_text":"","role_description":"heading","subrole":"AXUnknown"},{"role":"AXStaticText","text":"Restore","depth":9,"bounds":{"left":0.05277778,"top":0.47111112,"width":0.03888889,"height":0.02111111},"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXButton","text":"Browse… No file selected.","depth":8,"bounds":{"left":0.05277778,"top":0.50555557,"width":0.17152777,"height":0.024444444},"help_text":"","role_description":"button","subrole":"AXUnknown","is_enabled":true,"is_focused":false,"is_selected":false},{"role":"AXStaticText","text":"Browse…","depth":9,"bounds":{"left":0.056944445,"top":0.5088889,"width":0.03888889,"height":0.017777778},"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"No file selected.","depth":9,"bounds":{"left":0.103472225,"top":0.5088889,"width":0.07013889,"height":0.017777778},"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"Choose a backup file to restore.","depth":9,"bounds":{"left":0.23819445,"top":0.50666666,"width":0.11736111,"height":0.015555556},"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"Type","depth":10,"bounds":{"left":0.05277778,"top":0.0,"width":0.02013889,"height":0.015555556},"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"?","depth":11,"bounds":{"left":0.072916664,"top":0.0,"width":0.0055555557,"height":0.015555556},"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"to show the help dialog.","depth":10,"bounds":{"left":0.07847222,"top":0.0,"width":0.08958333,"height":0.015555556},"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"Type","depth":10,"bounds":{"left":0.05277778,"top":0.0,"width":0.02013889,"height":0.015555556},"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"Cmd-Enter","depth":11,"bounds":{"left":0.072916664,"top":0.0,"width":0.043055557,"height":0.015555556},"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"to save all options.","depth":10,"bounds":{"left":0.11597222,"top":0.0,"width":0.07083333,"height":0.015555556},"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXButton","text":"No changes","depth":10,"bounds":{"left":0.4138889,"top":0.0,"width":0.06736111,"height":0.025555555},"help_text":"","role_description":"button","subrole":"AXUnknown","is_enabled":false,"is_focused":false,"is_selected":false}]...
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4462788281262115522
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click
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accessibility
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NULL
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DXP4800PLUS-B5F8
Inbox (1) - [EMAIL] - Gmail
Edit DXP4800PLUS-B5F8
Inbox (1) - [EMAIL] - Gmail
Edit profile
Edit profile
How to Get Through the Product Management Bottleneck
How to Get Through the Product Management Bottleneck
Časť 2 • HBO Max
Časť 2 • HBO Max
Settings
Settings
firefox sidebar - Google Search
firefox sidebar - Google Search
How to use AI-enhanced tab groups | Firefox Help
How to use AI-enhanced tab groups | Firefox Help
Add-ons Manager
Add-ons Manager
Vimium – Get this Extension for 🦊 Firefox (en-US)
Vimium – Get this Extension for 🦊 Firefox (en-US)
Maďarské voľby – Denník N
Maďarské voľby – Denník N
Vimium Options
Vimium Options
Close tab
Loď Orion úspešne pristála na Zemi. Desať vecí, ktoré si pamätať o misii Artemis II — Denník N
Loď Orion úspešne pristála na Zemi. Desať vecí, ktoré si pamätať o misii Artemis II — Denník N
Problem loading page
Problem loading page
Machines - Tailscale
Machines - Tailscale
New Tab
New Tab
Screenpipe Dashboard
Screenpipe Dashboard
New Tab
New Tab
New Tab
New Tab
New Tab
Customize sidebar
Close Google Gemini (⌃X)
Tabs from other devices
Open history (⇧⌘H)
Open bookmarks (⌘B)
AI Chat settings
Close
Google Account: Lukáš Koválik ([EMAIL])
Main menu
New chat
Gemini
Temporary chat
PLUS
PLUS
Conversation with Gemini
Conversation with Gemini
Hi Lukáš
Where should we start?
Where should we start?
🖼️ Create image, button, tap to use tool
🖼️ Create image
🎸 Create music, button, tap to use tool
🎸 Create music
Write anything, button, tap to use tool
Write anything
Boost my day, button, tap to use tool
Boost my day
Help me learn, button, tap to use tool
Help me learn
Create a video, button, tap to use tool
Create a video
Ask Gemini
Ask Gemini
Open upload file menu
Tools
Open mode picker
Pro
Microphone
Summarize page
Summarize page
Vimium Options
Excluded URLs and keys
Excluded URLs and keys
Patterns
Keys to exclude
https?://mail.google.com/*
All
✖
Patterns
https?://mail.google.com/*
Keys to exclude
All
✖
Add rule
Disable Vimium on URLs.
"Patterns" are URL regular expressions.
*
will match zero or more characters.
"Keys": Vimium will exclude these keys and pass them through to the page.
Custom key mappings
Custom key mappings
# Insert your preferred key mappings here.
Example syntax:
map j scrollDown
map z2 setZoom level=2
unmap j
unmapAll
" this is a comment
# this is also a comment
See all available commands
See all available commands
.
Custom search engines
Custom search engines
w: https://www.wikipedia.org/w/index.php?title=Special:Search&search=%s Wikipedia
# More examples.
#
# (Vimium supports search completion Wikipedia, as
# above, and for these.)
#
# g: https://www.google.com/search?q=%s Google
# l: https://www.google.com/search?q=%s&btnI I'm feeling lucky...
# y: https://www.youtube.com/results?search_query=%s Youtube
# gm: https://www.google.com/maps?q=%s Google maps
# b: https://www.bing.com/search?q=%s Bing
# d: https://duckduckgo.com/?q=%s DuckDuckGo
# az: https://www.amazon.com/s/?field-keywords=%s
# qw: https://www.qwant.com/?q=%s Qwant
Add search-engine shortcuts to the Vomnibar. Format:
a: http://a.com/?q=%s
b: http://b.com/?q=%s description
" this is a comment
# this is also a comment
%s is replaced with the search terms.
For search completion, see
here
here
.
New tab URL
New tab URL
Vimium blank new tab page
Vimium blank new tab page
Open the Vomnibar when the page loads
Open the Vomnibar when the page loads
Browser's default new tab page
Browser's default new tab page
Custom URL
Custom URL
The page to open when using Vimium's "create new tab" command. To have Vimium commands work on
all
new tab pages opened by the browser, a separate Vimium new tab extension is required. See the full details
here
here
.
Advanced Options
Scroll step size
Scroll step size
60
px
The size for basic movements (usually j/k/h/l).
Characters used for link hints
Characters used for link hints
sadfjklewcmpgh
Reset
Reset
The characters placed next to each link after typing "f" to enter link-hint mode.
Use smooth scrolling
Use smooth scrolling
Use the link's name and characters for link-hint filtering
Use the link's name and characters for link-hint filtering
In link-hint mode, this option lets you select a link by typing its text.
Don't let pages steal the focus on load
Don't let pages steal the focus on load
Prevent pages from focusing an input on load (e.g. Google, Bing, etc.).
Hide the Heads Up Display (HUD) in insert mode
Hide the Heads Up Display (HUD) in insert mode
When enabled, the HUD will not be displayed in insert mode.
Hide update notifications
Hide update notifications
When enabled, "Vimium has been updated" notifications will not be shown.
Treat find queries as JavaScript regular expressions
Treat find queries as JavaScript regular expressions
Switch back to plain find mode by using the
\R
escape sequence.
Ignore keyboard layout
Ignore keyboard layout
This forces the use of
en-US
QWERTY layout and can be helpful for non-Latin keyboards.
Previous patterns
Previous patterns
prev,previous,back,older,<,‹,←,«,≪,<<
Reset
Reset
The "navigate to previous page" command uses these patterns to find the link to follow.
Next patterns
Next patterns
next,more,newer,>,›,→,»,≫,>>
Reset
Reset
The "navigate to next page" command uses these patterns to find the link to follow.
CSS for Vimium UI
CSS for Vimium UI
div > .vimiumHintMarker {
/* linkhint boxes */
background: -webkit-gradient(linear, left top, left bottom, color-stop(0%,#FFF785),
color-stop(100%,#FFC542));
border: 1px solid #E3BE23;
}
div > .vimiumHintMarker span {
/* linkhint text */
color: black;
font-weight: bold;
font-size: 12px;
}
div > .vimiumHintMarker > .matchingCharacter {
}
Reset
Reset
These styles are applied to link hints, the Vomnibar, the help dialog, the exclusions pop-up and the HUD.
By default, this CSS is used to style the characters next to each link hint.
These styles are used in addition to and take precedence over Vimium's default styles.
[SEED_PHRASE].
Restore
Restore
Browse… No file selected.
Browse…
No file selected.
Choose a backup file to restore.
Type
?
to show the help dialog.
Type
Cmd-Enter
to save all options.
No changes...
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2026-04-11T15:34:52.475611+00:00
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/Users/lukas/.screenpipe/data/data/2026-04-11/1775 /Users/lukas/.screenpipe/data/data/2026-04-11/1775921692475_m1.jpg...
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Firefox
|
Vimium Options — Personal
|
True
|
moz-extension://f5e9c63e-b25b-4f15-8ba2-4813105e11 moz-extension://f5e9c63e-b25b-4f15-8ba2-4813105e11bb/pages/options.html...
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monitor_1
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NULL
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NULL
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NULL
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NULL
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DXP4800PLUS-B5F8
Inbox (1) - [EMAIL] - Gmail
Edit DXP4800PLUS-B5F8
Inbox (1) - [EMAIL] - Gmail
Edit profile
Edit profile
How to Get Through the Product Management Bottleneck
How to Get Through the Product Management Bottleneck
Časť 2 • HBO Max
Časť 2 • HBO Max
Settings
Settings
firefox sidebar - Google Search
firefox sidebar - Google Search
How to use AI-enhanced tab groups | Firefox Help
How to use AI-enhanced tab groups | Firefox Help
Add-ons Manager
Add-ons Manager
Vimium – Get this Extension for 🦊 Firefox (en-US)
Vimium – Get this Extension for 🦊 Firefox (en-US)
Maďarské voľby – Denník N
Maďarské voľby – Denník N
Vimium Options
Vimium Options
Close tab
Loď Orion úspešne pristála na Zemi. Desať vecí, ktoré si pamätať o misii Artemis II — Denník N
Loď Orion úspešne pristála na Zemi. Desať vecí, ktoré si pamätať o misii Artemis II — Denník N
Problem loading page
Problem loading page
Machines - Tailscale
Machines - Tailscale
New Tab
New Tab
Screenpipe Dashboard
Screenpipe Dashboard
New Tab
New Tab
New Tab
New Tab
New Tab
Customize sidebar
Close Google Gemini (⌃X)
Tabs from other devices
Open history (⇧⌘H)
Open bookmarks (⌘B)
AI Chat settings
Close
Google Account: Lukáš Koválik ([EMAIL])
Main menu
New chat
Open menu for conversation actions.
Conversation with Gemini
Conversation with Gemini
Copy prompt
Edit
You said how to use vimium in firefox
You said
how to use vimium in firefox
Show more options
Show thinking
Gemini said
Gemini said
Vimium (specifically
Vimium-FF
for Firefox) is a fantastic extension that lets you navigate the web entirely from your keyboard,
using standard Vim shortcuts.
Here is a guide on how to get started and the essential commands you need to know.
1. Installation
1. Installation
If you haven't already,
go to the Firefox Add-ons page,
search for
Vimium-FF
,
and click
Add to Firefox
.
Ask Gemini
Ask Gemini
Open upload file menu
Tools
Open mode picker
Pro
Stop response
Gemini is AI and can make mistakes, including about people.
Your privacy and Gemini Opens in a new window
Your privacy and Gemini
Opens in a new window
Summarize page
Summarize page
Vimium Options
Excluded URLs and keys
Excluded URLs and keys
Patterns
Keys to exclude
https?://mail.google.com/*
All
✖
Patterns
https?://mail.google.com/*
Keys to exclude
All
✖
Add rule
Disable Vimium on URLs.
"Patterns" are URL regular expressions.
*
will match zero or more characters.
"Keys": Vimium will exclude these keys and pass them through to the page.
Custom key mappings
Custom key mappings
# Insert your preferred key mappings here.
Example syntax:
map j scrollDown
map z2 setZoom level=2
unmap j
unmapAll
" this is a comment
# this is also a comment
See all available commands
See all available commands
.
Custom search engines
Custom search engines
w: https://www.wikipedia.org/w/index.php?title=Special:Search&search=%s Wikipedia
# More examples.
#
# (Vimium supports search completion Wikipedia, as
# above, and for these.)
#
# g: https://www.google.com/search?q=%s Google
# l: https://www.google.com/search?q=%s&btnI I'm feeling lucky...
# y: https://www.youtube.com/results?search_query=%s Youtube
# gm: https://www.google.com/maps?q=%s Google maps
# b: https://www.bing.com/search?q=%s Bing
# d: https://duckduckgo.com/?q=%s DuckDuckGo
# az: https://www.amazon.com/s/?field-keywords=%s
# qw: https://www.qwant.com/?q=%s Qwant
Add search-engine shortcuts to the Vomnibar. Format:
a: http://a.com/?q=%s
b: http://b.com/?q=%s description
" this is a comment
# this is also a comment
%s is replaced with the search terms.
For search completion, see
here
here
.
New tab URL
New tab URL
Vimium blank new tab page
Vimium blank new tab page
Open the Vomnibar when the page loads
Open the Vomnibar when the page loads
Browser's default new tab page
Browser's default new tab page
Custom URL
Custom URL
The page to open when using Vimium's "create new tab" command. To have Vimium commands work on
all
new tab pages opened by the browser, a separate Vimium new tab extension is required. See the full details
here
here
.
Advanced Options
Scroll step size
Scroll step size
60
px
The size for basic movements (usually j/k/h/l).
Characters used for link hints
Characters used for link hints
sadfjklewcmpgh
Reset
Reset
The characters placed next to each link after typing "f" to enter link-hint mode.
Use smooth scrolling
Use smooth scrolling
Use the link's name and characters for link-hint filtering
Use the link's name and characters for link-hint filtering
In link-hint mode, this option lets you select a link by typing its text.
Don't let pages steal the focus on load
Don't let pages steal the focus on load
Prevent pages from focusing an input on load (e.g. Google, Bing, etc.).
Hide the Heads Up Display (HUD) in insert mode
Hide the Heads Up Display (HUD) in insert mode
When enabled, the HUD will not be displayed in insert mode.
Hide update notifications
Hide update notifications
When enabled, "Vimium has been updated" notifications will not be shown.
Treat find queries as JavaScript regular expressions
Treat find queries as JavaScript regular expressions
Switch back to plain find mode by using the
\R
escape sequence.
Ignore keyboard layout
Ignore keyboard layout
This forces the use of
en-US
QWERTY layout and can be helpful for non-Latin keyboards.
Previous patterns
Previous patterns
prev,previous,back,older,<,‹,←,«,≪,<<
Reset
Reset
The "navigate to previous page" command uses these patterns to find the link to follow.
Next patterns
Next patterns
next,more,newer,>,›,→,»,≫,>>
Reset
Reset
The "navigate to next page" command uses these patterns to find the link to follow.
CSS for Vimium UI
CSS for Vimium UI
div > .vimiumHintMarker {
/* linkhint boxes */
background: -webkit-gradient(linear, left top, left bottom, color-stop(0%,#FFF785),
color-stop(100%,#FFC542));
border: 1px solid #E3BE23;
}
div > .vimiumHintMarker span {
/* linkhint text */
color: black;
font-weight: bold;
font-size: 12px;
}
div > .vimiumHintMarker > .matchingCharacter {
}
Reset
Reset
These styles are applied to link hints, the Vomnibar, the help dialog, the exclusions pop-up and the HUD.
By default, this CSS is used to style the characters next to each link hint.
These styles are used in addition to and take precedence over Vimium's default styles.
[SEED_PHRASE].
Restore
Restore
Browse… No file selected.
Browse…
No file selected.
Choose a backup file to restore.
Type
?
to show the help dialog.
Type
Cmd-Enter
to save all options.
No changes...
|
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Desať vecí, ktoré si pamätať o misii Artemis II — Denník N","depth":4,"help_text":"","role_description":"tab","subrole":"AXTabButton","is_enabled":true,"is_focused":false,"is_selected":false},{"role":"AXStaticText","text":"Loď Orion úspešne pristála na Zemi. Desať vecí, ktoré si pamätať o misii Artemis II — Denník N","depth":5,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXRadioButton","text":"Problem loading page","depth":4,"help_text":"","role_description":"tab","subrole":"AXTabButton","is_enabled":true,"is_focused":false,"is_selected":false},{"role":"AXStaticText","text":"Problem loading page","depth":5,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXRadioButton","text":"Machines - Tailscale","depth":4,"help_text":"","role_description":"tab","subrole":"AXTabButton","is_enabled":true,"is_focused":false,"is_selected":false},{"role":"AXStaticText","text":"Machines - Tailscale","depth":5,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXRadioButton","text":"New Tab","depth":4,"help_text":"","role_description":"tab","subrole":"AXTabButton","is_enabled":true,"is_focused":false,"is_selected":false},{"role":"AXStaticText","text":"New Tab","depth":5,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXRadioButton","text":"Screenpipe Dashboard","depth":4,"help_text":"","role_description":"tab","subrole":"AXTabButton","is_enabled":true,"is_focused":false,"is_selected":false},{"role":"AXStaticText","text":"Screenpipe Dashboard","depth":5,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXRadioButton","text":"New Tab","depth":4,"help_text":"","role_description":"tab","subrole":"AXTabButton","is_enabled":true,"is_focused":false,"is_selected":false},{"role":"AXStaticText","text":"New Tab","depth":5,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXRadioButton","text":"New Tab","depth":4,"help_text":"","role_description":"tab","subrole":"AXTabButton","is_enabled":true,"is_focused":false,"is_selected":false},{"role":"AXStaticText","text":"New Tab","depth":5,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXButton","text":"New Tab","depth":4,"help_text":"","role_description":"button","subrole":"AXUnknown","is_enabled":true,"is_focused":false,"is_selected":false},{"role":"AXCheckBox","text":"Customize sidebar","depth":6,"help_text":"","role_description":"toggle button","subrole":"AXToggle","is_enabled":true,"is_focused":false,"is_selected":false},{"role":"AXCheckBox","text":"Close Google Gemini (⌃X)","depth":6,"help_text":"","role_description":"toggle button","subrole":"AXToggle","is_enabled":true,"is_focused":false,"is_selected":false},{"role":"AXCheckBox","text":"Tabs from other devices","depth":6,"help_text":"","role_description":"toggle button","subrole":"AXToggle","is_enabled":true,"is_focused":false,"is_selected":false},{"role":"AXCheckBox","text":"Open history (⇧⌘H)","depth":6,"help_text":"","role_description":"toggle button","subrole":"AXToggle","is_enabled":true,"is_focused":false,"is_selected":false},{"role":"AXCheckBox","text":"Open bookmarks (⌘B)","depth":6,"help_text":"","role_description":"toggle button","subrole":"AXToggle","is_enabled":true,"is_focused":false,"is_selected":false},{"role":"AXButton","text":"AI Chat settings","depth":7,"help_text":"","role_description":"button","subrole":"AXUnknown","is_enabled":true,"is_focused":false,"is_selected":false,"is_expanded":false},{"role":"AXButton","text":"Close","depth":7,"help_text":"","role_description":"button","subrole":"AXUnknown","is_enabled":true,"is_focused":false,"is_selected":false},{"role":"AXButton","text":"Google Account: Lukáš Koválik (kovaliklukas@gmail.com)","depth":12,"help_text":"","role_description":"button","subrole":"AXUnknown","is_enabled":true,"is_focused":false,"is_selected":false,"is_expanded":false},{"role":"AXButton","text":"Main menu","depth":12,"role_description":"button","subrole":"AXUnknown","is_enabled":true,"is_focused":false,"is_selected":false},{"role":"AXButton","text":"New chat","depth":12,"help_text":"","role_description":"button","subrole":"AXUnknown","is_enabled":true,"is_focused":false,"is_selected":false},{"role":"AXButton","text":"Open menu for conversation actions.","depth":12,"help_text":"","role_description":"button","subrole":"AXUnknown","is_enabled":true,"is_focused":false,"is_selected":false,"is_expanded":false},{"role":"AXHeading","text":"Conversation with Gemini","depth":15,"help_text":"","role_description":"heading","subrole":"AXUnknown"},{"role":"AXStaticText","text":"Conversation with Gemini","depth":16,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXButton","text":"Copy prompt","depth":21,"help_text":"","role_description":"button","subrole":"AXUnknown","is_enabled":true,"is_focused":false,"is_selected":false},{"role":"AXButton","text":"Edit","depth":21,"role_description":"button","subrole":"AXUnknown","is_enabled":false,"is_focused":false,"is_selected":false},{"role":"AXHeading","text":"You said how to use vimium in firefox","depth":21,"help_text":"","role_description":"heading","subrole":"AXUnknown"},{"role":"AXStaticText","text":"You said","depth":23,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"how to use vimium in firefox","depth":23,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXButton","text":"Show more options","depth":23,"role_description":"button","subrole":"AXUnknown","is_enabled":true,"is_focused":false,"is_selected":false},{"role":"AXStaticText","text":"Show thinking","depth":29,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXHeading","text":"Gemini said","depth":23,"help_text":"","role_description":"heading","subrole":"AXUnknown"},{"role":"AXStaticText","text":"Gemini said","depth":24,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"Vimium (specifically","depth":27,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"Vimium-FF","depth":27,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"for Firefox) is a fantastic extension that lets you navigate the web entirely from your keyboard,","depth":27,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"using standard Vim shortcuts.","depth":27,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"Here is a guide on how to get started and the essential commands you need to know.","depth":27,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXHeading","text":"1. Installation","depth":26,"help_text":"","role_description":"heading","subrole":"AXUnknown"},{"role":"AXStaticText","text":"1. Installation","depth":27,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"If you haven't already,","depth":27,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"go to the Firefox Add-ons page,","depth":27,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"search for","depth":27,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"Vimium-FF","depth":27,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":",","depth":27,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"and click","depth":27,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"Add to Firefox","depth":27,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":".","depth":27,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXTextArea","text":"Ask Gemini","depth":20,"value":"Ask Gemini","help_text":"","role_description":"text entry area","subrole":"AXUnknown","is_enabled":true,"is_focused":true,"is_selected":false},{"role":"AXStaticText","text":"Ask Gemini","depth":21,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXButton","text":"Open upload file menu","depth":20,"role_description":"button","subrole":"AXUnknown","is_enabled":true,"is_focused":false,"is_selected":false,"is_expanded":false},{"role":"AXButton","text":"Tools","depth":18,"help_text":"","role_description":"button","subrole":"AXUnknown","is_enabled":true,"is_focused":false,"is_selected":false,"is_expanded":false},{"role":"AXButton","text":"Open mode picker","depth":20,"help_text":"","role_description":"button","subrole":"AXUnknown","is_enabled":true,"is_focused":false,"is_selected":false},{"role":"AXStaticText","text":"Pro","depth":23,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXButton","text":"Stop response","depth":19,"help_text":"","role_description":"button","subrole":"AXUnknown","is_enabled":true,"is_focused":false,"is_selected":false},{"role":"AXStaticText","text":"Gemini is AI and can make mistakes, including about people.","depth":17,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXLink","text":"Your privacy and Gemini Opens in a new window","depth":17,"help_text":"","role_description":"link","subrole":"AXUnknown","is_enabled":true,"is_focused":false,"is_selected":false},{"role":"AXStaticText","text":"Your privacy and Gemini","depth":18,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"Opens in a new window","depth":19,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXButton","text":"Summarize page","depth":7,"help_text":"","role_description":"button","subrole":"AXUnknown","is_enabled":true,"is_focused":false,"is_selected":false},{"role":"AXStaticText","text":"Summarize page","depth":9,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"Vimium Options","depth":8,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXHeading","text":"Excluded URLs and keys","depth":8,"help_text":"","role_description":"heading","subrole":"AXUnknown"},{"role":"AXStaticText","text":"Excluded URLs and keys","depth":9,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"Patterns","depth":12,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"Keys to exclude","depth":12,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXTextField","text":"https?://mail.google.com/*","depth":12,"value":"https?://mail.google.com/*","help_text":"","role_description":"text field","subrole":"AXUnknown","is_enabled":true,"is_focused":false,"is_selected":false},{"role":"AXTextField","text":"All","depth":12,"help_text":"","role_description":"text field","subrole":"AXUnknown","is_enabled":true,"is_focused":false,"is_selected":false},{"role":"AXButton","text":"✖","depth":12,"help_text":"","role_description":"button","subrole":"AXUnknown","is_enabled":true,"is_focused":false,"is_selected":false},{"role":"AXStaticText","text":"Patterns","depth":12,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXTextField","text":"https?://mail.google.com/*","depth":12,"value":"https?://mail.google.com/*","help_text":"","role_description":"text 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expressions.","depth":9,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"*","depth":10,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"will match zero or more characters.","depth":9,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"\"Keys\": Vimium will exclude these keys and pass them through to the page.","depth":9,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXHeading","text":"Custom key mappings","depth":8,"help_text":"","role_description":"heading","subrole":"AXUnknown"},{"role":"AXStaticText","text":"Custom key mappings","depth":9,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXTextArea","text":"# Insert your preferred key mappings here.","depth":8,"value":"# Insert your preferred key mappings here.","help_text":"","role_description":"text entry area","subrole":"AXUnknown","is_enabled":true,"is_focused":false,"is_selected":false},{"role":"AXStaticText","text":"Example syntax:","depth":9,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"map j scrollDown\nmap z2 setZoom level=2\nunmap j\nunmapAll\n\" this is a comment\n# this is also a comment","depth":10,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXLink","text":"See all available commands","depth":9,"help_text":"","role_description":"link","subrole":"AXUnknown","is_enabled":true,"is_focused":false,"is_selected":false},{"role":"AXStaticText","text":"See all available commands","depth":10,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":".","depth":9,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXHeading","text":"Custom search 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completion Wikipedia, as\n# above, and for these.)\n#\n# g: https://www.google.com/search?q=%s Google\n# l: https://www.google.com/search?q=%s&btnI I'm feeling lucky...\n# y: https://www.youtube.com/results?search_query=%s Youtube\n# gm: https://www.google.com/maps?q=%s Google maps\n# b: https://www.bing.com/search?q=%s Bing\n# d: https://duckduckgo.com/?q=%s DuckDuckGo\n# az: https://www.amazon.com/s/?field-keywords=%s\n# qw: https://www.qwant.com/?q=%s Qwant","help_text":"","role_description":"text entry area","subrole":"AXUnknown","is_enabled":true,"is_focused":false,"is_selected":false},{"role":"AXStaticText","text":"Add search-engine shortcuts to the Vomnibar. Format:","depth":9,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"a: http://a.com/?q=%s\nb: http://b.com/?q=%s description\n\" this is a comment\n# this is also a comment","depth":10,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"%s is replaced with the search terms.","depth":9,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"For search completion, see","depth":9,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXLink","text":"here","depth":9,"help_text":"","role_description":"link","subrole":"AXUnknown","is_enabled":true,"is_focused":false,"is_selected":false},{"role":"AXStaticText","text":"here","depth":10,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":".","depth":9,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXHeading","text":"New tab URL","depth":8,"help_text":"","role_description":"heading","subrole":"AXUnknown"},{"role":"AXStaticText","text":"New tab URL","depth":9,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXRadioButton","text":"Vimium blank new tab page","depth":9,"help_text":"","role_description":"radio button","subrole":"AXUnknown","is_enabled":true,"is_focused":false,"is_selected":false},{"role":"AXStaticText","text":"Vimium blank new tab page","depth":10,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXCheckBox","text":"Open the Vomnibar when the page loads","depth":10,"help_text":"","role_description":"checkbox","subrole":"AXUnknown","is_enabled":true,"is_focused":false,"is_selected":false},{"role":"AXStaticText","text":"Open the Vomnibar when the page loads","depth":11,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXRadioButton","text":"Browser's default new tab page","depth":9,"help_text":"","role_description":"radio button","subrole":"AXUnknown","is_enabled":true,"is_focused":false,"is_selected":false},{"role":"AXStaticText","text":"Browser's default new tab page","depth":10,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXRadioButton","text":"Custom URL","depth":9,"help_text":"","role_description":"radio button","subrole":"AXUnknown","is_enabled":true,"is_focused":false,"is_selected":false},{"role":"AXStaticText","text":"Custom URL","depth":10,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"The page to open when using Vimium's \"create new tab\" command. To have Vimium commands work on","depth":9,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"all","depth":10,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"new tab pages opened by the browser, a separate Vimium new tab extension is required. See the full details","depth":9,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXLink","text":"here","depth":9,"help_text":"","role_description":"link","subrole":"AXUnknown","is_enabled":true,"is_focused":false,"is_selected":false},{"role":"AXStaticText","text":"here","depth":10,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":".","depth":9,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"Advanced Options","depth":9,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXHeading","text":"Scroll step size","depth":8,"help_text":"","role_description":"heading","subrole":"AXUnknown"},{"role":"AXStaticText","text":"Scroll step size","depth":9,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"60","depth":10,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"px","depth":9,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"The size for basic movements (usually j/k/h/l).","depth":9,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXHeading","text":"Characters used for link hints","depth":9,"help_text":"","role_description":"heading","subrole":"AXUnknown"},{"role":"AXStaticText","text":"Characters used for link hints","depth":10,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXTextField","text":"sadfjklewcmpgh","depth":10,"value":"sadfjklewcmpgh","help_text":"","role_description":"text field","subrole":"AXUnknown","is_enabled":true,"is_focused":false,"is_selected":false},{"role":"AXLink","text":"Reset","depth":11,"help_text":"","role_description":"link","subrole":"AXUnknown","is_enabled":true,"is_focused":false,"is_selected":false},{"role":"AXStaticText","text":"Reset","depth":12,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"The characters placed next to each link after typing \"f\" to enter link-hint mode.","depth":10,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXCheckBox","text":"Use smooth scrolling","depth":9,"help_text":"","role_description":"checkbox","subrole":"AXUnknown","is_enabled":true,"is_focused":false,"is_selected":false},{"role":"AXStaticText","text":"Use smooth scrolling","depth":9,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXCheckBox","text":"Use the link's name and characters for link-hint filtering","depth":9,"help_text":"","role_description":"checkbox","subrole":"AXUnknown","is_enabled":true,"is_focused":false,"is_selected":false},{"role":"AXStaticText","text":"Use the link's name and characters for link-hint filtering","depth":9,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"In link-hint mode, this option lets you select a link by typing its text.","depth":9,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXCheckBox","text":"Don't let pages steal the focus on load","depth":9,"help_text":"","role_description":"checkbox","subrole":"AXUnknown","is_enabled":true,"is_focused":false,"is_selected":false},{"role":"AXStaticText","text":"Don't let pages steal the focus on load","depth":9,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"Prevent pages from focusing an input on load (e.g. Google, Bing, etc.).","depth":9,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXCheckBox","text":"Hide the Heads Up Display (HUD) in insert mode","depth":9,"help_text":"","role_description":"checkbox","subrole":"AXUnknown","is_enabled":true,"is_focused":false,"is_selected":false},{"role":"AXStaticText","text":"Hide the Heads Up Display (HUD) in insert mode","depth":9,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"When enabled, the HUD will not be displayed in insert mode.","depth":9,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXCheckBox","text":"Hide update notifications","depth":9,"help_text":"","role_description":"checkbox","subrole":"AXUnknown","is_enabled":true,"is_focused":false,"is_selected":false},{"role":"AXStaticText","text":"Hide update notifications","depth":9,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"When enabled, \"Vimium has been updated\" notifications will not be shown.","depth":9,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXCheckBox","text":"Treat find queries as JavaScript regular expressions","depth":9,"help_text":"","role_description":"checkbox","subrole":"AXUnknown","is_enabled":true,"is_focused":false,"is_selected":false},{"role":"AXStaticText","text":"Treat find queries as JavaScript regular expressions","depth":9,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"Switch back to plain find mode by using the","depth":9,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"\\R","depth":10,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"escape sequence.","depth":9,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXCheckBox","text":"Ignore keyboard layout","depth":9,"help_text":"","role_description":"checkbox","subrole":"AXUnknown","is_enabled":true,"is_focused":false,"is_selected":false},{"role":"AXStaticText","text":"Ignore keyboard layout","depth":9,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"This forces the use of","depth":9,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"en-US","depth":10,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"QWERTY layout and can be helpful for non-Latin keyboards.","depth":9,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXHeading","text":"Previous patterns","depth":8,"bounds":{"left":0.05277778,"top":0.0,"width":0.39375,"height":0.022222223},"help_text":"","role_description":"heading","subrole":"AXUnknown"},{"role":"AXStaticText","text":"Previous patterns","depth":9,"bounds":{"left":0.05277778,"top":0.0,"width":0.08680555,"height":0.02111111},"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXTextField","text":"prev,previous,back,older,<,‹,←,«,≪,<<","depth":9,"bounds":{"left":0.05277778,"top":0.0,"width":0.17152777,"height":0.026666667},"value":"prev,previous,back,older,<,‹,←,«,≪,<<","help_text":"","role_description":"text field","subrole":"AXUnknown","is_enabled":true,"is_focused":false,"is_selected":false},{"role":"AXLink","text":"Reset","depth":10,"bounds":{"left":0.20277777,"top":0.0,"width":0.021527778,"height":0.015555556},"help_text":"","role_description":"link","subrole":"AXUnknown","is_enabled":true,"is_focused":false,"is_selected":false},{"role":"AXStaticText","text":"Reset","depth":11,"bounds":{"left":0.20277777,"top":0.0,"width":0.021527778,"height":0.015555556},"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"The \"navigate to previous page\" command uses these patterns to find the link to follow.","depth":9,"bounds":{"left":0.23819445,"top":0.0,"width":0.19930555,"height":0.033333335},"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXHeading","text":"Next patterns","depth":8,"bounds":{"left":0.05277778,"top":0.022222223,"width":0.39375,"height":0.022222223},"help_text":"","role_description":"heading","subrole":"AXUnknown"},{"role":"AXStaticText","text":"Next patterns","depth":9,"bounds":{"left":0.05277778,"top":0.022222223,"width":0.065972224,"height":0.02111111},"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXTextField","text":"next,more,newer,>,›,→,»,≫,>>","depth":9,"bounds":{"left":0.05277778,"top":0.057777777,"width":0.17152777,"height":0.026666667},"value":"next,more,newer,>,›,→,»,≫,>>","help_text":"","role_description":"text field","subrole":"AXUnknown","is_enabled":true,"is_focused":false,"is_selected":false},{"role":"AXLink","text":"Reset","depth":10,"bounds":{"left":0.20277777,"top":0.08555555,"width":0.021527778,"height":0.015555556},"help_text":"","role_description":"link","subrole":"AXUnknown","is_enabled":true,"is_focused":false,"is_selected":false},{"role":"AXStaticText","text":"Reset","depth":11,"bounds":{"left":0.20277777,"top":0.08555555,"width":0.021527778,"height":0.015555556},"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"The \"navigate to next page\" command uses these patterns to find the link to follow.","depth":9,"bounds":{"left":0.23819445,"top":0.05888889,"width":0.18402778,"height":0.033333335},"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXHeading","text":"CSS for Vimium UI","depth":8,"bounds":{"left":0.05277778,"top":0.115555555,"width":0.39375,"height":0.022222223},"help_text":"","role_description":"heading","subrole":"AXUnknown"},{"role":"AXStaticText","text":"CSS for Vimium UI","depth":9,"bounds":{"left":0.05277778,"top":0.115555555,"width":0.093055554,"height":0.02111111},"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXTextArea","text":"div > .vimiumHintMarker {\n/* linkhint boxes */\nbackground: -webkit-gradient(linear, left top, left bottom, color-stop(0%,#FFF785),\n color-stop(100%,#FFC542));\nborder: 1px solid #E3BE23;\n}\n\ndiv > .vimiumHintMarker span {\n/* linkhint text */\ncolor: black;\nfont-weight: bold;\nfont-size: 12px;\n}\n\ndiv > .vimiumHintMarker > .matchingCharacter {\n}","depth":9,"bounds":{"left":0.05277778,"top":0.15222222,"width":0.17152777,"height":0.15555556},"value":"div > .vimiumHintMarker {\n/* linkhint boxes */\nbackground: -webkit-gradient(linear, left top, left bottom, color-stop(0%,#FFF785),\n color-stop(100%,#FFC542));\nborder: 1px solid #E3BE23;\n}\n\ndiv > .vimiumHintMarker span {\n/* linkhint text */\ncolor: black;\nfont-weight: bold;\nfont-size: 12px;\n}\n\ndiv > .vimiumHintMarker > .matchingCharacter {\n}","help_text":"","role_description":"text entry area","subrole":"AXUnknown","is_enabled":true,"is_focused":false,"is_selected":false},{"role":"AXLink","text":"Reset","depth":10,"bounds":{"left":0.20277777,"top":0.31,"width":0.021527778,"height":0.015555556},"help_text":"","role_description":"link","subrole":"AXUnknown","is_enabled":true,"is_focused":false,"is_selected":false},{"role":"AXStaticText","text":"Reset","depth":11,"bounds":{"left":0.20277777,"top":0.31,"width":0.021527778,"height":0.015555556},"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"These styles are applied to link hints, the Vomnibar, the help dialog, the exclusions pop-up and the HUD.","depth":9,"bounds":{"left":0.23819445,"top":0.15222222,"width":0.20347223,"height":0.033333335},"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"By default, this CSS is used to style the characters next to each link hint.","depth":9,"bounds":{"left":0.23819445,"top":0.18777777,"width":0.2048611,"height":0.033333335},"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"These styles are used in addition to and take precedence over Vimium's default styles.","depth":9,"bounds":{"left":0.23819445,"top":0.24111111,"width":0.16527778,"height":0.033333335},"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"Backup and Restore","depth":9,"bounds":{"left":0.05277778,"top":0.34888887,"width":0.11319444,"height":0.023333333},"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXHeading","text":"Backup","depth":8,"bounds":{"left":0.05277778,"top":0.40333334,"width":0.39375,"height":0.022222223},"help_text":"","role_description":"heading","subrole":"AXUnknown"},{"role":"AXStaticText","text":"Backup","depth":9,"bounds":{"left":0.05277778,"top":0.40444446,"width":0.036805555,"height":0.02111111},"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXLink","text":"Download backup","depth":8,"bounds":{"left":0.05277778,"top":0.43888888,"width":0.17152777,"height":0.017777778},"help_text":"","role_description":"link","subrole":"AXUnknown","is_enabled":true,"is_focused":false,"is_selected":false},{"role":"AXStaticText","text":"Download backup","depth":9,"bounds":{"left":0.05277778,"top":0.43888888,"width":0.077083334,"height":0.017777778},"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"Download a backup of your settings.","depth":9,"bounds":{"left":0.23819445,"top":0.44,"width":0.13402778,"height":0.015555556},"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXHeading","text":"Restore","depth":8,"bounds":{"left":0.05277778,"top":0.47,"width":0.39375,"height":0.022222223},"help_text":"","role_description":"heading","subrole":"AXUnknown"},{"role":"AXStaticText","text":"Restore","depth":9,"bounds":{"left":0.05277778,"top":0.47111112,"width":0.03888889,"height":0.02111111},"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXButton","text":"Browse… No file selected.","depth":8,"bounds":{"left":0.05277778,"top":0.50555557,"width":0.17152777,"height":0.024444444},"help_text":"","role_description":"button","subrole":"AXUnknown","is_enabled":true,"is_focused":false,"is_selected":false},{"role":"AXStaticText","text":"Browse…","depth":9,"bounds":{"left":0.056944445,"top":0.5088889,"width":0.03888889,"height":0.017777778},"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"No file selected.","depth":9,"bounds":{"left":0.103472225,"top":0.5088889,"width":0.07013889,"height":0.017777778},"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"Choose a backup file to restore.","depth":9,"bounds":{"left":0.23819445,"top":0.50666666,"width":0.11736111,"height":0.015555556},"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"Type","depth":10,"bounds":{"left":0.05277778,"top":0.0,"width":0.02013889,"height":0.015555556},"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"?","depth":11,"bounds":{"left":0.072916664,"top":0.0,"width":0.0055555557,"height":0.015555556},"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"to show the help dialog.","depth":10,"bounds":{"left":0.07847222,"top":0.0,"width":0.08958333,"height":0.015555556},"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"Type","depth":10,"bounds":{"left":0.05277778,"top":0.0,"width":0.02013889,"height":0.015555556},"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"Cmd-Enter","depth":11,"bounds":{"left":0.072916664,"top":0.0,"width":0.043055557,"height":0.015555556},"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"to save all options.","depth":10,"bounds":{"left":0.11597222,"top":0.0,"width":0.07083333,"height":0.015555556},"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXButton","text":"No changes","depth":10,"bounds":{"left":0.4138889,"top":0.0,"width":0.06736111,"height":0.025555555},"help_text":"","role_description":"button","subrole":"AXUnknown","is_enabled":false,"is_focused":false,"is_selected":false}]...
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3307685878295759494
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app_switch
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accessibility
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DXP4800PLUS-B5F8
Inbox (1) - [EMAIL] - Gmail
Edit DXP4800PLUS-B5F8
Inbox (1) - [EMAIL] - Gmail
Edit profile
Edit profile
How to Get Through the Product Management Bottleneck
How to Get Through the Product Management Bottleneck
Časť 2 • HBO Max
Časť 2 • HBO Max
Settings
Settings
firefox sidebar - Google Search
firefox sidebar - Google Search
How to use AI-enhanced tab groups | Firefox Help
How to use AI-enhanced tab groups | Firefox Help
Add-ons Manager
Add-ons Manager
Vimium – Get this Extension for 🦊 Firefox (en-US)
Vimium – Get this Extension for 🦊 Firefox (en-US)
Maďarské voľby – Denník N
Maďarské voľby – Denník N
Vimium Options
Vimium Options
Close tab
Loď Orion úspešne pristála na Zemi. Desať vecí, ktoré si pamätať o misii Artemis II — Denník N
Loď Orion úspešne pristála na Zemi. Desať vecí, ktoré si pamätať o misii Artemis II — Denník N
Problem loading page
Problem loading page
Machines - Tailscale
Machines - Tailscale
New Tab
New Tab
Screenpipe Dashboard
Screenpipe Dashboard
New Tab
New Tab
New Tab
New Tab
New Tab
Customize sidebar
Close Google Gemini (⌃X)
Tabs from other devices
Open history (⇧⌘H)
Open bookmarks (⌘B)
AI Chat settings
Close
Google Account: Lukáš Koválik ([EMAIL])
Main menu
New chat
Open menu for conversation actions.
Conversation with Gemini
Conversation with Gemini
Copy prompt
Edit
You said how to use vimium in firefox
You said
how to use vimium in firefox
Show more options
Show thinking
Gemini said
Gemini said
Vimium (specifically
Vimium-FF
for Firefox) is a fantastic extension that lets you navigate the web entirely from your keyboard,
using standard Vim shortcuts.
Here is a guide on how to get started and the essential commands you need to know.
1. Installation
1. Installation
If you haven't already,
go to the Firefox Add-ons page,
search for
Vimium-FF
,
and click
Add to Firefox
.
Ask Gemini
Ask Gemini
Open upload file menu
Tools
Open mode picker
Pro
Stop response
Gemini is AI and can make mistakes, including about people.
Your privacy and Gemini Opens in a new window
Your privacy and Gemini
Opens in a new window
Summarize page
Summarize page
Vimium Options
Excluded URLs and keys
Excluded URLs and keys
Patterns
Keys to exclude
https?://mail.google.com/*
All
✖
Patterns
https?://mail.google.com/*
Keys to exclude
All
✖
Add rule
Disable Vimium on URLs.
"Patterns" are URL regular expressions.
*
will match zero or more characters.
"Keys": Vimium will exclude these keys and pass them through to the page.
Custom key mappings
Custom key mappings
# Insert your preferred key mappings here.
Example syntax:
map j scrollDown
map z2 setZoom level=2
unmap j
unmapAll
" this is a comment
# this is also a comment
See all available commands
See all available commands
.
Custom search engines
Custom search engines
w: https://www.wikipedia.org/w/index.php?title=Special:Search&search=%s Wikipedia
# More examples.
#
# (Vimium supports search completion Wikipedia, as
# above, and for these.)
#
# g: https://www.google.com/search?q=%s Google
# l: https://www.google.com/search?q=%s&btnI I'm feeling lucky...
# y: https://www.youtube.com/results?search_query=%s Youtube
# gm: https://www.google.com/maps?q=%s Google maps
# b: https://www.bing.com/search?q=%s Bing
# d: https://duckduckgo.com/?q=%s DuckDuckGo
# az: https://www.amazon.com/s/?field-keywords=%s
# qw: https://www.qwant.com/?q=%s Qwant
Add search-engine shortcuts to the Vomnibar. Format:
a: http://a.com/?q=%s
b: http://b.com/?q=%s description
" this is a comment
# this is also a comment
%s is replaced with the search terms.
For search completion, see
here
here
.
New tab URL
New tab URL
Vimium blank new tab page
Vimium blank new tab page
Open the Vomnibar when the page loads
Open the Vomnibar when the page loads
Browser's default new tab page
Browser's default new tab page
Custom URL
Custom URL
The page to open when using Vimium's "create new tab" command. To have Vimium commands work on
all
new tab pages opened by the browser, a separate Vimium new tab extension is required. See the full details
here
here
.
Advanced Options
Scroll step size
Scroll step size
60
px
The size for basic movements (usually j/k/h/l).
Characters used for link hints
Characters used for link hints
sadfjklewcmpgh
Reset
Reset
The characters placed next to each link after typing "f" to enter link-hint mode.
Use smooth scrolling
Use smooth scrolling
Use the link's name and characters for link-hint filtering
Use the link's name and characters for link-hint filtering
In link-hint mode, this option lets you select a link by typing its text.
Don't let pages steal the focus on load
Don't let pages steal the focus on load
Prevent pages from focusing an input on load (e.g. Google, Bing, etc.).
Hide the Heads Up Display (HUD) in insert mode
Hide the Heads Up Display (HUD) in insert mode
When enabled, the HUD will not be displayed in insert mode.
Hide update notifications
Hide update notifications
When enabled, "Vimium has been updated" notifications will not be shown.
Treat find queries as JavaScript regular expressions
Treat find queries as JavaScript regular expressions
Switch back to plain find mode by using the
\R
escape sequence.
Ignore keyboard layout
Ignore keyboard layout
This forces the use of
en-US
QWERTY layout and can be helpful for non-Latin keyboards.
Previous patterns
Previous patterns
prev,previous,back,older,<,‹,←,«,≪,<<
Reset
Reset
The "navigate to previous page" command uses these patterns to find the link to follow.
Next patterns
Next patterns
next,more,newer,>,›,→,»,≫,>>
Reset
Reset
The "navigate to next page" command uses these patterns to find the link to follow.
CSS for Vimium UI
CSS for Vimium UI
div > .vimiumHintMarker {
/* linkhint boxes */
background: -webkit-gradient(linear, left top, left bottom, color-stop(0%,#FFF785),
color-stop(100%,#FFC542));
border: 1px solid #E3BE23;
}
div > .vimiumHintMarker span {
/* linkhint text */
color: black;
font-weight: bold;
font-size: 12px;
}
div > .vimiumHintMarker > .matchingCharacter {
}
Reset
Reset
These styles are applied to link hints, the Vomnibar, the help dialog, the exclusions pop-up and the HUD.
By default, this CSS is used to style the characters next to each link hint.
These styles are used in addition to and take precedence over Vimium's default styles.
[SEED_PHRASE].
Restore
Restore
Browse… No file selected.
Browse…
No file selected.
Choose a backup file to restore.
Type
?
to show the help dialog.
Type
Cmd-Enter
to save all options.
No changes...
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2026-04-13T14:42:17.855842+00:00
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/Users/lukas/.screenpipe/data/data/2026-04-13/1776 /Users/lukas/.screenpipe/data/data/2026-04-13/1776091337855_m1.jpg...
|
Firefox
|
Vimium Options — Personal
|
True
|
moz-extension://f5e9c63e-b25b-4f15-8ba2-4813105e11 moz-extension://f5e9c63e-b25b-4f15-8ba2-4813105e11bb/pages/options.html...
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monitor_1
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DXP4800PLUS-B5F8
Inbox (9) - [EMAIL] - Gmail
Sham DXP4800PLUS-B5F8
Inbox (9) - [EMAIL] - Gmail
Shameless • HBO Max
Shameless • HBO Max
Settings
Settings
firefox sidebar - Google Search
firefox sidebar - Google Search
How to use AI-enhanced tab groups | Firefox Help
How to use AI-enhanced tab groups | Firefox Help
Add-ons Manager
Add-ons Manager
Vimium – Get this Extension for 🦊 Firefox (en-US)
Vimium – Get this Extension for 🦊 Firefox (en-US)
dennikn.sk/
dennikn.sk/
Vimium Options
Vimium Options
Close tab
Loď Orion úspešne pristála na Zemi. Desať vecí, ktoré si pamätať o misii Artemis II — Denník N
Loď Orion úspešne pristála na Zemi. Desať vecí, ktoré si pamätať o misii Artemis II — Denník N
Machines - Tailscale
Machines - Tailscale
Screenpipe Dashboard
Screenpipe Dashboard
Add-ons for Firefox (en-US)
Add-ons for Firefox (en-US)
Pazaruvaj.com — Знак, че е време за най-добрите оферти
Pazaruvaj.com — Знак, че е време за най-добрите оферти
Bitwarden Password Manager – Get this Extension for 🦊 Firefox (en-US)
Bitwarden Password Manager – Get this Extension for 🦊 Firefox (en-US)
Browser Extension Getting Started | Bitwarden
Browser Extension Getting Started | Bitwarden
Extensions – Add-ons for Firefox (en-US)
Extensions – Add-ons for Firefox (en-US)
Dangbei Atom Review - RTINGS.com
Dangbei Atom Review - RTINGS.com
Screenpipe: Open Source 24/7 Screen & Audio Capture : r/software
Screenpipe: Open Source 24/7 Screen & Audio Capture : r/software
Add-ons for Firefox (en-US)
Add-ons for Firefox (en-US)
Problem loading page
Problem loading page
Welcome to Firefox
Welcome to Firefox
New Tab
Customize sidebar
Open Google Gemini (⌃X)
Open history (⇧⌘H)
Open bookmarks (⌘B)
Bitwarden
Vimium Options
Excluded URLs and keys
Excluded URLs and keys
Patterns
Keys to exclude
https?://mail.google.com/*
All
✖
Patterns
https?://mail.google.com/*
Keys to exclude
All
✖
Add rule
Disable Vimium on URLs.
"Patterns" are URL regular expressions.
*
will match zero or more characters.
"Keys": Vimium will exclude these keys and pass them through to the page.
Custom key mappings
Custom key mappings
# Insert your preferred key mappings here.
Example syntax:
map j scrollDown
map z2 setZoom level=2
unmap j
unmapAll
" this is a comment
# this is also a comment
See all available commands
See all available commands
.
Custom search engines
Custom search engines
w: https://www.wikipedia.org/w/index.php?title=Special:Search&search=%s Wikipedia
# More examples.
#
# (Vimium supports search completion Wikipedia, as
# above, and for these.)
#
# g: https://www.google.com/search?q=%s Google
# l: https://www.google.com/search?q=%s&btnI I'm feeling lucky...
# y: https://www.youtube.com/results?search_query=%s Youtube
# gm: https://www.google.com/maps?q=%s Google maps
# b: https://www.bing.com/search?q=%s Bing
# d: https://duckduckgo.com/?q=%s DuckDuckGo
# az: https://www.amazon.com/s/?field-keywords=%s
# qw: https://www.qwant.com/?q=%s Qwant
Add search-engine shortcuts to the Vomnibar. Format:
a: http://a.com/?q=%s
b: http://b.com/?q=%s description
" this is a comment
# this is also a comment
%s is replaced with the search terms.
For search completion, see
here
here
.
New tab URL
New tab URL
Vimium blank new tab page
Vimium blank new tab page
Open the Vomnibar when the page loads
Open the Vomnibar when the page loads
Browser's default new tab page
Browser's default new tab page
Custom URL
Custom URL
The page to open when using Vimium's "create new tab" command. To have Vimium commands work on
all
new tab pages opened by the browser, a separate Vimium new tab extension is required. See the full details
here
here
.
Advanced Options
Scroll step size
Scroll step size
60
px
The size for basic movements (usually j/k/h/l).
Characters used for link hints
Characters used for link hints
sadfjklewcmpgh
Reset
Reset
The characters placed next to each link after typing "f" to enter link-hint mode.
Use smooth scrolling
Use smooth scrolling
Use the link's name and characters for link-hint filtering
Use the link's name and characters for link-hint filtering
In link-hint mode, this option lets you select a link by typing its text.
Don't let pages steal the focus on load
Don't let pages steal the focus on load
Prevent pages from focusing an input on load (e.g. Google, Bing, etc.).
Hide the Heads Up Display (HUD) in insert mode
Hide the Heads Up Display (HUD) in insert mode
When enabled, the HUD will not be displayed in insert mode....
|
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Desať vecí, ktoré si pamätať o misii Artemis II — Denník N","depth":4,"help_text":"","role_description":"tab","subrole":"AXTabButton","is_enabled":true,"is_focused":false,"is_selected":false},{"role":"AXStaticText","text":"Loď Orion úspešne pristála na Zemi. 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Firefox (en-US)","depth":5,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXRadioButton","text":"Pazaruvaj.com — Знак, че е време за най-добрите оферти","depth":4,"help_text":"","role_description":"tab","subrole":"AXTabButton","is_enabled":true,"is_focused":false,"is_selected":false},{"role":"AXStaticText","text":"Pazaruvaj.com — Знак, че е време за най-добрите оферти","depth":5,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXRadioButton","text":"Bitwarden Password Manager – Get this Extension for 🦊 Firefox (en-US)","depth":4,"help_text":"","role_description":"tab","subrole":"AXTabButton","is_enabled":true,"is_focused":false,"is_selected":false},{"role":"AXStaticText","text":"Bitwarden Password Manager – Get this Extension for 🦊 Firefox (en-US)","depth":5,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXRadioButton","text":"Browser Extension Getting Started | Bitwarden","depth":4,"help_text":"","role_description":"tab","subrole":"AXTabButton","is_enabled":true,"is_focused":false,"is_selected":false},{"role":"AXStaticText","text":"Browser Extension Getting Started | Bitwarden","depth":5,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXRadioButton","text":"Extensions – Add-ons for Firefox (en-US)","depth":4,"help_text":"","role_description":"tab","subrole":"AXTabButton","is_enabled":true,"is_focused":false,"is_selected":false},{"role":"AXStaticText","text":"Extensions – Add-ons for Firefox (en-US)","depth":5,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXRadioButton","text":"Dangbei Atom Review - RTINGS.com","depth":4,"help_text":"","role_description":"tab","subrole":"AXTabButton","is_enabled":true,"is_focused":false,"is_selected":false},{"role":"AXStaticText","text":"Dangbei Atom Review - RTINGS.com","depth":5,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXRadioButton","text":"Screenpipe: Open Source 24/7 Screen & Audio Capture : r/software","depth":4,"help_text":"","role_description":"tab","subrole":"AXTabButton","is_enabled":true,"is_focused":false,"is_selected":false},{"role":"AXStaticText","text":"Screenpipe: Open Source 24/7 Screen & Audio Capture : r/software","depth":5,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXRadioButton","text":"Add-ons for Firefox (en-US)","depth":4,"help_text":"","role_description":"tab","subrole":"AXTabButton","is_enabled":true,"is_focused":false,"is_selected":false},{"role":"AXStaticText","text":"Add-ons for Firefox (en-US)","depth":5,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXRadioButton","text":"Problem loading page","depth":4,"help_text":"","role_description":"tab","subrole":"AXTabButton","is_enabled":true,"is_focused":false,"is_selected":false},{"role":"AXStaticText","text":"Problem loading page","depth":5,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXRadioButton","text":"Welcome to Firefox","depth":4,"help_text":"","role_description":"tab","subrole":"AXTabButton","is_enabled":true,"is_focused":false,"is_selected":false},{"role":"AXStaticText","text":"Welcome to Firefox","depth":5,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXButton","text":"New Tab","depth":4,"help_text":"","role_description":"button","subrole":"AXUnknown","is_enabled":true,"is_focused":false,"is_selected":false},{"role":"AXCheckBox","text":"Customize sidebar","depth":6,"help_text":"","role_description":"toggle button","subrole":"AXToggle","is_enabled":true,"is_focused":false,"is_selected":false},{"role":"AXCheckBox","text":"Open Google Gemini (⌃X)","depth":6,"help_text":"","role_description":"toggle button","subrole":"AXToggle","is_enabled":true,"is_focused":false,"is_selected":false},{"role":"AXCheckBox","text":"Open history (⇧⌘H)","depth":6,"help_text":"","role_description":"toggle button","subrole":"AXToggle","is_enabled":true,"is_focused":false,"is_selected":false},{"role":"AXCheckBox","text":"Open bookmarks (⌘B)","depth":6,"help_text":"","role_description":"toggle button","subrole":"AXToggle","is_enabled":true,"is_focused":false,"is_selected":false},{"role":"AXCheckBox","text":"Bitwarden","depth":6,"help_text":"","role_description":"toggle button","subrole":"AXToggle","is_enabled":true,"is_focused":false,"is_selected":false},{"role":"AXStaticText","text":"Vimium Options","depth":8,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXHeading","text":"Excluded URLs and keys","depth":8,"help_text":"","role_description":"heading","subrole":"AXUnknown"},{"role":"AXStaticText","text":"Excluded URLs and keys","depth":9,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"Patterns","depth":12,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"Keys to exclude","depth":12,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXTextField","text":"https?://mail.google.com/*","depth":12,"value":"https?://mail.google.com/*","help_text":"","role_description":"text field","subrole":"AXUnknown","is_enabled":true,"is_focused":false,"is_selected":false},{"role":"AXTextField","text":"All","depth":12,"help_text":"","role_description":"text field","subrole":"AXUnknown","is_enabled":true,"is_focused":false,"is_selected":false},{"role":"AXButton","text":"✖","depth":12,"help_text":"","role_description":"button","subrole":"AXUnknown","is_enabled":true,"is_focused":false,"is_selected":false},{"role":"AXStaticText","text":"Patterns","depth":12,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXTextField","text":"https?://mail.google.com/*","depth":12,"value":"https?://mail.google.com/*","help_text":"","role_description":"text field","subrole":"AXUnknown","is_enabled":true,"is_focused":false,"is_selected":false},{"role":"AXStaticText","text":"Keys to exclude","depth":12,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXTextField","text":"All","depth":12,"help_text":"","role_description":"text field","subrole":"AXUnknown","is_enabled":true,"is_focused":false,"is_selected":false},{"role":"AXButton","text":"✖","depth":12,"help_text":"","role_description":"button","subrole":"AXUnknown","is_enabled":true,"is_focused":false,"is_selected":false},{"role":"AXButton","text":"Add rule","depth":8,"help_text":"","role_description":"button","subrole":"AXUnknown","is_enabled":true,"is_focused":false,"is_selected":false},{"role":"AXStaticText","text":"Disable Vimium on URLs.","depth":9,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"\"Patterns\" are URL regular expressions.","depth":9,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"*","depth":10,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"will match zero or more characters.","depth":9,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"\"Keys\": Vimium will exclude these keys and pass them through to the page.","depth":9,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXHeading","text":"Custom key mappings","depth":8,"help_text":"","role_description":"heading","subrole":"AXUnknown"},{"role":"AXStaticText","text":"Custom key mappings","depth":9,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXTextArea","text":"# Insert your preferred key mappings here.","depth":8,"value":"# Insert your preferred key mappings here.","help_text":"","role_description":"text entry area","subrole":"AXUnknown","is_enabled":true,"is_focused":false,"is_selected":false},{"role":"AXStaticText","text":"Example syntax:","depth":9,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"map j scrollDown\nmap z2 setZoom level=2\nunmap j\nunmapAll\n\" this is a comment\n# this is also a comment","depth":10,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXLink","text":"See all available commands","depth":9,"help_text":"","role_description":"link","subrole":"AXUnknown","is_enabled":true,"is_focused":false,"is_selected":false},{"role":"AXStaticText","text":"See all available commands","depth":10,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":".","depth":9,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXHeading","text":"Custom search engines","depth":8,"help_text":"","role_description":"heading","subrole":"AXUnknown"},{"role":"AXStaticText","text":"Custom search engines","depth":9,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXTextArea","text":"w: https://www.wikipedia.org/w/index.php?title=Special:Search&search=%s Wikipedia\n\n# More examples.\n#\n# (Vimium supports search completion Wikipedia, as\n# above, and for these.)\n#\n# g: https://www.google.com/search?q=%s Google\n# l: https://www.google.com/search?q=%s&btnI I'm feeling lucky...\n# y: https://www.youtube.com/results?search_query=%s Youtube\n# gm: https://www.google.com/maps?q=%s Google maps\n# b: https://www.bing.com/search?q=%s Bing\n# d: https://duckduckgo.com/?q=%s DuckDuckGo\n# az: https://www.amazon.com/s/?field-keywords=%s\n# qw: https://www.qwant.com/?q=%s Qwant","depth":8,"value":"w: https://www.wikipedia.org/w/index.php?title=Special:Search&search=%s Wikipedia\n\n# More examples.\n#\n# (Vimium supports search completion Wikipedia, as\n# above, and for these.)\n#\n# g: https://www.google.com/search?q=%s Google\n# l: https://www.google.com/search?q=%s&btnI I'm feeling lucky...\n# y: https://www.youtube.com/results?search_query=%s Youtube\n# gm: https://www.google.com/maps?q=%s Google maps\n# b: https://www.bing.com/search?q=%s Bing\n# d: https://duckduckgo.com/?q=%s DuckDuckGo\n# az: https://www.amazon.com/s/?field-keywords=%s\n# qw: https://www.qwant.com/?q=%s Qwant","help_text":"","role_description":"text entry area","subrole":"AXUnknown","is_enabled":true,"is_focused":false,"is_selected":false},{"role":"AXStaticText","text":"Add search-engine shortcuts to the Vomnibar. Format:","depth":9,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"a: http://a.com/?q=%s\nb: http://b.com/?q=%s description\n\" this is a comment\n# this is also a comment","depth":10,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"%s is replaced with the search terms.","depth":9,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"For search completion, see","depth":9,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXLink","text":"here","depth":9,"help_text":"","role_description":"link","subrole":"AXUnknown","is_enabled":true,"is_focused":false,"is_selected":false},{"role":"AXStaticText","text":"here","depth":10,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":".","depth":9,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXHeading","text":"New tab URL","depth":8,"help_text":"","role_description":"heading","subrole":"AXUnknown"},{"role":"AXStaticText","text":"New tab URL","depth":9,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXRadioButton","text":"Vimium blank new tab page","depth":9,"help_text":"","role_description":"radio button","subrole":"AXUnknown","is_enabled":true,"is_focused":false,"is_selected":false},{"role":"AXStaticText","text":"Vimium blank new tab page","depth":10,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXCheckBox","text":"Open the Vomnibar when the page loads","depth":10,"help_text":"","role_description":"checkbox","subrole":"AXUnknown","is_enabled":true,"is_focused":false,"is_selected":false},{"role":"AXStaticText","text":"Open the Vomnibar when the page loads","depth":11,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXRadioButton","text":"Browser's default new tab page","depth":9,"help_text":"","role_description":"radio button","subrole":"AXUnknown","is_enabled":true,"is_focused":false,"is_selected":false},{"role":"AXStaticText","text":"Browser's default new tab page","depth":10,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXRadioButton","text":"Custom URL","depth":9,"help_text":"","role_description":"radio button","subrole":"AXUnknown","is_enabled":true,"is_focused":false,"is_selected":false},{"role":"AXStaticText","text":"Custom URL","depth":10,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"The page to open when using Vimium's \"create new tab\" command. To have Vimium commands work on","depth":9,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"all","depth":10,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"new tab pages opened by the browser, a separate Vimium new tab extension is required. See the full details","depth":9,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXLink","text":"here","depth":9,"help_text":"","role_description":"link","subrole":"AXUnknown","is_enabled":true,"is_focused":false,"is_selected":false},{"role":"AXStaticText","text":"here","depth":10,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":".","depth":9,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"Advanced Options","depth":9,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXHeading","text":"Scroll step size","depth":8,"help_text":"","role_description":"heading","subrole":"AXUnknown"},{"role":"AXStaticText","text":"Scroll step size","depth":9,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"60","depth":10,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"px","depth":9,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"The size for basic movements (usually j/k/h/l).","depth":9,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXHeading","text":"Characters used for link hints","depth":9,"help_text":"","role_description":"heading","subrole":"AXUnknown"},{"role":"AXStaticText","text":"Characters used for link hints","depth":10,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXTextField","text":"sadfjklewcmpgh","depth":10,"value":"sadfjklewcmpgh","help_text":"","role_description":"text field","subrole":"AXUnknown","is_enabled":true,"is_focused":false,"is_selected":false},{"role":"AXLink","text":"Reset","depth":11,"help_text":"","role_description":"link","subrole":"AXUnknown","is_enabled":true,"is_focused":false,"is_selected":false},{"role":"AXStaticText","text":"Reset","depth":12,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"The characters placed next to each link after typing \"f\" to enter link-hint mode.","depth":10,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXCheckBox","text":"Use smooth scrolling","depth":9,"help_text":"","role_description":"checkbox","subrole":"AXUnknown","is_enabled":true,"is_focused":false,"is_selected":false},{"role":"AXStaticText","text":"Use smooth scrolling","depth":9,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXCheckBox","text":"Use the link's name and characters for link-hint filtering","depth":9,"help_text":"","role_description":"checkbox","subrole":"AXUnknown","is_enabled":true,"is_focused":false,"is_selected":false},{"role":"AXStaticText","text":"Use the link's name and characters for link-hint filtering","depth":9,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"In link-hint mode, this option lets you select a link by typing its text.","depth":9,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXCheckBox","text":"Don't let pages steal the focus on load","depth":9,"help_text":"","role_description":"checkbox","subrole":"AXUnknown","is_enabled":true,"is_focused":false,"is_selected":false},{"role":"AXStaticText","text":"Don't let pages steal the focus on load","depth":9,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"Prevent pages from focusing an input on load (e.g. Google, Bing, etc.).","depth":9,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXCheckBox","text":"Hide the Heads Up Display (HUD) in insert mode","depth":9,"help_text":"","role_description":"checkbox","subrole":"AXUnknown","is_enabled":true,"is_focused":false,"is_selected":false},{"role":"AXStaticText","text":"Hide the Heads Up Display (HUD) in insert mode","depth":9,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"When enabled, the HUD will not be displayed in insert mode.","depth":9,"help_text":"","role_description":"text","subrole":"AXUnknown"}]...
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|
3810734493051242710
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click
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accessibility
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DXP4800PLUS-B5F8
Inbox (9) - [EMAIL] - Gmail
Sham DXP4800PLUS-B5F8
Inbox (9) - [EMAIL] - Gmail
Shameless • HBO Max
Shameless • HBO Max
Settings
Settings
firefox sidebar - Google Search
firefox sidebar - Google Search
How to use AI-enhanced tab groups | Firefox Help
How to use AI-enhanced tab groups | Firefox Help
Add-ons Manager
Add-ons Manager
Vimium – Get this Extension for 🦊 Firefox (en-US)
Vimium – Get this Extension for 🦊 Firefox (en-US)
dennikn.sk/
dennikn.sk/
Vimium Options
Vimium Options
Close tab
Loď Orion úspešne pristála na Zemi. Desať vecí, ktoré si pamätať o misii Artemis II — Denník N
Loď Orion úspešne pristála na Zemi. Desať vecí, ktoré si pamätať o misii Artemis II — Denník N
Machines - Tailscale
Machines - Tailscale
Screenpipe Dashboard
Screenpipe Dashboard
Add-ons for Firefox (en-US)
Add-ons for Firefox (en-US)
Pazaruvaj.com — Знак, че е време за най-добрите оферти
Pazaruvaj.com — Знак, че е време за най-добрите оферти
Bitwarden Password Manager – Get this Extension for 🦊 Firefox (en-US)
Bitwarden Password Manager – Get this Extension for 🦊 Firefox (en-US)
Browser Extension Getting Started | Bitwarden
Browser Extension Getting Started | Bitwarden
Extensions – Add-ons for Firefox (en-US)
Extensions – Add-ons for Firefox (en-US)
Dangbei Atom Review - RTINGS.com
Dangbei Atom Review - RTINGS.com
Screenpipe: Open Source 24/7 Screen & Audio Capture : r/software
Screenpipe: Open Source 24/7 Screen & Audio Capture : r/software
Add-ons for Firefox (en-US)
Add-ons for Firefox (en-US)
Problem loading page
Problem loading page
Welcome to Firefox
Welcome to Firefox
New Tab
Customize sidebar
Open Google Gemini (⌃X)
Open history (⇧⌘H)
Open bookmarks (⌘B)
Bitwarden
Vimium Options
Excluded URLs and keys
Excluded URLs and keys
Patterns
Keys to exclude
https?://mail.google.com/*
All
✖
Patterns
https?://mail.google.com/*
Keys to exclude
All
✖
Add rule
Disable Vimium on URLs.
"Patterns" are URL regular expressions.
*
will match zero or more characters.
"Keys": Vimium will exclude these keys and pass them through to the page.
Custom key mappings
Custom key mappings
# Insert your preferred key mappings here.
Example syntax:
map j scrollDown
map z2 setZoom level=2
unmap j
unmapAll
" this is a comment
# this is also a comment
See all available commands
See all available commands
.
Custom search engines
Custom search engines
w: https://www.wikipedia.org/w/index.php?title=Special:Search&search=%s Wikipedia
# More examples.
#
# (Vimium supports search completion Wikipedia, as
# above, and for these.)
#
# g: https://www.google.com/search?q=%s Google
# l: https://www.google.com/search?q=%s&btnI I'm feeling lucky...
# y: https://www.youtube.com/results?search_query=%s Youtube
# gm: https://www.google.com/maps?q=%s Google maps
# b: https://www.bing.com/search?q=%s Bing
# d: https://duckduckgo.com/?q=%s DuckDuckGo
# az: https://www.amazon.com/s/?field-keywords=%s
# qw: https://www.qwant.com/?q=%s Qwant
Add search-engine shortcuts to the Vomnibar. Format:
a: http://a.com/?q=%s
b: http://b.com/?q=%s description
" this is a comment
# this is also a comment
%s is replaced with the search terms.
For search completion, see
here
here
.
New tab URL
New tab URL
Vimium blank new tab page
Vimium blank new tab page
Open the Vomnibar when the page loads
Open the Vomnibar when the page loads
Browser's default new tab page
Browser's default new tab page
Custom URL
Custom URL
The page to open when using Vimium's "create new tab" command. To have Vimium commands work on
all
new tab pages opened by the browser, a separate Vimium new tab extension is required. See the full details
here
here
.
Advanced Options
Scroll step size
Scroll step size
60
px
The size for basic movements (usually j/k/h/l).
Characters used for link hints
Characters used for link hints
sadfjklewcmpgh
Reset
Reset
The characters placed next to each link after typing "f" to enter link-hint mode.
Use smooth scrolling
Use smooth scrolling
Use the link's name and characters for link-hint filtering
Use the link's name and characters for link-hint filtering
In link-hint mode, this option lets you select a link by typing its text.
Don't let pages steal the focus on load
Don't let pages steal the focus on load
Prevent pages from focusing an input on load (e.g. Google, Bing, etc.).
Hide the Heads Up Display (HUD) in insert mode
Hide the Heads Up Display (HUD) in insert mode
When enabled, the HUD will not be displayed in insert mode....
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/Users/lukas/.screenpipe/data/data/2026-04-13/1776 /Users/lukas/.screenpipe/data/data/2026-04-13/1776095304478_m1.jpg...
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Firefox
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Vimium Options — Personal
|
True
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moz-extension://f5e9c63e-b25b-4f15-8ba2-4813105e11 moz-extension://f5e9c63e-b25b-4f15-8ba2-4813105e11bb/pages/options.html...
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monitor_1
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NULL
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NULL
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NULL
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DXP4800PLUS-B5F8
Inbox (10) - [EMAIL] - Gmail
Sha DXP4800PLUS-B5F8
Inbox (10) - [EMAIL] - Gmail
Shameless • HBO Max
Shameless • HBO Max
Settings
Settings
firefox sidebar - Google Search
firefox sidebar - Google Search
How to use AI-enhanced tab groups | Firefox Help
How to use AI-enhanced tab groups | Firefox Help
Add-ons Manager
Add-ons Manager
Vimium – Get this Extension for 🦊 Firefox (en-US)
Vimium – Get this Extension for 🦊 Firefox (en-US)
dennikn.sk/
dennikn.sk/
Vimium Options
Vimium Options
Close tab
Loď Orion úspešne pristála na Zemi. Desať vecí, ktoré si pamätať o misii Artemis II — Denník N
Loď Orion úspešne pristála na Zemi. Desať vecí, ktoré si pamätať o misii Artemis II — Denník N
Machines - Tailscale
Machines - Tailscale
Screenpipe Dashboard
Screenpipe Dashboard
Pazaruvaj.com — Знак, че е време за най-добрите оферти
Pazaruvaj.com — Знак, че е време за най-добрите оферти
Browser Extension Getting Started | Bitwarden
Browser Extension Getting Started | Bitwarden
Extensions – Add-ons for Firefox (en-US)
Extensions – Add-ons for Firefox (en-US)
Dangbei Atom Review - RTINGS.com
Dangbei Atom Review - RTINGS.com
Screenpipe: Open Source 24/7 Screen & Audio Capture : r/software
Screenpipe: Open Source 24/7 Screen & Audio Capture : r/software
Add-ons for Firefox (en-US)
Add-ons for Firefox (en-US)
Problem loading page
Problem loading page
Welcome to Firefox
Welcome to Firefox
New Tab
Customize sidebar
Close Google Gemini (⌃X)
Open history (⇧⌘H)
Open bookmarks (⌘B)
Bitwarden
AI Chat settings
Close
Google Account: Lukáš Koválik ([EMAIL])
Main menu
New chat
Gemini
Temporary chat
PLUS
PLUS
Conversation with Gemini
Conversation with Gemini
Hi Lukáš
Where should we start?
Where should we start?
🖼️ Create image, button, tap to use tool
🖼️ Create image
🎸 Create music, button, tap to use tool
🎸 Create music
Boost my day, button, tap to use tool
Boost my day
Help me learn, button, tap to use tool
Help me learn
Write anything, button, tap to use tool
Write anything
Create a video, button, tap to use tool
Create a video
Dismiss
Try video templates instead of starting from scratch
Try it
Try it
Ask Gemini
Ask Gemini
Open upload file menu
Tools
Open mode picker
Pro
Microphone
Summarize page
Summarize page
Vimium Options
Excluded URLs and keys
Excluded URLs and keys
Patterns
Keys to exclude
https?://mail.google.com/*
All
✖
Patterns
https?://mail.google.com/*
Keys to exclude
All
✖
Add rule
Disable Vimium on URLs.
"Patterns" are URL regular expressions.
*
will match zero or more characters.
"Keys": Vimium will exclude these keys and pass them through to the page.
Custom key mappings
Custom key mappings
# Insert your preferred key mappings here.
Example syntax:
map j scrollDown
map z2 setZoom level=2
unmap j
unmapAll
" this is a comment
# this is also a comment
See all available commands
See all available commands
.
Custom search engines
Custom search engines
w: https://www.wikipedia.org/w/index.php?title=Special:Search&search=%s Wikipedia
# More examples.
#
# (Vimium supports search completion Wikipedia, as
# above, and for these.)
#
# g: https://www.google.com/search?q=%s Google
# l: https://www.google.com/search?q=%s&btnI I'm feeling lucky...
# y: https://www.youtube.com/results?search_query=%s Youtube
# gm: https://www.google.com/maps?q=%s Google maps
# b: https://www.bing.com/search?q=%s Bing
# d: https://duckduckgo.com/?q=%s DuckDuckGo
# az: https://www.amazon.com/s/?field-keywords=%s
# qw: https://www.qwant.com/?q=%s Qwant
Add search-engine shortcuts to the Vomnibar. Format:
a: http://a.com/?q=%s
b: http://b.com/?q=%s description
" this is a comment
# this is also a comment
%s is replaced with the search terms.
For search completion, see
here
here
.
New tab URL
New tab URL
Vimium blank new tab page
Vimium blank new tab page
Open the Vomnibar when the page loads
Open the Vomnibar when the page loads
Browser's default new tab page
Browser's default new tab page
Custom URL
Custom URL
The page to open when using Vimium's "create new tab" command. To have Vimium commands work on
all
new tab pages opened by the browser, a separate Vimium new tab extension is required. See the full details
here
here
.
Advanced Options
Scroll step size
Scroll step size
60
px
The size for basic movements (usually j/k/h/l).
Characters used for link hints
Characters used for link hints
sadfjklewcmpgh
Reset
Reset
The characters placed next to each link after typing "f" to enter link-hint mode.
Use smooth scrolling
Use smooth scrolling
Use the link's name and characters for link-hint filtering
Use the link's name and characters for link-hint filtering
In link-hint mode, this option lets you select a link by typing its text.
Don't let pages steal the focus on load
Don't let pages steal the focus on load
Prevent pages from focusing an input on load (e.g. Google, Bing, etc.).
Hide the Heads Up Display (HUD) in insert mode
Hide the Heads Up Display (HUD) in insert mode
When enabled, the HUD will not be displayed in insert mode.
Hide update notifications
Hide update notifications
When enabled, "Vimium has been updated" notifications will not be shown.
Treat find queries as JavaScript regular expressions
Treat find queries as JavaScript regular expressions
Switch back to plain find mode by using the
\R
escape sequence.
Ignore keyboard layout
Ignore keyboard layout
This forces the use of
en-US
QWERTY layout and can be helpful for non-Latin keyboards.
Previous patterns
Previous patterns
prev,previous,back,older,<,‹,←,«,≪,<<
Reset
Reset
The "navigate to previous page" command uses these patterns to find the link to follow.
Next patterns
Next patterns
next,more,newer,>,›,→,»,≫,>>
Reset
Reset
The "navigate to next page" command uses these patterns to find the link to follow.
CSS for Vimium UI
CSS for Vimium UI
div > .vimiumHintMarker {
/* linkhint boxes */
background: -webkit-gradient(linear, left top, left bottom, color-stop(0%,#FFF785),
color-stop(100%,#FFC542));
border: 1px solid #E3BE23;
}
div > .vimiumHintMarker span {
/* linkhint text */
color: black;
font-weight: bold;
font-size: 12px;
}
div > .vimiumHintMarker > .matchingCharacter {
}
Reset
Reset
These styles are applied to link hints, the Vomnibar, the help dialog, the exclusions pop-up and the HUD.
By default, this CSS is used to style the characters next to each link hint.
These styles are used in addition to and take precedence over Vimium's default styles.
[SEED_PHRASE].
Restore
Restore
Browse… No file selected.
Browse…
No file selected.
Choose a backup file to restore.
Type
?
to show the help dialog.
Type
Cmd-Enter
to save all options.
No changes...
|
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field","subrole":"AXUnknown","is_enabled":true,"is_focused":false,"is_selected":false},{"role":"AXButton","text":"✖","depth":12,"help_text":"","role_description":"button","subrole":"AXUnknown","is_enabled":true,"is_focused":false,"is_selected":false},{"role":"AXButton","text":"Add rule","depth":8,"help_text":"","role_description":"button","subrole":"AXUnknown","is_enabled":true,"is_focused":false,"is_selected":false},{"role":"AXStaticText","text":"Disable Vimium on URLs.","depth":9,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"\"Patterns\" are URL regular expressions.","depth":9,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"*","depth":10,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"will match zero or more characters.","depth":9,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"\"Keys\": Vimium will exclude these keys and pass them through to the page.","depth":9,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXHeading","text":"Custom key mappings","depth":8,"help_text":"","role_description":"heading","subrole":"AXUnknown"},{"role":"AXStaticText","text":"Custom key mappings","depth":9,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXTextArea","text":"# Insert your preferred key mappings here.","depth":8,"value":"# Insert your preferred key mappings here.","help_text":"","role_description":"text entry area","subrole":"AXUnknown","is_enabled":true,"is_focused":false,"is_selected":false},{"role":"AXStaticText","text":"Example syntax:","depth":9,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"map j scrollDown\nmap z2 setZoom level=2\nunmap j\nunmapAll\n\" this is a comment\n# this is also a comment","depth":10,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXLink","text":"See all available commands","depth":9,"help_text":"","role_description":"link","subrole":"AXUnknown","is_enabled":true,"is_focused":false,"is_selected":false},{"role":"AXStaticText","text":"See all available commands","depth":10,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":".","depth":9,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXHeading","text":"Custom search engines","depth":8,"help_text":"","role_description":"heading","subrole":"AXUnknown"},{"role":"AXStaticText","text":"Custom search engines","depth":9,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXTextArea","text":"w: https://www.wikipedia.org/w/index.php?title=Special:Search&search=%s Wikipedia\n\n# More examples.\n#\n# (Vimium supports search completion Wikipedia, as\n# above, and for these.)\n#\n# g: https://www.google.com/search?q=%s Google\n# l: https://www.google.com/search?q=%s&btnI I'm feeling lucky...\n# y: https://www.youtube.com/results?search_query=%s Youtube\n# gm: https://www.google.com/maps?q=%s Google maps\n# b: https://www.bing.com/search?q=%s Bing\n# d: https://duckduckgo.com/?q=%s DuckDuckGo\n# az: https://www.amazon.com/s/?field-keywords=%s\n# qw: https://www.qwant.com/?q=%s Qwant","depth":8,"value":"w: https://www.wikipedia.org/w/index.php?title=Special:Search&search=%s Wikipedia\n\n# More examples.\n#\n# (Vimium supports search completion Wikipedia, as\n# above, and for these.)\n#\n# g: https://www.google.com/search?q=%s Google\n# l: https://www.google.com/search?q=%s&btnI I'm feeling lucky...\n# y: https://www.youtube.com/results?search_query=%s Youtube\n# gm: https://www.google.com/maps?q=%s Google maps\n# b: https://www.bing.com/search?q=%s Bing\n# d: https://duckduckgo.com/?q=%s DuckDuckGo\n# az: https://www.amazon.com/s/?field-keywords=%s\n# qw: https://www.qwant.com/?q=%s Qwant","help_text":"","role_description":"text entry area","subrole":"AXUnknown","is_enabled":true,"is_focused":false,"is_selected":false},{"role":"AXStaticText","text":"Add search-engine shortcuts to the Vomnibar. Format:","depth":9,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"a: http://a.com/?q=%s\nb: http://b.com/?q=%s description\n\" this is a comment\n# this is also a comment","depth":10,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"%s is replaced with the search terms.","depth":9,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"For search completion, see","depth":9,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXLink","text":"here","depth":9,"help_text":"","role_description":"link","subrole":"AXUnknown","is_enabled":true,"is_focused":false,"is_selected":false},{"role":"AXStaticText","text":"here","depth":10,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":".","depth":9,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXHeading","text":"New tab URL","depth":8,"help_text":"","role_description":"heading","subrole":"AXUnknown"},{"role":"AXStaticText","text":"New tab URL","depth":9,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXRadioButton","text":"Vimium blank new tab page","depth":9,"help_text":"","role_description":"radio button","subrole":"AXUnknown","is_enabled":true,"is_focused":false,"is_selected":false},{"role":"AXStaticText","text":"Vimium blank new tab page","depth":10,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXCheckBox","text":"Open the Vomnibar when the page loads","depth":10,"help_text":"","role_description":"checkbox","subrole":"AXUnknown","is_enabled":true,"is_focused":false,"is_selected":false},{"role":"AXStaticText","text":"Open the Vomnibar when the page loads","depth":11,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXRadioButton","text":"Browser's default new tab page","depth":9,"help_text":"","role_description":"radio button","subrole":"AXUnknown","is_enabled":true,"is_focused":false,"is_selected":false},{"role":"AXStaticText","text":"Browser's default new tab page","depth":10,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXRadioButton","text":"Custom URL","depth":9,"help_text":"","role_description":"radio button","subrole":"AXUnknown","is_enabled":true,"is_focused":false,"is_selected":false},{"role":"AXStaticText","text":"Custom URL","depth":10,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"The page to open when using Vimium's \"create new tab\" command. To have Vimium commands work on","depth":9,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"all","depth":10,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"new tab pages opened by the browser, a separate Vimium new tab extension is required. See the full details","depth":9,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXLink","text":"here","depth":9,"help_text":"","role_description":"link","subrole":"AXUnknown","is_enabled":true,"is_focused":false,"is_selected":false},{"role":"AXStaticText","text":"here","depth":10,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":".","depth":9,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"Advanced Options","depth":9,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXHeading","text":"Scroll step size","depth":8,"help_text":"","role_description":"heading","subrole":"AXUnknown"},{"role":"AXStaticText","text":"Scroll step size","depth":9,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"60","depth":10,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"px","depth":9,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"The size for basic movements (usually j/k/h/l).","depth":9,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXHeading","text":"Characters used for link hints","depth":9,"help_text":"","role_description":"heading","subrole":"AXUnknown"},{"role":"AXStaticText","text":"Characters used for link hints","depth":10,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXTextField","text":"sadfjklewcmpgh","depth":10,"value":"sadfjklewcmpgh","help_text":"","role_description":"text field","subrole":"AXUnknown","is_enabled":true,"is_focused":false,"is_selected":false},{"role":"AXLink","text":"Reset","depth":11,"help_text":"","role_description":"link","subrole":"AXUnknown","is_enabled":true,"is_focused":false,"is_selected":false},{"role":"AXStaticText","text":"Reset","depth":12,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"The characters placed next to each link after typing \"f\" to enter link-hint mode.","depth":10,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXCheckBox","text":"Use smooth scrolling","depth":9,"help_text":"","role_description":"checkbox","subrole":"AXUnknown","is_enabled":true,"is_focused":false,"is_selected":false},{"role":"AXStaticText","text":"Use smooth scrolling","depth":9,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXCheckBox","text":"Use the link's name and characters for link-hint filtering","depth":9,"help_text":"","role_description":"checkbox","subrole":"AXUnknown","is_enabled":true,"is_focused":false,"is_selected":false},{"role":"AXStaticText","text":"Use the link's name and characters for link-hint filtering","depth":9,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"In link-hint mode, this option lets you select a link by typing its text.","depth":9,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXCheckBox","text":"Don't let pages steal the focus on load","depth":9,"help_text":"","role_description":"checkbox","subrole":"AXUnknown","is_enabled":true,"is_focused":false,"is_selected":false},{"role":"AXStaticText","text":"Don't let pages steal the focus on load","depth":9,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"Prevent pages from focusing an input on load (e.g. Google, Bing, etc.).","depth":9,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXCheckBox","text":"Hide the Heads Up Display (HUD) in insert mode","depth":9,"help_text":"","role_description":"checkbox","subrole":"AXUnknown","is_enabled":true,"is_focused":false,"is_selected":false},{"role":"AXStaticText","text":"Hide the Heads Up Display (HUD) in insert mode","depth":9,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"When enabled, the HUD will not be displayed in insert mode.","depth":9,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXCheckBox","text":"Hide update notifications","depth":9,"help_text":"","role_description":"checkbox","subrole":"AXUnknown","is_enabled":true,"is_focused":false,"is_selected":false},{"role":"AXStaticText","text":"Hide update notifications","depth":9,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"When enabled, \"Vimium has been updated\" notifications will not be shown.","depth":9,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXCheckBox","text":"Treat find queries as JavaScript regular expressions","depth":9,"help_text":"","role_description":"checkbox","subrole":"AXUnknown","is_enabled":true,"is_focused":false,"is_selected":false},{"role":"AXStaticText","text":"Treat find queries as JavaScript regular expressions","depth":9,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"Switch back to plain find mode by using the","depth":9,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"\\R","depth":10,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"escape sequence.","depth":9,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXCheckBox","text":"Ignore keyboard layout","depth":9,"help_text":"","role_description":"checkbox","subrole":"AXUnknown","is_enabled":true,"is_focused":false,"is_selected":false},{"role":"AXStaticText","text":"Ignore keyboard layout","depth":9,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"This forces the use of","depth":9,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"en-US","depth":10,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"QWERTY layout and can be helpful for non-Latin keyboards.","depth":9,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXHeading","text":"Previous patterns","depth":8,"bounds":{"left":0.12361111,"top":0.0,"width":0.7291667,"height":0.02111111},"help_text":"","role_description":"heading","subrole":"AXUnknown"},{"role":"AXStaticText","text":"Previous patterns","depth":9,"bounds":{"left":0.12361111,"top":0.0,"width":0.08680555,"height":0.02111111},"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXTextField","text":"prev,previous,back,older,<,‹,←,«,≪,<<","depth":9,"bounds":{"left":0.12361111,"top":0.0,"width":0.5069444,"height":0.027777778},"value":"prev,previous,back,older,<,‹,←,«,≪,<<","help_text":"","role_description":"text field","subrole":"AXUnknown","is_enabled":true,"is_focused":false,"is_selected":false},{"role":"AXLink","text":"Reset","depth":10,"bounds":{"left":0.6090278,"top":0.0,"width":0.021527778,"height":0.015555556},"help_text":"","role_description":"link","subrole":"AXUnknown","is_enabled":true,"is_focused":false,"is_selected":false},{"role":"AXStaticText","text":"Reset","depth":11,"bounds":{"left":0.6090278,"top":0.0,"width":0.021527778,"height":0.015555556},"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"The \"navigate to previous page\" command uses these patterns to find the link to follow.","depth":9,"bounds":{"left":0.64444447,"top":0.0,"width":0.19930555,"height":0.033333335},"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXHeading","text":"Next patterns","depth":8,"bounds":{"left":0.12361111,"top":0.0022222223,"width":0.7291667,"height":0.02111111},"help_text":"","role_description":"heading","subrole":"AXUnknown"},{"role":"AXStaticText","text":"Next patterns","depth":9,"bounds":{"left":0.12361111,"top":0.0022222223,"width":0.065972224,"height":0.02111111},"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXTextField","text":"next,more,newer,>,›,→,»,≫,>>","depth":9,"bounds":{"left":0.12361111,"top":0.036666665,"width":0.5069444,"height":0.027777778},"value":"next,more,newer,>,›,→,»,≫,>>","help_text":"","role_description":"text field","subrole":"AXUnknown","is_enabled":true,"is_focused":false,"is_selected":false},{"role":"AXLink","text":"Reset","depth":10,"bounds":{"left":0.6090278,"top":0.06555556,"width":0.021527778,"height":0.015555556},"help_text":"","role_description":"link","subrole":"AXUnknown","is_enabled":true,"is_focused":false,"is_selected":false},{"role":"AXStaticText","text":"Reset","depth":11,"bounds":{"left":0.6090278,"top":0.06555556,"width":0.021527778,"height":0.015555556},"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"The \"navigate to next page\" command uses these patterns to find the link to follow.","depth":9,"bounds":{"left":0.64444447,"top":0.037777778,"width":0.18402778,"height":0.033333335},"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXHeading","text":"CSS for Vimium UI","depth":8,"bounds":{"left":0.12361111,"top":0.09555556,"width":0.7291667,"height":0.02111111},"help_text":"","role_description":"heading","subrole":"AXUnknown"},{"role":"AXStaticText","text":"CSS for Vimium UI","depth":9,"bounds":{"left":0.12361111,"top":0.09555556,"width":0.093055554,"height":0.02111111},"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXTextArea","text":"div > .vimiumHintMarker {\n/* linkhint boxes */\nbackground: -webkit-gradient(linear, left top, left bottom, color-stop(0%,#FFF785),\n color-stop(100%,#FFC542));\nborder: 1px solid #E3BE23;\n}\n\ndiv > .vimiumHintMarker span {\n/* linkhint text */\ncolor: black;\nfont-weight: bold;\nfont-size: 12px;\n}\n\ndiv > .vimiumHintMarker > .matchingCharacter {\n}","depth":9,"bounds":{"left":0.12361111,"top":0.13111112,"width":0.5069444,"height":0.15555556},"value":"div > .vimiumHintMarker {\n/* linkhint boxes */\nbackground: -webkit-gradient(linear, left top, left bottom, color-stop(0%,#FFF785),\n color-stop(100%,#FFC542));\nborder: 1px solid #E3BE23;\n}\n\ndiv > .vimiumHintMarker span {\n/* linkhint text */\ncolor: black;\nfont-weight: bold;\nfont-size: 12px;\n}\n\ndiv > .vimiumHintMarker > .matchingCharacter {\n}","help_text":"","role_description":"text entry area","subrole":"AXUnknown","is_enabled":true,"is_focused":false,"is_selected":false},{"role":"AXLink","text":"Reset","depth":10,"bounds":{"left":0.6090278,"top":0.2888889,"width":0.021527778,"height":0.015555556},"help_text":"","role_description":"link","subrole":"AXUnknown","is_enabled":true,"is_focused":false,"is_selected":false},{"role":"AXStaticText","text":"Reset","depth":11,"bounds":{"left":0.6090278,"top":0.2888889,"width":0.021527778,"height":0.015555556},"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"These styles are applied to link hints, the Vomnibar, the help dialog, the exclusions pop-up and the HUD.","depth":9,"bounds":{"left":0.64444447,"top":0.13111112,"width":0.20347223,"height":0.033333335},"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"By default, this CSS is used to style the characters next to each link hint.","depth":9,"bounds":{"left":0.64444447,"top":0.16666667,"width":0.2048611,"height":0.033333335},"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"These styles are used in addition to and take precedence over Vimium's default styles.","depth":9,"bounds":{"left":0.64444447,"top":0.22,"width":0.16527778,"height":0.033333335},"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"Backup and Restore","depth":9,"bounds":{"left":0.12361111,"top":0.3288889,"width":0.11319444,"height":0.023333333},"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXHeading","text":"Backup","depth":8,"bounds":{"left":0.12361111,"top":0.38333333,"width":0.7291667,"height":0.02111111},"help_text":"","role_description":"heading","subrole":"AXUnknown"},{"role":"AXStaticText","text":"Backup","depth":9,"bounds":{"left":0.12361111,"top":0.38333333,"width":0.036805555,"height":0.02111111},"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXLink","text":"Download backup","depth":8,"bounds":{"left":0.12361111,"top":0.41777778,"width":0.5069444,"height":0.018888889},"help_text":"","role_description":"link","subrole":"AXUnknown","is_enabled":true,"is_focused":false,"is_selected":false},{"role":"AXStaticText","text":"Download backup","depth":9,"bounds":{"left":0.12361111,"top":0.4188889,"width":0.077083334,"height":0.017777778},"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"Download a backup of your settings.","depth":9,"bounds":{"left":0.64444447,"top":0.4188889,"width":0.13402778,"height":0.015555556},"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXHeading","text":"Restore","depth":8,"bounds":{"left":0.12361111,"top":0.45,"width":0.7291667,"height":0.02111111},"help_text":"","role_description":"heading","subrole":"AXUnknown"},{"role":"AXStaticText","text":"Restore","depth":9,"bounds":{"left":0.12361111,"top":0.45,"width":0.03888889,"height":0.02111111},"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXButton","text":"Browse… No file selected.","depth":8,"bounds":{"left":0.12361111,"top":0.48444444,"width":0.2777778,"height":0.024444444},"help_text":"","role_description":"button","subrole":"AXUnknown","is_enabled":true,"is_focused":false,"is_selected":false},{"role":"AXStaticText","text":"Browse…","depth":9,"bounds":{"left":0.12777779,"top":0.48777777,"width":0.03888889,"height":0.017777778},"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"No file selected.","depth":9,"bounds":{"left":0.17430556,"top":0.48777777,"width":0.07013889,"height":0.017777778},"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"Choose a backup file to restore.","depth":9,"bounds":{"left":0.64444447,"top":0.48555556,"width":0.11736111,"height":0.015555556},"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"Type","depth":10,"bounds":{"left":0.12361111,"top":0.0,"width":0.02013889,"height":0.015555556},"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"?","depth":11,"bounds":{"left":0.14375,"top":0.0,"width":0.0055555557,"height":0.015555556},"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"to show the help dialog.","depth":10,"bounds":{"left":0.14930555,"top":0.0,"width":0.08958333,"height":0.015555556},"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"Type","depth":10,"bounds":{"left":0.12361111,"top":0.0,"width":0.02013889,"height":0.015555556},"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"Cmd-Enter","depth":11,"bounds":{"left":0.14375,"top":0.0,"width":0.043055557,"height":0.015555556},"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"to save all options.","depth":10,"bounds":{"left":0.18680556,"top":0.0,"width":0.07083333,"height":0.015555556},"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXButton","text":"No changes","depth":10,"bounds":{"left":0.78541666,"top":0.0,"width":0.06736111,"height":0.025555555},"help_text":"","role_description":"button","subrole":"AXUnknown","is_enabled":false,"is_focused":false,"is_selected":false}]...
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8612826691778232576
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4462824084109494466
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click
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accessibility
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DXP4800PLUS-B5F8
Inbox (10) - [EMAIL] - Gmail
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Shameless • HBO Max
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Loď Orion úspešne pristála na Zemi. Desať vecí, ktoré si pamätať o misii Artemis II — Denník N
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Machines - Tailscale
Machines - Tailscale
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Screenpipe Dashboard
Pazaruvaj.com — Знак, че е време за най-добрите оферти
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Browser Extension Getting Started | Bitwarden
Browser Extension Getting Started | Bitwarden
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Dangbei Atom Review - RTINGS.com
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Screenpipe: Open Source 24/7 Screen & Audio Capture : r/software
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Platform Sprint 2 Q2 - Platform Team - Scrum Board Platform Sprint 2 Q2 - Platform Team - Scrum Board - Jira
SevenShores\Hubspot\Exceptions\BadRequest: Client error: `POST [URL_WITH_CREDENTIALS] Graham . I made the product related changes in the table and for the rest I left them as a note in the Technical section for the team to look at when they start looking at this. I wonder about your points related to GDPR. Currently multiple customers are using the Customer API/zapier to feed this data to AI and BI tools. They are also manually exporting transcripts and other information from the platform and feeding it to AI tools. I don’t get how MCP is so much different that all of these and why it will introduce new data processors (which are already being utilised) and would require any changes to the consent provided by participants.
You said
Jiminny MCP Connector
Epic
Link to Epik in Jira
Document status
DRAFT
Objective
Enable customers to connect Jiminny data to external AI tools (Claude, OpenAI, Gemini) so it can be used as part of their broader knowledge base and workflows.
Position Jiminny as a data layer for AI-driven revenue workflows, not just a standalone product.
👤 Target user
Revenue teams using AI tools (Sales, CS, RevOps)
Companies already experimenting with Claude / OpenAI
Mid-market & Enterprise customers with multiple data sources (CRM, docs, CI tools, Support tools etc)
🤕 Pain point or problem
Jiminny data is locked in the platform
AI tools lack access to high-value conversation context
Customers must manually export/copy transcripts
No easy way to combine calls with CRM + docs + other info - using the Jiminny API is not suitable for non technical sales people
Peer pressure as almost all competitors have this
💥 Impact and benefits
For customers
Better AI outputs using real customer conversations
Ability to build automated workflows across tools
For Jiminny
Increased product stickiness (embedded in workflows)
Competitive parity with Gong / Avoma etc.
💡 Solution ideas
Build an AI Knowledge Connector (MCP-based) that:
Exposes Jiminny data (calls, transcripts, metadata) to AI tools
Provides structured insights (summaries, action items, scoring etc.)
Supports deal-level context
Allows integration into customer-owned AI stacks (Claude + Zapier, etc.)
Success metrics
List the key goals and how you will measure success. Include both qualitative and quantitative metrics (e.g., user adoption, retention rate, revenue targets).
Goal
Metric
Increase stickiness by ensuring Jiminny is embedded in the customer’s workflows
% of customers connecting external AI tools
Number of MCP/API calls per customer - and which ones are being used the most
Decrease the manual copying of transcripts
decrease by X %
User interaction and design
Simple setup flow:
Generate API key / connect MCP
Clear instructions for Claude / Zapier setup
Provide:
Example prompts for Claude
Pre-built workflow templates for Zapier
Clear documentation - with use cases
👉 Focus: usable by non-technical users
Detailed Requirements
List the functional and non-functional requirements. Prioritize them (e.g., High, Medium, Low) and add notes for clarification.
Requirement
Importance
Notes
Allow customers to connect Jiminny to their AI tools (e.g. Claude, OpenAI)
HIGH
Provide MCP endpoint so customers can easily integrate Jiminny into their AI stack
Allow customers to access call data through AI tools
HIGH
Expose Jiminny data:
list calls (filter by date, user, account, deal)
get call
get transcript (speaker-separated)
get call metadata
search calls (keyword + semantic)
Support filtering by:
account / contact/ lead / deal
jiminny user
date range
Allow customers to search and query calls using AI tools
HIGH
Support keyword and semantic search across conversations
Provide structured insights so customers can generate better outputs
HIGH
For each call, expose:
Summary
Action items
Key points
Activity type
Notes
Call Score
CRM information
Allow customers to understand deal status across multiple calls/emails
HIGH
For each deal expose:
calls/meetings/emails
Identified risks
contacts related to the deal with their job title...
|
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Position Jiminny as a data layer for AI-driven revenue workflows, not just a standalone product. 👤 Target user Revenue teams using AI tools (Sales, CS, RevOps) Companies already experimenting with Claude / OpenAI Mid-market & Enterprise customers with multiple data sources (CRM, docs, CI tools, Support tools etc) 🤕 Pain point or problem Jiminny data is locked in the platform AI tools lack access to high-value conversation context Customers must manually export/copy transcripts No easy way to combine calls with CRM + docs + other info - using the Jiminny API is not suitable for non technical sales people Peer pressure as almost all competitors have this 💥 Impact and benefits For customers Better AI outputs using real customer conversations Ability to build automated workflows across tools For Jiminny Increased product stickiness (embedded in workflows) Competitive parity with Gong / Avoma etc. 💡 Solution ideas Build an AI Knowledge Connector (MCP-based) that: Exposes Jiminny data (calls, transcripts, metadata) to AI tools Provides structured insights (summaries, action items, scoring etc.) Supports deal-level context Allows integration into customer-owned AI stacks (Claude + Zapier, etc.) Success metrics List the key goals and how you will measure success. Include both qualitative and quantitative metrics (e.g., user adoption, retention rate, revenue targets). Goal Metric Increase stickiness by ensuring Jiminny is embedded in the customer’s workflows % of customers connecting external AI tools Number of MCP/API calls per customer - and which ones are being used the most Decrease the manual copying of transcripts decrease by X % User interaction and design Simple setup flow: Generate API key / connect MCP Clear instructions for Claude / Zapier setup Provide: Example prompts for Claude Pre-built workflow templates for Zapier Clear documentation - with use cases 👉 Focus: usable by non-technical users Detailed Requirements List the functional and non-functional requirements. Prioritize them (e.g., High, Medium, Low) and add notes for clarification. Requirement Importance Notes Allow customers to connect Jiminny to their AI tools (e.g. Claude, OpenAI) HIGH Provide MCP endpoint so customers can easily integrate Jiminny into their AI stack Allow customers to access call data through AI tools HIGH Expose Jiminny data: list calls (filter by date, user, account, deal) get call get transcript (speaker-separated) get call metadata search calls (keyword + semantic) Support filtering by: account / contact/ lead / deal jiminny user date range Allow customers to search and query calls using AI tools HIGH Support keyword and semantic search across conversations Provide structured insights so customers can generate better outputs HIGH For each call, expose: Summary Action items Key points Activity type Notes Call Score CRM information Allow customers to understand deal status across multiple calls/emails HIGH For each deal expose: calls/meetings/emails Identified risks contacts related to the deal with their job title linked account details all CRM field information that we have in DI + fields used for CRM filling example - get_deal_summary request - { \"tool\": \"get_deal_summary\", \"arguments\": { \"deal_name\": \"ACME\" } } responce: { \"deal_name\": \"ACME\", \"stage\": \"Negotiation\", \"recent_activity\": [ \"Demo call on 2026-04-01\", \"Pricing discussion on 2026-04-03\" ], \"risks\": [ \"Pricing concerns\", \"Security review pending\" ], \"next_steps\": [ \"Send follow-up to VP Sales\", \"Share security documentation\" ] } Ensure the AI can easily understand the schema of the data coming from Jiminny HIGH Models perform much better when tools have: clear names rich descriptions predictable schemas Provide clear, actionable error states for customers when MCP connections fail HIGH Error messages should guide agents toward solutions with specific suggestions and next steps. Expired or revoked key — “Error: Authentication failed. The API key used to access Jiminny has been revoked or has expired. Please ask your Jiminny admin to generate a new API key in Settings > Organization > General and reconnect the MCP server.” Rate limit hit — “Error: Rate limit exceeded. Too many requests have been made to the Jiminny MCP server in a short period. Please wait 60 seconds before retrying.” Permissions mismatch — if a user tries to access data outside their team visibility settings - “Error: Access denied. The requested call (call_id: [X]) is outside your team's visibility settings in Jiminny. Only calls within your permitted scope are accessible.” Trying to access private meeting - “Error: Access denied. This meeting has been marked as private by the host and cannot be accessed through the MCP connector. Try requesting a different call or ask the meeting host to change the visibility settings in Jiminny.” Downgraded/Capture account — if a customer's plan drops below Scale tier or the Customer is on Capture in the first place - “Error: MCP access unavailable. The Jiminny MCP connector is available on the Scale plan and above. Your account does not currently have an active Scale subscription.” Jiminny-side outage — “Error:Jiminny is temporarily unavailable (status 503). This is not a data or permissions issue — please retry in a few minutes.” No data found - “Error:No calls found matching your criteria. Try adjusting your filters — for example, widening the date range, removing the account filter, or checking the rep name is spelled correctly in Jiminny.” Allow customers to securely control who and what data is accessible externally HIGH Ensure MCP only exposes data user has access to - based on team visibility settings. This means that if a user is not allow to access calls/deals in Jiminny UI then they shouldn’t be able to access those through the MCP as well. Private meetings shouldn’t be exposed via MCP HIGH When a meetings is set to Private then the information about it shouldn’t be exposed through the MCP. Ensure Jiminny data can be combined with other sources (e.g. CRM, docs) in AI workflows HIGH Ensure data is structured to be easily combined with: CRM (accounts, deals) external docs Use consistent identifiers: account IDs deal IDs MCP is available only for Scale tier and above HIGH Customers who are on Capture tier should be able to access any of their data through MCP. This should also cover the scenario when a customer has been on Scale but then downgrades to Capture - their MCP access should stop working. Provide visibility into how external AI tools access Jiminny data HIGH Audit logs: what data was accessed by which external system when identity - who made the request specific queries/filters used failed access attempts (especially cross-visibility-boundary attempts) Admins should be able to access the logs from the org settings.We can start with a csv export before building a specific page for it. example from Atlassian - Provide customers with example prompts to get started quickly HIGH MCP prompts are explicitly defined as prompt templates that clients can discover and call with arguments. See examples in table below. Expose Jiminny as a Connector in Claude medium Competitors like Fathom are listed as Connectors in Claude. This will make it easier for customers to find us and to connect Jiminny Provide customers with example workflows to get started quickly medium A workflow is usually multiple steps, maybe multiple tools, still focused on one outcome. See examples in table below. Allow customers to use predefined Jiminny skills for common workflows medium Anthropic describes Skills as folders that include instructions, scripts, and resources that Claude can load when relevant, and as a way to teach Claude repeatable workflows, preferences, and domain expertise once instead of re-explaining them every time. Skills - a reusable package of behavior that can include prompts, instructions, resources, and sometimes scripts/tools for a broader job. Claude skills - https://resources.anthropic.com/hubfs/The-Complete-Guide-to-Building-Skill-for-Claude.pdf?hsLang=en&utm_source=chatgpt.com See examples in table below. Jiminny UI widget for OpenAI medium The reason to have this is to make certain Jiminny use cases much easier than pure chat. Instead of ChatGPT only replying with text like “Here are the last 5 ACME calls,” it could also show a visual Jiminny card or mini-app inside the chat. That widget could list calls, show a deal summary, let the user filter by rep/date/account, open a transcript section, or save a snippet—while the conversation continues in normal chat alongside it. For Jiminny, the best widget use cases are the ones where users need to browse or compare rather than ask one-off questions. A strong example is deal review: the user asks ChatGPT, “What is the status of the ACME deal?” ChatGPT calls your Jiminny MCP tools, and the widget shows a compact deal view with recent calls, risks, next steps, stakeholders, and links to transcripts/snippets. The chat can still summarize the answer in words, but the widget gives a clearer, scannable interface. Another good Jiminny widget use case is call search and exploration. A text answer can say “I found 12 calls mentioning pricing objections,” but a widget could show a sortable list with date, rep, account, score, and objection count, then let the user click into one call to see the exact excerpt or jump to a transcript section. Allow customers to run long-running analyses asynchronously and retrieve progress/results low Some requests/questions require analysis of Hugh volumes of data. For those, it may be better to: start the job let it run in the background return a status like “in progress” let the client come back for the result later For example - User asks in Claude: “Analyse all calls from this quarter and tell me the top 5 objections by segment.” That might require: searching lots of calls pulling many summaries/transcripts aggregating results Instead of making Claude wait 45+ seconds, Jiminny could: create an analysis job return: job_id = 123, status = running We need this in order to support: large-scale analysis multi-call aggregation across lots of data playlist generation across many calls heavy recap/report generation Creating a snippet through the MCP low Create a shareable snippet from a call recording by specifying a time range. Useful for highlighting key moments — objection handling, pricing discussions, competitive mentions — and sharing them with your team. example request: { \"tool\": \"create_snippet\", \"arguments\": { \"call_id\": \"call_123\", \"start_time\": \"00:18:24\", \"end_time\": \"00:19:10\", \"title\": \"Pricing objection\" } } example response: { \"snippet_id\": \"snip_987\", \"title\": \"Pricing objection\", \"share_url\": \"https://app.jiminny.com/snippets/snip_987\" } Ability to add recordings or snippets to a playlist low Allow customers to create libraries of calls automatically. They can use those for onboarding or other purposes Allow AI tools to read reusable Jiminny resources low fathom Resources are useful for data that should be read consistently rather than recomputed every time. In Jiminny terms, that could be: current deal snapshot account summary weekly rep recap approved talk tracks / objection handling guidance curated playlists or snippet libraries This is useful because an AI can consume these directly as context, instead of repeatedly stitching together many tool calls. Ability to write coaching notes in Jiminny through MCP low What we want to do for prompts/worflows and skills Capability Type User value / job to be done Example Jiminny use case Inputs Steps performed Output Draft follow-up email Prompt Help reps quickly create tailored follow-ups after calls Use the latest customer call to draft an email with recap and next steps Call ID optional tone optional recipient type Retrieve call summary and action items from Jiminny. Pull key points, commitments, and next steps. Apply the chosen tone and structure. Draft the email in a consistent format. Customer-ready follow-up email draft Summarise call Prompt Help users quickly extract the most important points from a conversation Generate a concise summary of one call for internal or external use Call ID optional summary style optional audience Retrieve transcript, metadata, and structured insights. Identify key topics, decisions, risks, and next steps. Format output for the chosen audience. Short or structured call summary with actions and risks Generate deal recap Prompt Help reps and managers get a fast overview of a deal Summarise the current state of a deal based on recent calls and linked CRM context Deal ID or account name optional date range Retrieve calls and meetings linked to the deal. Pull deal metadata and CRM-linked context. Identify recent changes, blockers, risks, and next steps. Summarise into a concise recap. Deal recap with status, blockers, risks, and recommended next steps Prepare weekly recap Prompt Help managers or reps review what changed over a time period Weekly recap of calls, themes, and actions for one rep, team, or account Rep ID team ID or account ID time period Retrieve relevant calls and summaries for the selected time period. Aggregate themes, action items, and changes. Highlight notable risks, opportunities, and follow-ups. Weekly recap with top themes, risks, opportunities, and actions Prepare deal review Workflow Help reps and managers review deal status using multiple sources of context Review a deal before pipeline review or forecast meeting Deal ID optional date range Retrieve all recent calls, emails, and meetings tied to the deal. Pull structured call summaries, score, action items, and key points. Pull linked CRM context such as stage, contacts, and account details. Aggregate open risks, unresolved objections, stakeholder gaps, and next steps. Format into a review-ready structure. Deal review document with current status, risks, stakeholders, blockers, and next steps Weekly team recap Workflow Help managers monitor activity and risk across a group of reps or accounts End-of-week team summary for sales leadership Team ID date range Retrieve calls and structured insights across the team. Group by rep, account, or deal. Identify recurring themes, major risks, strong calls, and missed follow-ups. Highlight calls or deals that need attention. Team-level recap with patterns, key risks, notable wins, and action areas Objection analysis across calls Workflow Help teams identify patterns across multiple conversations Analyse pricing or competitor objections across recent calls Account ID deal ID rep ID keyword/topic date range Search calls matching the topic or keyword. Retrieve summaries, transcripts, and snippets where relevant. Identify recurring objections and how they were handled. Assess whether objections were resolved or remain open. Summarise patterns and examples. Objection analysis with themes, frequency, examples, and suggested follow-up actions Build onboarding playlist Workflow Help enablement teams curate useful learning content faster Build a playlist of strong discovery, demo, or pricing calls for new hires Topic call type rep/team filter optional time period Search for calls matching the selected criteria. Rank or filter calls based on score, topics, or key moments. Identify useful snippets or full recordings. Add selected calls/snippets into a playlist structure. Generate short descriptions for each item. Curated onboarding playlist with selected calls/snippets and descriptions Deal Inspection Skill Skill Give users a consistent, opinionated way to assess a deal Claude reviews a deal using a repeatable Jiminny methodology Deal ID or account name optional review scope Determine whether the request is suitable for a deal inspection. Retrieve relevant calls, summaries, CRM context, stakeholders, and risks. Apply a standard Jiminny review framework to assess deal health. Look for missing next steps, unresolved objections, stakeholder gaps, and warning signs. Present findings in a consistent structure with recommended actions. Structured deal inspection with health assessment, red flags, and recommendations Manager Coaching Skill Skill Help managers review calls consistently and identify coaching moments Analyse a rep’s call and surface strengths, gaps, and examples for coaching Call ID optional rep ID optional coaching focus Retrieve transcript, score, summary, and key moments from the call. Evaluate the conversation against a coaching framework. Identify what went well and where the rep could improve. Suggest moments to clip as snippets. Recommend coaching actions or playlist additions. Coaching review with strengths, gaps, snippet suggestions, and recommended coaching actions CSM / QBR Prep Skill Skill Help CS or AM teams prepare structured customer reviews from conversations Generate an account review or QBR-style summary from recent customer interactions Account ID, optional time period Retrieve all recent calls, emails, and account-linked context. Aggregate themes, requests, blockers, sentiment shifts, and opportunities. Apply a repeatable account review structure. Summarise outcomes, open issues, and suggested next steps. Structured QBR/account review summary with themes, risks, opportunities, and actions Snippet Builder Skill Skill Help users consistently capture and label useful moments from calls Identify useful moments in a call and convert them into reusable snippets Call ID, optional focus area such as pricing, objection, competitor, discovery Retrieve transcript, recording timeline, and call insights. Detect moments matching the requested focus area. Propose snippet start/end times and titles. Tag snippets by type or theme. Optionally save them or add them to a playlist. One or more proposed or saved snippets with title, timing, and tags 💡 Technical details Auth model needs specifying. Are API keys scoped per user, per team, or per Jiminny instance? If a key is generated by an admin, does it inherit their visibility level, or provide org-wide? Are permissions evaluated at query time or frozen at key creation? Needs to be query-time, otherwise permission changes won't propagate. Key lifecycle management is missing. No mention of rotation, expiry, or revocation. A departed employee's active key is a data leak. Need: revocation, optional expiry, alerts on stale keys, and consider whether keys should be tied to service accounts rather than personal users. Rate limiting should be HIGH. A compromised key or misconfigured automation could bulk-export an entire customer's call history. Need per-key rate limits and anomaly detection on unusual access patterns. Open Questions Track unresolved issues or decisions that need to be made. Update as answers become available. Question Answer Date Answered Competitor research Competitor MCP Availability Core Capabilities Advanced Capabilities Positioning Key Strength Key Weakness Gong ✅ Mature MCP List/search calls Get transcripts get Call metadata Deal intelligence Scorecards, analytics CRM context Enterprise data layer Deep data + ecosystem integrations Limited opinionated AI workflows Avoma ✅ Mature MCP list_meetings get_meeting get_transcript key topics Deal fields/Deal level analysis Coaching/Scoring CRM context pushing insights into Notion / Confluence AI-ready meeting intelligence Strongest “outputs” layer Mostly pull-based interactions Fathom ✅ MCP list/search meetings get transcript get summary/action items Team/org context Webhooks (event-based triggers) get_weekly_recap aggregated action items across meetings creating webhooks directly from the MCP server Lightweight meeting data access Includes summaries + actions Limited analytics depth Grain ✅ Basic MCP get meetings download transcripts Notes Deals Scorecards Data access utility Simple + accessible Low sophistication, sometimes browser-based Outreach ⚠️ MCP (workflow-focused) Search sequences Emails Meetings (Kaia) account / prospect / opportunity lookups Workflow automation Multi-system orchestration Revenue workflow engine End-to-end GTM workflows Less depth in conversation data Attention ⚠️ Emerging MCP Meeting data Transcripts CRM-linked context AI insights Sales assistant workflows create snippets AI sales assistant + CRM Strong CRM linkage Less focus on external knowledge layer Planhat - Related content Ask Jiminny Anything on Call level Galya Dimitrova Hubspot app Galya Dimitrova Product Vision & Strategy Galya Dimitrova Automated CRM Filling Simona Georgieva (Deactivated) Competitive analysis Galya Dimitrova AI agent ideas Steliyan Georgiev Comments James Graham 9 Apr A few areas around Security & Compliance that need more depth before this moves beyond draft: Auth model needs specifying. Are API keys scoped per user, per team, or per Jiminny instance? If a key is generated by an admin, does it inherit their visibility level, or provide org-wide? Are permissions evaluated at query time or frozen at key creation? Needs to be query-time, otherwise permission changes won't propagate. Team visibility enforcement should be its own HIGH requirement. The current note under access control (\"ensure MCP only exposes data user has access to\") is doing too much work as a single line. Every MCP tool response (especially search_calls and deal-level aggregations) must be filtered through the same visibility engine as the UI. Semantic search is the riskiest here; it could surface results across team boundaries if not properly scoped. No data minimisation or scoping controls. We're exposing transcripts, CRM fields, contact details with job titles, deal context - significant PII and commercial data leaving the platform. Can customers configure which data types are exposed? Can transcripts be PII-stripped before they leave Jiminny? Given we position GDPR consent as a differentiator, we should be thinking about this. GDPR downstream processing is unaddressed. Piping transcripts to OpenAI/Gemini introduces new data processors. Customers need to acknowledge responsibility for downstream processing during setup. We should also consider whether call participants' recording consent covers onward sharing to third-party AI - it almost certainly doesn't by default. This is one for me to pick up. Key lifecycle management is missing. No mention of rotation, expiry, or revocation. A departed employee's active key is a data leak. Need: revocation, optional expiry, alerts on stale keys, and consider whether keys should be tied to service accounts rather than personal users. Rate limiting should be HIGH. A compromised key or misconfigured automation could bulk-export an entire customer's call history. Need per-key rate limits and anomaly detection on unusual access patterns. Audit logs should go deeper. Current spec (what data, which system, when) is a start. Add: identity behind the key, specific queries/filters used, and failed access attempts (especially cross-visibility-boundary attempts). Enterprise compliance teams will expect this. Downgrade handling. Doc says Scale tier and above, but doesn't say what happens on downgrade. Keys should auto-deactivate. Happy to help draft a dedicated Security & Compliance section if useful. Galya Dimitrova 15 Apr Thanks for the input @James Graham . I made the product related changes in the table and for the rest I left them as a note in the Technical section for the team to look at when they start looking at this. I wonder about your points related to GDPR. Currently multiple customers are using the Customer API/zapier to feed this data to AI and BI tools. They are also manually exporting transcripts and other information from the platform and feeding it to AI tools. 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using the Jiminny API is not suitable for non technical sales people","depth":23,"bounds":{"left":0.30868056,"top":0.4677778,"width":0.1,"height":0.24055555},"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"Peer pressure as almost all competitors have this","depth":23,"bounds":{"left":0.30868056,"top":0.71666664,"width":0.0875,"height":0.116111115},"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"💥 Impact and benefits","depth":23,"bounds":{"left":0.30868056,"top":0.9027778,"width":0.07083333,"height":0.054444443},"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"For customers","depth":23,"bounds":{"left":0.30868056,"top":0.96555555,"width":0.072222225,"height":0.022777777},"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"Better AI outputs using real customer conversations","depth":23,"bounds":{"left":0.30868056,"top":0.99666667,"width":0.099305555,"height":0.0033333302},"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"Ability to build automated workflows across tools","depth":23,"bounds":{"left":0.30868056,"top":1.0,"width":0.08715278,"height":-0.09000003},"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"For Jiminny","depth":23,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"Increased product stickiness (embedded in workflows)","depth":23,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"Competitive parity with Gong / Avoma etc.","depth":23,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"💡 Solution ideas","depth":23,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"Build an AI Knowledge Connector (MCP-based) that:","depth":23,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"Exposes Jiminny data (calls, transcripts, metadata) to AI tools","depth":23,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"Provides structured insights (summaries, action items, scoring etc.)","depth":23,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"Supports deal-level context","depth":23,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"Allows integration into customer-owned AI stacks (Claude + Zapier, etc.)","depth":23,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"Success metrics","depth":23,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"List the key goals and how you will measure success. 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each deal expose:","depth":23,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"calls/meetings/emails","depth":23,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"Identified risks","depth":23,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"contacts related to the deal with their job title","depth":23,"help_text":"","role_description":"text","subrole":"AXUnknown"}]...
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Platform Sprint 2 Q2 - Platform Team - Scrum Board Platform Sprint 2 Q2 - Platform Team - Scrum Board - Jira
SevenShores\Hubspot\Exceptions\BadRequest: Client error: `POST [URL_WITH_CREDENTIALS] Graham . I made the product related changes in the table and for the rest I left them as a note in the Technical section for the team to look at when they start looking at this. I wonder about your points related to GDPR. Currently multiple customers are using the Customer API/zapier to feed this data to AI and BI tools. They are also manually exporting transcripts and other information from the platform and feeding it to AI tools. I don’t get how MCP is so much different that all of these and why it will introduce new data processors (which are already being utilised) and would require any changes to the consent provided by participants.
You said
Jiminny MCP Connector
Epic
Link to Epik in Jira
Document status
DRAFT
Objective
Enable customers to connect Jiminny data to external AI tools (Claude, OpenAI, Gemini) so it can be used as part of their broader knowledge base and workflows.
Position Jiminny as a data layer for AI-driven revenue workflows, not just a standalone product.
👤 Target user
Revenue teams using AI tools (Sales, CS, RevOps)
Companies already experimenting with Claude / OpenAI
Mid-market & Enterprise customers with multiple data sources (CRM, docs, CI tools, Support tools etc)
🤕 Pain point or problem
Jiminny data is locked in the platform
AI tools lack access to high-value conversation context
Customers must manually export/copy transcripts
No easy way to combine calls with CRM + docs + other info - using the Jiminny API is not suitable for non technical sales people
Peer pressure as almost all competitors have this
💥 Impact and benefits
For customers
Better AI outputs using real customer conversations
Ability to build automated workflows across tools
For Jiminny
Increased product stickiness (embedded in workflows)
Competitive parity with Gong / Avoma etc.
💡 Solution ideas
Build an AI Knowledge Connector (MCP-based) that:
Exposes Jiminny data (calls, transcripts, metadata) to AI tools
Provides structured insights (summaries, action items, scoring etc.)
Supports deal-level context
Allows integration into customer-owned AI stacks (Claude + Zapier, etc.)
Success metrics
List the key goals and how you will measure success. Include both qualitative and quantitative metrics (e.g., user adoption, retention rate, revenue targets).
Goal
Metric
Increase stickiness by ensuring Jiminny is embedded in the customer’s workflows
% of customers connecting external AI tools
Number of MCP/API calls per customer - and which ones are being used the most
Decrease the manual copying of transcripts
decrease by X %
User interaction and design
Simple setup flow:
Generate API key / connect MCP
Clear instructions for Claude / Zapier setup
Provide:
Example prompts for Claude
Pre-built workflow templates for Zapier
Clear documentation - with use cases
👉 Focus: usable by non-technical users
Detailed Requirements
List the functional and non-functional requirements. Prioritize them (e.g., High, Medium, Low) and add notes for clarification.
Requirement
Importance
Notes
Allow customers to connect Jiminny to their AI tools (e.g. Claude, OpenAI)
HIGH
Provide MCP endpoint so customers can easily integrate Jiminny into their AI stack
Allow customers to access call data through AI tools
HIGH
Expose Jiminny data:
list calls (filter by date, user, account, deal)
get call
get transcript (speaker-separated)
get call metadata
search calls (keyword + semantic)
Support filtering by:
account / contact/ lead / deal
jiminny user
date range
Allow customers to search and query calls using AI tools
HIGH
Support keyword and semantic search across conversations
Provide structured insights so customers can generate better outputs
HIGH
For each call, expose:
Summary
Action items
Key points
Activity type
Notes
Call Score
CRM information
Allow customers to understand deal status across multiple calls/emails
HIGH
For each deal expose:
calls/meetings/emails
Identified risks
contacts related to the deal with their job title...
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Platform Sprint 2 Q2 - Platform Team - Scrum Board Platform Sprint 2 Q2 - Platform Team - Scrum Board - Jira
SevenShores\Hubspot\Exceptions\BadRequest: Client error: `POST https://api.hubapi.com/crm/v3/objects/contact/search` resulted in a `429 Too Many Requests` response: {"status":"error","message":"You have reached your secondly limit.","errorType":"RATE_LIMIT
SevenShores\Hubspot\Exceptions\BadRequest: Client error: `POST https://api.hubapi.com/crm/v3/objects/contact/search` resulted in a `429 Too Many Requests` response: {"status":"error","message":"You have reached your secondly limit.","errorType":"RATE_LIMIT
[JY-20372] AI Reports > Empty page design and promotion - Jira
[JY-20372] AI Reports > Empty page design and promotion - Jira
Jiminny MCP Connector - Product - Confluence
Jiminny MCP Connector - Product - Confluence
Jiminny
Jiminny
Workers | Datadog
Workers | Datadog
Pull requests · jiminny/app
Pull requests · jiminny/app
[JY-20728] [HubSpot] Find the root cause of 429 hit and tweak API client rate limiter - Jira
[JY-20728] [HubSpot] Find the root cause of 429 hit and tweak API client rate limiter - Jira
JY-9712 | Nuges to expire after one year by nikolaybiaivanov · Pull Request #11981 · jiminny/app
JY-9712 | Nuges to expire after one year by nikolaybiaivanov · Pull Request #11981 · jiminny/app
Jiminny
Jiminny
CloudWatch | us-east-2
CloudWatch | us-east-2
Your 'Not enpough activities' report wasn't generated - [EMAIL] - Jiminny Mail
Your 'Not enpough activities' report wasn't generated - [EMAIL] - Jiminny Mail...
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SevenShores\Hubspot\Exceptions\BadRequest: Client error: `POST https://api.hubapi.com/crm/v3/objects/contact/search` resulted in a `429 Too Many Requests` response: {"status":"error","message":"You have reached your secondly limit.","errorType":"RATE_LIMIT
SevenShores\Hubspot\Exceptions\BadRequest: Client error: `POST https://api.hubapi.com/crm/v3/objects/contact/search` resulted in a `429 Too Many Requests` response: {"status":"error","message":"You have reached your secondly limit.","errorType":"RATE_LIMIT
[JY-20372] AI Reports > Empty page design and promotion - Jira
[JY-20372] AI Reports > Empty page design and promotion - Jira
Jiminny MCP Connector - Product - Confluence
Jiminny MCP Connector - Product - Confluence
Jiminny
Jiminny
Workers | Datadog
Workers | Datadog
Pull requests · jiminny/app
Pull requests · jiminny/app
[JY-20728] [HubSpot] Find the root cause of 429 hit and tweak API client rate limiter - Jira
[JY-20728] [HubSpot] Find the root cause of 429 hit and tweak API client rate limiter - Jira
JY-9712 | Nuges to expire after one year by nikolaybiaivanov · Pull Request #11981 · jiminny/app
JY-9712 | Nuges to expire after one year by nikolaybiaivanov · Pull Request #11981 · jiminny/app
Jiminny
Jiminny
CloudWatch | us-east-2
CloudWatch | us-east-2
Your 'Not enpough activities' report wasn't generated - [EMAIL] - Jiminny Mail
Your 'Not enpough activities' report wasn't generated - [EMAIL] - Jiminny Mail...
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Platform Sprint 2 Q2 - Platform Team - Scrum Board Platform Sprint 2 Q2 - Platform Team - Scrum Board - Jira
SevenShores\Hubspot\Exceptions\BadRequest: Client error: `POST [URL_WITH_CREDENTIALS] Graham . I made the product related changes in the table and for the rest I left them as a note in the Technical section for the team to look at when they start looking at this. I wonder about your points related to GDPR. Currently multiple customers are using the Customer API/zapier to feed this data to AI and BI tools. They are also manually exporting transcripts and other information from the platform and feeding it to AI tools. I don’t get how MCP is so much different that all of these and why it will introduce new data processors (which are already being utilised) and would require any changes to the consent provided by participants.
You said
Jiminny MCP Connector
Epic
Link to Epik in Jira
Document status
DRAFT
Objective
Enable customers to connect Jiminny data to external AI tools (Claude, OpenAI, Gemini) so it can be used as part of their broader knowledge base and workflows.
Position Jiminny as a data layer for AI-driven revenue workflows, not just a standalone product.
👤 Target user
Revenue teams using AI tools (Sales, CS, RevOps)
Companies already experimenting with Claude / OpenAI
Mid-market & Enterprise customers with multiple data sources (CRM, docs, CI tools, Support tools etc)
🤕 Pain point or problem
Jiminny data is locked in the platform
AI tools lack access to high-value conversation context
Customers must manually export/copy transcripts
No easy way to combine calls with CRM + docs + other info - using the Jiminny API is not suitable for non technical sales people
Peer pressure as almost all competitors have this
💥 Impact and benefits
For customers
Better AI outputs using real customer conversations
Ability to build automated workflows across tools
For Jiminny
Increased product stickiness (embedded in workflows)
Competitive parity with Gong / Avoma etc.
💡 Solution ideas
Build an AI Knowledge Connector (MCP-based) that:
Exposes Jiminny data (calls, transcripts, metadata) to AI tools
Provides structured insights (summaries, action items, scoring etc.)
Supports deal-level context
Allows integration into customer-owned AI stacks (Claude + Zapier, etc.)
Success metrics
List the key goals and how you will measure success. Include both qualitative and quantitative metrics (e.g., user adoption, retention rate, revenue targets).
Goal
Metric
Increase stickiness by ensuring Jiminny is embedded in the customer’s workflows
% of customers connecting external AI tools
Number of MCP/API calls per customer - and which ones are being used the most
Decrease the manual copying of transcripts
decrease by X %
User interaction and design
Simple setup flow:
Generate API key / connect MCP
Clear instructions for Claude / Zapier setup
Provide:
Example prompts for Claude
Pre-built workflow templates for Zapier
Clear documentation - with use cases
👉 Focus: usable by non-technical users
Detailed Requirements
List the functional and non-functional requirements. Prioritize them (e.g., High, Medium, Low) and add notes for clarification.
Requirement
Importance
Notes
Allow customers to connect Jiminny to their AI tools (e.g. Claude, OpenAI)
HIGH
Provide MCP endpoint so customers can easily integrate Jiminny into their AI stack
Allow customers to access call data through AI tools
HIGH
Expose Jiminny data:
list calls (filter by date, user, account, deal)
get call
get transcript (speaker-separated)
get call metadata
search calls (keyword + semantic)
Support filtering by:
account / contact/ lead / deal
jiminny user
date range
Allow customers to search and query calls using AI tools
HIGH
Support keyword and semantic search across conversations
Provide structured insights so customers can generate better outputs
HIGH
For each call, expose:
Summary
Action items
Key points
Activity type
Notes
Call Score
CRM information
Allow customers to understand deal status across multiple calls/emails
HIGH
For each deal expose:
calls/meetings/emails
Identified risks
contacts related to the deal with their job title
linked account details
all CRM field information that we have in DI + fields used for CRM filling
example - get_deal_summary
request -
{
"tool": "get_deal_summary",
"arguments": {
"deal_name": "ACME"
}
}
responce:
{
"deal_name": "ACME",
"stage": "Negotiation",
"recent_activity": [
"Demo call on 2026-04-01",
"Pricing discussion on 2026-04-03"
],
"risks": [
"Pricing concerns",
"Security review pending"
], "next_steps": [
"Send follow-up to VP Sales",
"Share security documentation"
]
}
Ensure the AI can easily understand the schema of the data coming from Jiminny
HIGH
Models perform much better when tools have:
clear names
rich descriptions
predictable schemas
Provide clear, actionable error states for customers when MCP connections fail
HIGH
Error messages should guide agents toward solutions with specific suggestions and next steps.
Expired or revoked key — “Error: Authentication failed. The API key used to access Jiminny has been revoked or has expired. Please ask your Jiminny admin to generate a new API key in Settings > Organization > General and reconnect the MCP server.”
Rate limit hit — “Error: Rate limit exceeded. Too many requests have been made to the Jiminny MCP server in a short period. Please wait 60 seconds before retrying.”
Permissions mismatch — if a user tries to access data outside their team visibility settings - “Error: Access denied. The requested call (call_id: [X]) is outside your team's visibility settings in Jiminny. Only calls within your permitted scope are accessible.”
Trying to access private meeting - “Error: Access denied. This meeting has been marked as private by the host and cannot be accessed through the MCP connector. Try requesting a different call or ask the meeting host to change the visibility settings in Jiminny.”
Downgraded/Capture account — if a customer's plan drops below Scale tier or the Customer is on Capture in the first place - “Error: MCP access unavailable. The Jiminny MCP connector is available on the Scale plan and above. Your account does not currently have an active Scale subscription.”
Jiminny-side outage — “Error:Jiminny is temporarily unavailable (status 503). This is not a data or permissions issue — please retry in a few minutes.”
No data found - “Error:No calls found matching your criteria. Try adjusting your filters — for example, widening the date range, removing the account filter, or checking the rep name is spelled correctly in Jiminny.”
Allow customers to securely control who and what data is accessible externally
HIGH
Ensure MCP only exposes data user has access to - based on team visibility settings. This means that if a user is not allow to access calls/deals in Jiminny UI then they shouldn’t be able to access those through the MCP as well.
Private meetings shouldn’t be exposed via MCP
HIGH
When a meetings is set to Private then the information about it shouldn’t be exposed through the MCP.
Ensure Jiminny data can be combined with other sources (e.g. CRM, docs) in AI workflows
HIGH
Ensure data is structured to be easily combined with:
CRM (accounts, deals)
external docs
Use consistent identifiers:
account IDs
deal IDs
MCP is available only for Scale tier and above
HIGH
Customers who are on Capture tier should be able to access any of their data through MCP.
This should also cover the scenario when a customer has been on Scale but then downgrades to Capture - their MCP access should stop working.
Provide visibility into how external AI tools access Jiminny data
HIGH
Audit logs:
what data was accessed by which external system when
identity - who made the request
specific queries/filters used
failed access attempts (especially cross-visibility-boundary attempts)
Admins should be able to access the logs from the org settings.We can start with a csv export before building a specific page for it.
example from Atlassian -
Provide customers with example prompts to get started quickly
HIGH
MCP prompts are explicitly defined as prompt templates that clients can discover and call with arguments.
See examples in table below.
Expose Jiminny as a Connector in Claude
medium
Competitors like Fathom are listed as Connectors in Claude. This will make it easier for customers to find us and to connect Jiminny
Provide customers with example workflows to get started quickly
medium
A workflow is usually multiple steps, maybe multiple tools, still focused on one outcome.
See examples in table below.
Allow customers to use predefined Jiminny skills for common workflows
medium
Anthropic describes Skills as folders that include instructions, scripts, and resources that Claude can load when relevant, and as a way to teach Claude repeatable workflows, preferences, and domain expertise once instead of re-explaining them every time. Skills - a reusable package of behavior that can include prompts, instructions, resources, and sometimes scripts/tools for a broader job.
Claude skills - https://resources.anthropic.com/hubfs/The-Complete-Guide-to-Building-Skill-for-Claude.pdf?hsLang=en&utm_source=chatgpt.com
See examples in table below.
Jiminny UI widget for OpenAI
medium
The reason to have this is to make certain Jiminny use cases much easier than pure chat.
Instead of ChatGPT only replying with text like “Here are the last 5 ACME calls,” it could also show a visual Jiminny card or mini-app inside the chat. That widget could list calls, show a deal summary, let the user filter by rep/date/account, open a transcript section, or save a snippet—while the conversation continues in normal chat alongside it.
For Jiminny, the best widget use cases are the ones where users need to browse or compare rather than ask one-off questions. A strong example is deal review: the user asks ChatGPT, “What is the status of the ACME deal?” ChatGPT calls your Jiminny MCP tools, and the widget shows a compact deal view with recent calls, risks, next steps, stakeholders, and links to transcripts/snippets. The chat can still summarize the answer in words, but the widget gives a clearer, scannable interface.
Another good Jiminny widget use case is call search and exploration. A text answer can say “I found 12 calls mentioning pricing objections,” but a widget could show a sortable list with date, rep, account, score, and objection count, then let the user click into one call to see the exact excerpt or jump to a transcript section.
Allow customers to run long-running analyses asynchronously and retrieve progress/results
low
Some requests/questions require analysis of Hugh volumes of data. For those, it may be better to:
start the job
let it run in the background
return a status like “in progress”
let the client come back for the result later
For example - User asks in Claude:
“Analyse all calls from this quarter and tell me the top 5 objections by segment.”
That might require:
searching lots of calls
pulling many summaries/transcripts
aggregating results
Instead of making Claude wait 45+ seconds, Jiminny could:
create an analysis job
return: job_id = 123, status = running
We need this in order to support:
large-scale analysis
multi-call aggregation across lots of data
playlist generation across many calls
heavy recap/report generation
Creating a snippet through the MCP
low
Create a shareable snippet from a call recording by specifying a time range. Useful for highlighting key moments — objection handling, pricing discussions, competitive mentions — and sharing them with your team.
example request:
{
"tool": "create_snippet",
"arguments": {
"call_id": "call_123",
"start_time": "00:18:24",
"end_time": "00:19:10",
"title": "Pricing objection"
}
}
example response:
{
"snippet_id": "snip_987",
"title": "Pricing objection",
"share_url": "https://app.jiminny.com/snippets/snip_987"
}
Ability to add recordings or snippets to a playlist
low
Allow customers to create libraries of calls automatically. They can use those for onboarding or other purposes
Allow AI tools to read reusable Jiminny resources
low
fathom
Resources are useful for data that should be read consistently rather than recomputed every time. In Jiminny terms, that could be:
current deal snapshot
account summary
weekly rep recap
approved talk tracks / objection handling guidance
curated playlists or snippet libraries
This is useful because an AI can consume these directly as context, instead of repeatedly stitching together many tool calls.
Ability to write coaching notes in Jiminny through MCP
low
What we want to do for prompts/worflows and skills
Capability
Type
User value / job to be done
Example Jiminny use case
Inputs
Steps performed
Output
Draft follow-up email
Prompt
Help reps quickly create tailored follow-ups after calls
Use the latest customer call to draft an email with recap and next steps
Call ID
optional tone
optional recipient type
Retrieve call summary and action items from Jiminny.
Pull key points, commitments, and next steps.
Apply the chosen tone and structure.
Draft the email in a consistent format.
Customer-ready follow-up email draft
Summarise call
Prompt
Help users quickly extract the most important points from a conversation
Generate a concise summary of one call for internal or external use
Call ID
optional summary style
optional audience
Retrieve transcript, metadata, and structured insights.
Identify key topics, decisions, risks, and next steps.
Format output for the chosen audience.
Short or structured call summary with actions and risks
Generate deal recap
Prompt
Help reps and managers get a fast overview of a deal
Summarise the current state of a deal based on recent calls and linked CRM context
Deal ID or account name
optional date range
Retrieve calls and meetings linked to the deal.
Pull deal metadata and CRM-linked context.
Identify recent changes, blockers, risks, and next steps.
Summarise into a concise recap.
Deal recap with status, blockers, risks, and recommended next steps
Prepare weekly recap
Prompt
Help managers or reps review what changed over a time period
Weekly recap of calls, themes, and actions for one rep, team, or account
Rep ID
team ID or account ID
time period
Retrieve relevant calls and summaries for the selected time period.
Aggregate themes, action items, and changes.
Highlight notable risks, opportunities, and follow-ups.
Weekly recap with top themes, risks, opportunities, and actions
Prepare deal review
Workflow
Help reps and managers review deal status using multiple sources of context
Review a deal before pipeline review or forecast meeting
Deal ID
optional date range
Retrieve all recent calls, emails, and meetings tied to the deal.
Pull structured call summaries, score, action items, and key points.
Pull linked CRM context such as stage, contacts, and account details.
Aggregate open risks, unresolved objections, stakeholder gaps, and next steps.
Format into a review-ready structure.
Deal review document with current status, risks, stakeholders, blockers, and next steps
Weekly team recap
Workflow
Help managers monitor activity and risk across a group of reps or accounts
End-of-week team summary for sales leadership
Team ID
date range
Retrieve calls and structured insights across the team.
Group by rep, account, or deal.
Identify recurring themes, major risks, strong calls, and missed follow-ups.
Highlight calls or deals that need attention.
Team-level recap with patterns, key risks, notable wins, and action areas
Objection analysis across calls
Workflow
Help teams identify patterns across multiple conversations
Analyse pricing or competitor objections across recent calls
Account ID
deal ID
rep ID
keyword/topic
date range
Search calls matching the topic or keyword.
Retrieve summaries, transcripts, and snippets where relevant.
Identify recurring objections and how they were handled.
Assess whether objections were resolved or remain open.
Summarise patterns and examples.
Objection analysis with themes, frequency, examples, and suggested follow-up actions
Build onboarding playlist
Workflow...
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Objective Enable customers to connect Jiminny data to external AI tools (Claude, OpenAI, Gemini) so it can be used as part of their broader knowledge base and workflows. Position Jiminny as a data layer for AI-driven revenue workflows, not just a standalone product. 👤 Target user Revenue teams using AI tools (Sales, CS, RevOps) Companies already experimenting with Claude / OpenAI Mid-market & Enterprise customers with multiple data sources (CRM, docs, CI tools, Support tools etc) 🤕 Pain point or problem Jiminny data is locked in the platform AI tools lack access to high-value conversation context Customers must manually export/copy transcripts No easy way to combine calls with CRM + docs + other info - using the Jiminny API is not suitable for non technical sales people Peer pressure as almost all competitors have this 💥 Impact and benefits For customers Better AI outputs using real customer conversations Ability to build automated workflows across tools For Jiminny Increased product stickiness (embedded in workflows) Competitive parity with Gong / Avoma etc. 💡 Solution ideas Build an AI Knowledge Connector (MCP-based) that: Exposes Jiminny data (calls, transcripts, metadata) to AI tools Provides structured insights (summaries, action items, scoring etc.) Supports deal-level context Allows integration into customer-owned AI stacks (Claude + Zapier, etc.) Success metrics List the key goals and how you will measure success. Include both qualitative and quantitative metrics (e.g., user adoption, retention rate, revenue targets). Goal Metric Increase stickiness by ensuring Jiminny is embedded in the customer’s workflows % of customers connecting external AI tools Number of MCP/API calls per customer - and which ones are being used the most Decrease the manual copying of transcripts decrease by X % User interaction and design Simple setup flow: Generate API key / connect MCP Clear instructions for Claude / Zapier setup Provide: Example prompts for Claude Pre-built workflow templates for Zapier Clear documentation - with use cases 👉 Focus: usable by non-technical users Detailed Requirements List the functional and non-functional requirements. Prioritize them (e.g., High, Medium, Low) and add notes for clarification. Requirement Importance Notes Allow customers to connect Jiminny to their AI tools (e.g. Claude, OpenAI) HIGH Provide MCP endpoint so customers can easily integrate Jiminny into their AI stack Allow customers to access call data through AI tools HIGH Expose Jiminny data: list calls (filter by date, user, account, deal) get call get transcript (speaker-separated) get call metadata search calls (keyword + semantic) Support filtering by: account / contact/ lead / deal jiminny user date range Allow customers to search and query calls using AI tools HIGH Support keyword and semantic search across conversations Provide structured insights so customers can generate better outputs HIGH For each call, expose: Summary Action items Key points Activity type Notes Call Score CRM information Allow customers to understand deal status across multiple calls/emails HIGH For each deal expose: calls/meetings/emails Identified risks contacts related to the deal with their job title linked account details all CRM field information that we have in DI + fields used for CRM filling example - get_deal_summary request - { \"tool\": \"get_deal_summary\", \"arguments\": { \"deal_name\": \"ACME\" } } responce: { \"deal_name\": \"ACME\", \"stage\": \"Negotiation\", \"recent_activity\": [ \"Demo call on 2026-04-01\", \"Pricing discussion on 2026-04-03\" ], \"risks\": [ \"Pricing concerns\", \"Security review pending\" ], \"next_steps\": [ \"Send follow-up to VP Sales\", \"Share security documentation\" ] } Ensure the AI can easily understand the schema of the data coming from Jiminny HIGH Models perform much better when tools have: clear names rich descriptions predictable schemas Provide clear, actionable error states for customers when MCP connections fail HIGH Error messages should guide agents toward solutions with specific suggestions and next steps. Expired or revoked key — “Error: Authentication failed. The API key used to access Jiminny has been revoked or has expired. Please ask your Jiminny admin to generate a new API key in Settings > Organization > General and reconnect the MCP server.” Rate limit hit — “Error: Rate limit exceeded. Too many requests have been made to the Jiminny MCP server in a short period. Please wait 60 seconds before retrying.” Permissions mismatch — if a user tries to access data outside their team visibility settings - “Error: Access denied. The requested call (call_id: [X]) is outside your team's visibility settings in Jiminny. Only calls within your permitted scope are accessible.” Trying to access private meeting - “Error: Access denied. This meeting has been marked as private by the host and cannot be accessed through the MCP connector. Try requesting a different call or ask the meeting host to change the visibility settings in Jiminny.” Downgraded/Capture account — if a customer's plan drops below Scale tier or the Customer is on Capture in the first place - “Error: MCP access unavailable. The Jiminny MCP connector is available on the Scale plan and above. Your account does not currently have an active Scale subscription.” Jiminny-side outage — “Error:Jiminny is temporarily unavailable (status 503). This is not a data or permissions issue — please retry in a few minutes.” No data found - “Error:No calls found matching your criteria. Try adjusting your filters — for example, widening the date range, removing the account filter, or checking the rep name is spelled correctly in Jiminny.” Allow customers to securely control who and what data is accessible externally HIGH Ensure MCP only exposes data user has access to - based on team visibility settings. This means that if a user is not allow to access calls/deals in Jiminny UI then they shouldn’t be able to access those through the MCP as well. Private meetings shouldn’t be exposed via MCP HIGH When a meetings is set to Private then the information about it shouldn’t be exposed through the MCP. Ensure Jiminny data can be combined with other sources (e.g. CRM, docs) in AI workflows HIGH Ensure data is structured to be easily combined with: CRM (accounts, deals) external docs Use consistent identifiers: account IDs deal IDs MCP is available only for Scale tier and above HIGH Customers who are on Capture tier should be able to access any of their data through MCP. This should also cover the scenario when a customer has been on Scale but then downgrades to Capture - their MCP access should stop working. Provide visibility into how external AI tools access Jiminny data HIGH Audit logs: what data was accessed by which external system when identity - who made the request specific queries/filters used failed access attempts (especially cross-visibility-boundary attempts) Admins should be able to access the logs from the org settings.We can start with a csv export before building a specific page for it. example from Atlassian - Provide customers with example prompts to get started quickly HIGH MCP prompts are explicitly defined as prompt templates that clients can discover and call with arguments. See examples in table below. Expose Jiminny as a Connector in Claude medium Competitors like Fathom are listed as Connectors in Claude. This will make it easier for customers to find us and to connect Jiminny Provide customers with example workflows to get started quickly medium A workflow is usually multiple steps, maybe multiple tools, still focused on one outcome. See examples in table below. Allow customers to use predefined Jiminny skills for common workflows medium Anthropic describes Skills as folders that include instructions, scripts, and resources that Claude can load when relevant, and as a way to teach Claude repeatable workflows, preferences, and domain expertise once instead of re-explaining them every time. Skills - a reusable package of behavior that can include prompts, instructions, resources, and sometimes scripts/tools for a broader job. Claude skills - https://resources.anthropic.com/hubfs/The-Complete-Guide-to-Building-Skill-for-Claude.pdf?hsLang=en&utm_source=chatgpt.com See examples in table below. Jiminny UI widget for OpenAI medium The reason to have this is to make certain Jiminny use cases much easier than pure chat. Instead of ChatGPT only replying with text like “Here are the last 5 ACME calls,” it could also show a visual Jiminny card or mini-app inside the chat. That widget could list calls, show a deal summary, let the user filter by rep/date/account, open a transcript section, or save a snippet—while the conversation continues in normal chat alongside it. For Jiminny, the best widget use cases are the ones where users need to browse or compare rather than ask one-off questions. A strong example is deal review: the user asks ChatGPT, “What is the status of the ACME deal?” ChatGPT calls your Jiminny MCP tools, and the widget shows a compact deal view with recent calls, risks, next steps, stakeholders, and links to transcripts/snippets. The chat can still summarize the answer in words, but the widget gives a clearer, scannable interface. Another good Jiminny widget use case is call search and exploration. A text answer can say “I found 12 calls mentioning pricing objections,” but a widget could show a sortable list with date, rep, account, score, and objection count, then let the user click into one call to see the exact excerpt or jump to a transcript section. Allow customers to run long-running analyses asynchronously and retrieve progress/results low Some requests/questions require analysis of Hugh volumes of data. For those, it may be better to: start the job let it run in the background return a status like “in progress” let the client come back for the result later For example - User asks in Claude: “Analyse all calls from this quarter and tell me the top 5 objections by segment.” That might require: searching lots of calls pulling many summaries/transcripts aggregating results Instead of making Claude wait 45+ seconds, Jiminny could: create an analysis job return: job_id = 123, status = running We need this in order to support: large-scale analysis multi-call aggregation across lots of data playlist generation across many calls heavy recap/report generation Creating a snippet through the MCP low Create a shareable snippet from a call recording by specifying a time range. Useful for highlighting key moments — objection handling, pricing discussions, competitive mentions — and sharing them with your team. example request: { \"tool\": \"create_snippet\", \"arguments\": { \"call_id\": \"call_123\", \"start_time\": \"00:18:24\", \"end_time\": \"00:19:10\", \"title\": \"Pricing objection\" } } example response: { \"snippet_id\": \"snip_987\", \"title\": \"Pricing objection\", \"share_url\": \"https://app.jiminny.com/snippets/snip_987\" } Ability to add recordings or snippets to a playlist low Allow customers to create libraries of calls automatically. They can use those for onboarding or other purposes Allow AI tools to read reusable Jiminny resources low fathom Resources are useful for data that should be read consistently rather than recomputed every time. In Jiminny terms, that could be: current deal snapshot account summary weekly rep recap approved talk tracks / objection handling guidance curated playlists or snippet libraries This is useful because an AI can consume these directly as context, instead of repeatedly stitching together many tool calls. Ability to write coaching notes in Jiminny through MCP low What we want to do for prompts/worflows and skills Capability Type User value / job to be done Example Jiminny use case Inputs Steps performed Output Draft follow-up email Prompt Help reps quickly create tailored follow-ups after calls Use the latest customer call to draft an email with recap and next steps Call ID optional tone optional recipient type Retrieve call summary and action items from Jiminny. Pull key points, commitments, and next steps. Apply the chosen tone and structure. Draft the email in a consistent format. Customer-ready follow-up email draft Summarise call Prompt Help users quickly extract the most important points from a conversation Generate a concise summary of one call for internal or external use Call ID optional summary style optional audience Retrieve transcript, metadata, and structured insights. Identify key topics, decisions, risks, and next steps. Format output for the chosen audience. Short or structured call summary with actions and risks Generate deal recap Prompt Help reps and managers get a fast overview of a deal Summarise the current state of a deal based on recent calls and linked CRM context Deal ID or account name optional date range Retrieve calls and meetings linked to the deal. Pull deal metadata and CRM-linked context. Identify recent changes, blockers, risks, and next steps. Summarise into a concise recap. Deal recap with status, blockers, risks, and recommended next steps Prepare weekly recap Prompt Help managers or reps review what changed over a time period Weekly recap of calls, themes, and actions for one rep, team, or account Rep ID team ID or account ID time period Retrieve relevant calls and summaries for the selected time period. Aggregate themes, action items, and changes. Highlight notable risks, opportunities, and follow-ups. Weekly recap with top themes, risks, opportunities, and actions Prepare deal review Workflow Help reps and managers review deal status using multiple sources of context Review a deal before pipeline review or forecast meeting Deal ID optional date range Retrieve all recent calls, emails, and meetings tied to the deal. Pull structured call summaries, score, action items, and key points. Pull linked CRM context such as stage, contacts, and account details. Aggregate open risks, unresolved objections, stakeholder gaps, and next steps. Format into a review-ready structure. Deal review document with current status, risks, stakeholders, blockers, and next steps Weekly team recap Workflow Help managers monitor activity and risk across a group of reps or accounts End-of-week team summary for sales leadership Team ID date range Retrieve calls and structured insights across the team. Group by rep, account, or deal. Identify recurring themes, major risks, strong calls, and missed follow-ups. Highlight calls or deals that need attention. Team-level recap with patterns, key risks, notable wins, and action areas Objection analysis across calls Workflow Help teams identify patterns across multiple conversations Analyse pricing or competitor objections across recent calls Account ID deal ID rep ID keyword/topic date range Search calls matching the topic or keyword. Retrieve summaries, transcripts, and snippets where relevant. Identify recurring objections and how they were handled. Assess whether objections were resolved or remain open. Summarise patterns and examples. Objection analysis with themes, frequency, examples, and suggested follow-up actions Build onboarding playlist Workflow Help enablement teams curate useful learning content faster Build a playlist of strong discovery, demo, or pricing calls for new hires Topic call type rep/team filter optional time period Search for calls matching the selected criteria. Rank or filter calls based on score, topics, or key moments. Identify useful snippets or full recordings. Add selected calls/snippets into a playlist structure. Generate short descriptions for each item. Curated onboarding playlist with selected calls/snippets and descriptions Deal Inspection Skill Skill Give users a consistent, opinionated way to assess a deal Claude reviews a deal using a repeatable Jiminny methodology Deal ID or account name optional review scope Determine whether the request is suitable for a deal inspection. Retrieve relevant calls, summaries, CRM context, stakeholders, and risks. Apply a standard Jiminny review framework to assess deal health. Look for missing next steps, unresolved objections, stakeholder gaps, and warning signs. Present findings in a consistent structure with recommended actions. Structured deal inspection with health assessment, red flags, and recommendations Manager Coaching Skill Skill Help managers review calls consistently and identify coaching moments Analyse a rep’s call and surface strengths, gaps, and examples for coaching Call ID optional rep ID optional coaching focus Retrieve transcript, score, summary, and key moments from the call. Evaluate the conversation against a coaching framework. Identify what went well and where the rep could improve. Suggest moments to clip as snippets. Recommend coaching actions or playlist additions. Coaching review with strengths, gaps, snippet suggestions, and recommended coaching actions CSM / QBR Prep Skill Skill Help CS or AM teams prepare structured customer reviews from conversations Generate an account review or QBR-style summary from recent customer interactions Account ID, optional time period Retrieve all recent calls, emails, and account-linked context. Aggregate themes, requests, blockers, sentiment shifts, and opportunities. Apply a repeatable account review structure. Summarise outcomes, open issues, and suggested next steps. Structured QBR/account review summary with themes, risks, opportunities, and actions Snippet Builder Skill Skill Help users consistently capture and label useful moments from calls Identify useful moments in a call and convert them into reusable snippets Call ID, optional focus area such as pricing, objection, competitor, discovery Retrieve transcript, recording timeline, and call insights. Detect moments matching the requested focus area. Propose snippet start/end times and titles. Tag snippets by type or theme. Optionally save them or add them to a playlist. One or more proposed or saved snippets with title, timing, and tags 💡 Technical details Auth model needs specifying. Are API keys scoped per user, per team, or per Jiminny instance? If a key is generated by an admin, does it inherit their visibility level, or provide org-wide? Are permissions evaluated at query time or frozen at key creation? Needs to be query-time, otherwise permission changes won't propagate. Key lifecycle management is missing. No mention of rotation, expiry, or revocation. A departed employee's active key is a data leak. Need: revocation, optional expiry, alerts on stale keys, and consider whether keys should be tied to service accounts rather than personal users. Rate limiting should be HIGH. A compromised key or misconfigured automation could bulk-export an entire customer's call history. Need per-key rate limits and anomaly detection on unusual access patterns. Open Questions Track unresolved issues or decisions that need to be made. Update as answers become available. Question Answer Date Answered Competitor research Competitor MCP Availability Core Capabilities Advanced Capabilities Positioning Key Strength Key Weakness Gong ✅ Mature MCP List/search calls Get transcripts get Call metadata Deal intelligence Scorecards, analytics CRM context Enterprise data layer Deep data + ecosystem integrations Limited opinionated AI workflows Avoma ✅ Mature MCP list_meetings get_meeting get_transcript key topics Deal fields/Deal level analysis Coaching/Scoring CRM context pushing insights into Notion / Confluence AI-ready meeting intelligence Strongest “outputs” layer Mostly pull-based interactions Fathom ✅ MCP list/search meetings get transcript get summary/action items Team/org context Webhooks (event-based triggers) get_weekly_recap aggregated action items across meetings creating webhooks directly from the MCP server Lightweight meeting data access Includes summaries + actions Limited analytics depth Grain ✅ Basic MCP get meetings download transcripts Notes Deals Scorecards Data access utility Simple + accessible Low sophistication, sometimes browser-based Outreach ⚠️ MCP (workflow-focused) Search sequences Emails Meetings (Kaia) account / prospect / opportunity lookups Workflow automation Multi-system orchestration Revenue workflow engine End-to-end GTM workflows Less depth in conversation data Attention ⚠️ Emerging MCP Meeting data Transcripts CRM-linked context AI insights Sales assistant workflows create snippets AI sales assistant + CRM Strong CRM linkage Less focus on external knowledge layer Planhat - Related content Ask Jiminny Anything on Call level Galya Dimitrova Hubspot app Galya Dimitrova Product Vision & Strategy Galya Dimitrova Automated CRM Filling Simona Georgieva (Deactivated) Competitive analysis Galya Dimitrova AI agent ideas Steliyan Georgiev Comments James Graham 9 Apr A few areas around Security & Compliance that need more depth before this moves beyond draft: Auth model needs specifying. Are API keys scoped per user, per team, or per Jiminny instance? If a key is generated by an admin, does it inherit their visibility level, or provide org-wide? Are permissions evaluated at query time or frozen at key creation? Needs to be query-time, otherwise permission changes won't propagate. Team visibility enforcement should be its own HIGH requirement. The current note under access control (\"ensure MCP only exposes data user has access to\") is doing too much work as a single line. Every MCP tool response (especially search_calls and deal-level aggregations) must be filtered through the same visibility engine as the UI. Semantic search is the riskiest here; it could surface results across team boundaries if not properly scoped. No data minimisation or scoping controls. We're exposing transcripts, CRM fields, contact details with job titles, deal context - significant PII and commercial data leaving the platform. Can customers configure which data types are exposed? Can transcripts be PII-stripped before they leave Jiminny? Given we position GDPR consent as a differentiator, we should be thinking about this. GDPR downstream processing is unaddressed. Piping transcripts to OpenAI/Gemini introduces new data processors. Customers need to acknowledge responsibility for downstream processing during setup. We should also consider whether call participants' recording consent covers onward sharing to third-party AI - it almost certainly doesn't by default. This is one for me to pick up. Key lifecycle management is missing. No mention of rotation, expiry, or revocation. A departed employee's active key is a data leak. Need: revocation, optional expiry, alerts on stale keys, and consider whether keys should be tied to service accounts rather than personal users. Rate limiting should be HIGH. A compromised key or misconfigured automation could bulk-export an entire customer's call history. Need per-key rate limits and anomaly detection on unusual access patterns. Audit logs should go deeper. Current spec (what data, which system, when) is a start. Add: identity behind the key, specific queries/filters used, and failed access attempts (especially cross-visibility-boundary attempts). Enterprise compliance teams will expect this. Downgrade handling. Doc says Scale tier and above, but doesn't say what happens on downgrade. Keys should auto-deactivate. Happy to help draft a dedicated Security & Compliance section if useful. Galya Dimitrova 15 Apr Thanks for the input @James Graham . I made the product related changes in the table and for the rest I left them as a note in the Technical section for the team to look at when they start looking at this. I wonder about your points related to GDPR. Currently multiple customers are using the Customer API/zapier to feed this data to AI and BI tools. They are also manually exporting transcripts and other information from the platform and feeding it to AI tools. I don’t get how MCP is so much different that all of these and why it will introduce new data processors (which are already being utilised) and would require any changes to the consent provided by participants.","depth":21,"bounds":{"left":0.41805187,"top":0.19313647,"width":0.051861703,"height":0.11173184},"help_text":"","role_description":"heading","subrole":"AXUnknown"},{"role":"AXStaticText","text":"You said","depth":23,"bounds":{"left":0.36053857,"top":0.19553073,"width":0.019946808,"height":0.016360734},"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"Jiminny MCP Connector","depth":23,"bounds":{"left":0.41805187,"top":0.1963288,"width":0.03125,"height":0.038707104},"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"Epic","depth":23,"bounds":{"left":0.41805187,"top":0.30806065,"width":0.010305851,"height":0.016360734},"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"Link to Epik in Jira","depth":23,"bounds":{"left":0.41805187,"top":0.33040702,"width":0.043218084,"height":0.016360734},"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"Document status","depth":23,"bounds":{"left":0.41805187,"top":0.3527534,"width":0.04105718,"height":0.016360734},"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"DRAFT","depth":23,"bounds":{"left":0.41805187,"top":0.37509975,"width":0.016289894,"height":0.016360734},"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"Objective","depth":23,"bounds":{"left":0.41805187,"top":0.39744613,"width":0.024268618,"height":0.016360734},"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"Enable customers to connect Jiminny data to external AI tools (Claude, OpenAI, Gemini) so it can be used as part of their broader knowledge base and workflows.","depth":23,"bounds":{"left":0.41805187,"top":0.4197925,"width":0.051529255,"height":0.17278531},"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"Position Jiminny as a data layer for AI-driven revenue workflows, not just a standalone product.","depth":23,"bounds":{"left":0.41805187,"top":0.59856343,"width":0.049700797,"height":0.10574621},"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"👤 Target user","depth":23,"bounds":{"left":0.41805187,"top":0.75458896,"width":0.033909574,"height":0.016759777},"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"Revenue teams using AI tools (Sales, CS, RevOps)","depth":23,"bounds":{"left":0.41805187,"top":0.7773344,"width":0.051030584,"height":0.061053474},"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"Companies already experimenting with Claude / OpenAI","depth":23,"bounds":{"left":0.41805187,"top":0.8443735,"width":0.04637633,"height":0.061053474},"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"Mid-market & Enterprise customers with multiple data sources (CRM, docs, CI tools, Support tools etc)","depth":23,"bounds":{"left":0.41805187,"top":0.9114126,"width":0.051363032,"height":0.0885874},"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"🤕 Pain point or problem","depth":23,"bounds":{"left":0.41805187,"top":1.0,"width":0.03706782,"height":-0.0897845},"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"Jiminny data is locked in the platform","depth":23,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"AI tools lack access to high-value conversation context","depth":23,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"Customers must manually export/copy transcripts","depth":23,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"No easy way to combine calls with CRM + docs + other info - 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This is not a data or permissions issue — please retry in a few minutes.”","depth":23,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"No data found - “Error:No calls found matching your criteria. Try adjusting your filters — for example, widening the date range, removing the account filter, or checking the rep name is spelled correctly in Jiminny.”","depth":23,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"Allow customers to securely control who and what data is accessible externally","depth":23,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"HIGH","depth":23,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"Ensure MCP only exposes data user has access to - based on team visibility settings. This means that if a user is not allow to access calls/deals in Jiminny UI then they shouldn’t be able to access those through the MCP as well.","depth":23,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"Private meetings shouldn’t be exposed via MCP","depth":23,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"HIGH","depth":23,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"When a meetings is set to Private then the information about it shouldn’t be exposed through the MCP.","depth":23,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"Ensure Jiminny data can be combined with other sources (e.g. CRM, docs) in AI workflows","depth":23,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"HIGH","depth":23,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"Ensure data is structured to be easily combined with:","depth":23,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"CRM (accounts, deals)","depth":23,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"external docs","depth":23,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"Use consistent identifiers:","depth":23,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"account IDs","depth":23,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"deal IDs","depth":23,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"MCP is available only for Scale tier and above","depth":23,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"HIGH","depth":23,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"Customers who are on Capture tier should be able to access any of their data through MCP.","depth":23,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"This should also cover the scenario when a customer has been on Scale but then downgrades to Capture - their MCP access should stop working.","depth":23,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"Provide visibility into how external AI tools access Jiminny data","depth":23,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"HIGH","depth":23,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"Audit logs:","depth":23,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"what data was accessed by which external system when","depth":23,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"identity - who made the request","depth":23,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"specific queries/filters used","depth":23,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"failed access attempts (especially cross-visibility-boundary attempts)","depth":23,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"Admins should be able to access the logs from the org settings.We can start with a csv export before building a specific page for it.","depth":23,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"example from Atlassian -","depth":23,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"Provide customers with example prompts to get started quickly","depth":23,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"HIGH","depth":23,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"MCP prompts are explicitly defined as prompt templates that clients can discover and call with arguments.","depth":23,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"See examples in table below.","depth":23,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"Expose Jiminny as a Connector in Claude","depth":23,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"medium","depth":23,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"Competitors like Fathom are listed as Connectors in Claude. This will make it easier for customers to find us and to connect Jiminny","depth":23,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"Provide customers with example workflows to get started quickly","depth":23,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"medium","depth":23,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"A workflow is usually multiple steps, maybe multiple tools, still focused on one outcome.","depth":23,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"See examples in table below.","depth":23,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"Allow customers to use predefined Jiminny skills for common workflows","depth":23,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"medium","depth":23,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"Anthropic describes Skills as folders that include instructions, scripts, and resources that Claude can load when relevant, and as a way to teach Claude repeatable workflows, preferences, and domain expertise once instead of re-explaining them every time. Skills - a reusable package of behavior that can include prompts, instructions, resources, and sometimes scripts/tools for a broader job.","depth":23,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"Claude skills - https://resources.anthropic.com/hubfs/The-Complete-Guide-to-Building-Skill-for-Claude.pdf?hsLang=en&utm_source=chatgpt.com","depth":23,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"See examples in table below.","depth":23,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"Jiminny UI widget for OpenAI","depth":23,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"medium","depth":23,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"The reason to have this is to make certain Jiminny use cases much easier than pure chat.","depth":23,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"Instead of ChatGPT only replying with text like “Here are the last 5 ACME calls,” it could also show a visual Jiminny card or mini-app inside the chat. That widget could list calls, show a deal summary, let the user filter by rep/date/account, open a transcript section, or save a snippet—while the conversation continues in normal chat alongside it.","depth":23,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"For Jiminny, the best widget use cases are the ones where users need to browse or compare rather than ask one-off questions. A strong example is deal review: the user asks ChatGPT, “What is the status of the ACME deal?” ChatGPT calls your Jiminny MCP tools, and the widget shows a compact deal view with recent calls, risks, next steps, stakeholders, and links to transcripts/snippets. The chat can still summarize the answer in words, but the widget gives a clearer, scannable interface.","depth":23,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"Another good Jiminny widget use case is call search and exploration. A text answer can say “I found 12 calls mentioning pricing objections,” but a widget could show a sortable list with date, rep, account, score, and objection count, then let the user click into one call to see the exact excerpt or jump to a transcript section.","depth":23,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"Allow customers to run long-running analyses asynchronously and retrieve progress/results","depth":23,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"low","depth":23,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"Some requests/questions require analysis of Hugh volumes of data. For those, it may be better to:","depth":23,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"start the job","depth":23,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"let it run in the background","depth":23,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"return a status like “in progress”","depth":23,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"let the client come back for the result later","depth":23,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"For example - User asks in Claude:","depth":23,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"“Analyse all calls from this quarter and tell me the top 5 objections by segment.”","depth":23,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"That might require:","depth":23,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"searching lots of calls","depth":23,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"pulling many summaries/transcripts","depth":23,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"aggregating results","depth":23,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"Instead of making Claude wait 45+ seconds, Jiminny could:","depth":23,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"create an analysis job","depth":23,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"return: job_id = 123, status = running","depth":23,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"We need this in order to support:","depth":23,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"large-scale analysis","depth":23,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"multi-call aggregation across lots of data","depth":23,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"playlist generation across many calls","depth":23,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"heavy recap/report generation","depth":23,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"Creating a snippet through the MCP","depth":23,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"low","depth":23,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"Create a shareable snippet from a call recording by specifying a time range. Useful for highlighting key moments — objection handling, pricing discussions, competitive mentions — and sharing them with your team.","depth":23,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"example request:","depth":23,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"{","depth":23,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"\"tool\": \"create_snippet\",","depth":23,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"\"arguments\": {","depth":23,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"\"call_id\": \"call_123\",","depth":23,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"\"start_time\": \"00:18:24\",","depth":23,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"\"end_time\": \"00:19:10\",","depth":23,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"\"title\": \"Pricing objection\"","depth":23,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"}","depth":23,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"}","depth":23,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"example response:","depth":23,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"{","depth":23,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"\"snippet_id\": \"snip_987\",","depth":23,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"\"title\": \"Pricing objection\",","depth":23,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"\"share_url\": \"https://app.jiminny.com/snippets/snip_987\"","depth":23,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"}","depth":23,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"Ability to add recordings or snippets to a playlist","depth":23,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"low","depth":23,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"Allow customers to create libraries of calls automatically. They can use those for onboarding or other purposes","depth":23,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"Allow AI tools to read reusable Jiminny resources","depth":23,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"low","depth":23,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"fathom","depth":23,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"Resources are useful for data that should be read consistently rather than recomputed every time. In Jiminny terms, that could be:","depth":23,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"current deal snapshot","depth":23,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"account summary","depth":23,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"weekly rep recap","depth":23,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"approved talk tracks / objection handling guidance","depth":23,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"curated playlists or snippet libraries","depth":23,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"This is useful because an AI can consume these directly as context, instead of repeatedly stitching together many tool calls.","depth":23,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"Ability to write coaching notes in Jiminny through MCP","depth":23,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"low","depth":23,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"What we want to do for prompts/worflows and skills","depth":23,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"Capability","depth":23,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"Type","depth":23,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"User value / job to be done","depth":23,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"Example Jiminny use 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ID","depth":23,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"date range","depth":23,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"Retrieve calls and structured insights across the team.","depth":23,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"Group by rep, account, or deal.","depth":23,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"Identify recurring themes, major risks, strong calls, and missed follow-ups.","depth":23,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"Highlight calls or deals that need attention.","depth":23,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"Team-level recap with patterns, key risks, notable wins, and action areas","depth":23,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"Objection analysis across calls","depth":23,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"Workflow","depth":23,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"Help teams identify patterns across multiple conversations","depth":23,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"Analyse pricing or competitor objections across recent calls","depth":23,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"Account ID","depth":23,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"deal ID","depth":23,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"rep ID","depth":23,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"keyword/topic","depth":23,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"date range","depth":23,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"Search calls matching the topic or keyword.","depth":23,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"Retrieve summaries, transcripts, and snippets where relevant.","depth":23,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"Identify recurring objections and how they were handled.","depth":23,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"Assess whether objections were resolved or remain open.","depth":23,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"Summarise patterns and examples.","depth":23,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"Objection analysis with themes, frequency, examples, and suggested follow-up actions","depth":23,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"Build onboarding playlist","depth":23,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"Workflow","depth":23,"help_text":"","role_description":"text","subrole":"AXUnknown"}]...
|
4447310813642831864
|
7484418893791515225
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visual_change
|
accessibility
|
NULL
|
Platform Sprint 2 Q2 - Platform Team - Scrum Board Platform Sprint 2 Q2 - Platform Team - Scrum Board - Jira
SevenShores\Hubspot\Exceptions\BadRequest: Client error: `POST [URL_WITH_CREDENTIALS] Graham . I made the product related changes in the table and for the rest I left them as a note in the Technical section for the team to look at when they start looking at this. I wonder about your points related to GDPR. Currently multiple customers are using the Customer API/zapier to feed this data to AI and BI tools. They are also manually exporting transcripts and other information from the platform and feeding it to AI tools. I don’t get how MCP is so much different that all of these and why it will introduce new data processors (which are already being utilised) and would require any changes to the consent provided by participants.
You said
Jiminny MCP Connector
Epic
Link to Epik in Jira
Document status
DRAFT
Objective
Enable customers to connect Jiminny data to external AI tools (Claude, OpenAI, Gemini) so it can be used as part of their broader knowledge base and workflows.
Position Jiminny as a data layer for AI-driven revenue workflows, not just a standalone product.
👤 Target user
Revenue teams using AI tools (Sales, CS, RevOps)
Companies already experimenting with Claude / OpenAI
Mid-market & Enterprise customers with multiple data sources (CRM, docs, CI tools, Support tools etc)
🤕 Pain point or problem
Jiminny data is locked in the platform
AI tools lack access to high-value conversation context
Customers must manually export/copy transcripts
No easy way to combine calls with CRM + docs + other info - using the Jiminny API is not suitable for non technical sales people
Peer pressure as almost all competitors have this
💥 Impact and benefits
For customers
Better AI outputs using real customer conversations
Ability to build automated workflows across tools
For Jiminny
Increased product stickiness (embedded in workflows)
Competitive parity with Gong / Avoma etc.
💡 Solution ideas
Build an AI Knowledge Connector (MCP-based) that:
Exposes Jiminny data (calls, transcripts, metadata) to AI tools
Provides structured insights (summaries, action items, scoring etc.)
Supports deal-level context
Allows integration into customer-owned AI stacks (Claude + Zapier, etc.)
Success metrics
List the key goals and how you will measure success. Include both qualitative and quantitative metrics (e.g., user adoption, retention rate, revenue targets).
Goal
Metric
Increase stickiness by ensuring Jiminny is embedded in the customer’s workflows
% of customers connecting external AI tools
Number of MCP/API calls per customer - and which ones are being used the most
Decrease the manual copying of transcripts
decrease by X %
User interaction and design
Simple setup flow:
Generate API key / connect MCP
Clear instructions for Claude / Zapier setup
Provide:
Example prompts for Claude
Pre-built workflow templates for Zapier
Clear documentation - with use cases
👉 Focus: usable by non-technical users
Detailed Requirements
List the functional and non-functional requirements. Prioritize them (e.g., High, Medium, Low) and add notes for clarification.
Requirement
Importance
Notes
Allow customers to connect Jiminny to their AI tools (e.g. Claude, OpenAI)
HIGH
Provide MCP endpoint so customers can easily integrate Jiminny into their AI stack
Allow customers to access call data through AI tools
HIGH
Expose Jiminny data:
list calls (filter by date, user, account, deal)
get call
get transcript (speaker-separated)
get call metadata
search calls (keyword + semantic)
Support filtering by:
account / contact/ lead / deal
jiminny user
date range
Allow customers to search and query calls using AI tools
HIGH
Support keyword and semantic search across conversations
Provide structured insights so customers can generate better outputs
HIGH
For each call, expose:
Summary
Action items
Key points
Activity type
Notes
Call Score
CRM information
Allow customers to understand deal status across multiple calls/emails
HIGH
For each deal expose:
calls/meetings/emails
Identified risks
contacts related to the deal with their job title
linked account details
all CRM field information that we have in DI + fields used for CRM filling
example - get_deal_summary
request -
{
"tool": "get_deal_summary",
"arguments": {
"deal_name": "ACME"
}
}
responce:
{
"deal_name": "ACME",
"stage": "Negotiation",
"recent_activity": [
"Demo call on 2026-04-01",
"Pricing discussion on 2026-04-03"
],
"risks": [
"Pricing concerns",
"Security review pending"
], "next_steps": [
"Send follow-up to VP Sales",
"Share security documentation"
]
}
Ensure the AI can easily understand the schema of the data coming from Jiminny
HIGH
Models perform much better when tools have:
clear names
rich descriptions
predictable schemas
Provide clear, actionable error states for customers when MCP connections fail
HIGH
Error messages should guide agents toward solutions with specific suggestions and next steps.
Expired or revoked key — “Error: Authentication failed. The API key used to access Jiminny has been revoked or has expired. Please ask your Jiminny admin to generate a new API key in Settings > Organization > General and reconnect the MCP server.”
Rate limit hit — “Error: Rate limit exceeded. Too many requests have been made to the Jiminny MCP server in a short period. Please wait 60 seconds before retrying.”
Permissions mismatch — if a user tries to access data outside their team visibility settings - “Error: Access denied. The requested call (call_id: [X]) is outside your team's visibility settings in Jiminny. Only calls within your permitted scope are accessible.”
Trying to access private meeting - “Error: Access denied. This meeting has been marked as private by the host and cannot be accessed through the MCP connector. Try requesting a different call or ask the meeting host to change the visibility settings in Jiminny.”
Downgraded/Capture account — if a customer's plan drops below Scale tier or the Customer is on Capture in the first place - “Error: MCP access unavailable. The Jiminny MCP connector is available on the Scale plan and above. Your account does not currently have an active Scale subscription.”
Jiminny-side outage — “Error:Jiminny is temporarily unavailable (status 503). This is not a data or permissions issue — please retry in a few minutes.”
No data found - “Error:No calls found matching your criteria. Try adjusting your filters — for example, widening the date range, removing the account filter, or checking the rep name is spelled correctly in Jiminny.”
Allow customers to securely control who and what data is accessible externally
HIGH
Ensure MCP only exposes data user has access to - based on team visibility settings. This means that if a user is not allow to access calls/deals in Jiminny UI then they shouldn’t be able to access those through the MCP as well.
Private meetings shouldn’t be exposed via MCP
HIGH
When a meetings is set to Private then the information about it shouldn’t be exposed through the MCP.
Ensure Jiminny data can be combined with other sources (e.g. CRM, docs) in AI workflows
HIGH
Ensure data is structured to be easily combined with:
CRM (accounts, deals)
external docs
Use consistent identifiers:
account IDs
deal IDs
MCP is available only for Scale tier and above
HIGH
Customers who are on Capture tier should be able to access any of their data through MCP.
This should also cover the scenario when a customer has been on Scale but then downgrades to Capture - their MCP access should stop working.
Provide visibility into how external AI tools access Jiminny data
HIGH
Audit logs:
what data was accessed by which external system when
identity - who made the request
specific queries/filters used
failed access attempts (especially cross-visibility-boundary attempts)
Admins should be able to access the logs from the org settings.We can start with a csv export before building a specific page for it.
example from Atlassian -
Provide customers with example prompts to get started quickly
HIGH
MCP prompts are explicitly defined as prompt templates that clients can discover and call with arguments.
See examples in table below.
Expose Jiminny as a Connector in Claude
medium
Competitors like Fathom are listed as Connectors in Claude. This will make it easier for customers to find us and to connect Jiminny
Provide customers with example workflows to get started quickly
medium
A workflow is usually multiple steps, maybe multiple tools, still focused on one outcome.
See examples in table below.
Allow customers to use predefined Jiminny skills for common workflows
medium
Anthropic describes Skills as folders that include instructions, scripts, and resources that Claude can load when relevant, and as a way to teach Claude repeatable workflows, preferences, and domain expertise once instead of re-explaining them every time. Skills - a reusable package of behavior that can include prompts, instructions, resources, and sometimes scripts/tools for a broader job.
Claude skills - https://resources.anthropic.com/hubfs/The-Complete-Guide-to-Building-Skill-for-Claude.pdf?hsLang=en&utm_source=chatgpt.com
See examples in table below.
Jiminny UI widget for OpenAI
medium
The reason to have this is to make certain Jiminny use cases much easier than pure chat.
Instead of ChatGPT only replying with text like “Here are the last 5 ACME calls,” it could also show a visual Jiminny card or mini-app inside the chat. That widget could list calls, show a deal summary, let the user filter by rep/date/account, open a transcript section, or save a snippet—while the conversation continues in normal chat alongside it.
For Jiminny, the best widget use cases are the ones where users need to browse or compare rather than ask one-off questions. A strong example is deal review: the user asks ChatGPT, “What is the status of the ACME deal?” ChatGPT calls your Jiminny MCP tools, and the widget shows a compact deal view with recent calls, risks, next steps, stakeholders, and links to transcripts/snippets. The chat can still summarize the answer in words, but the widget gives a clearer, scannable interface.
Another good Jiminny widget use case is call search and exploration. A text answer can say “I found 12 calls mentioning pricing objections,” but a widget could show a sortable list with date, rep, account, score, and objection count, then let the user click into one call to see the exact excerpt or jump to a transcript section.
Allow customers to run long-running analyses asynchronously and retrieve progress/results
low
Some requests/questions require analysis of Hugh volumes of data. For those, it may be better to:
start the job
let it run in the background
return a status like “in progress”
let the client come back for the result later
For example - User asks in Claude:
“Analyse all calls from this quarter and tell me the top 5 objections by segment.”
That might require:
searching lots of calls
pulling many summaries/transcripts
aggregating results
Instead of making Claude wait 45+ seconds, Jiminny could:
create an analysis job
return: job_id = 123, status = running
We need this in order to support:
large-scale analysis
multi-call aggregation across lots of data
playlist generation across many calls
heavy recap/report generation
Creating a snippet through the MCP
low
Create a shareable snippet from a call recording by specifying a time range. Useful for highlighting key moments — objection handling, pricing discussions, competitive mentions — and sharing them with your team.
example request:
{
"tool": "create_snippet",
"arguments": {
"call_id": "call_123",
"start_time": "00:18:24",
"end_time": "00:19:10",
"title": "Pricing objection"
}
}
example response:
{
"snippet_id": "snip_987",
"title": "Pricing objection",
"share_url": "https://app.jiminny.com/snippets/snip_987"
}
Ability to add recordings or snippets to a playlist
low
Allow customers to create libraries of calls automatically. They can use those for onboarding or other purposes
Allow AI tools to read reusable Jiminny resources
low
fathom
Resources are useful for data that should be read consistently rather than recomputed every time. In Jiminny terms, that could be:
current deal snapshot
account summary
weekly rep recap
approved talk tracks / objection handling guidance
curated playlists or snippet libraries
This is useful because an AI can consume these directly as context, instead of repeatedly stitching together many tool calls.
Ability to write coaching notes in Jiminny through MCP
low
What we want to do for prompts/worflows and skills
Capability
Type
User value / job to be done
Example Jiminny use case
Inputs
Steps performed
Output
Draft follow-up email
Prompt
Help reps quickly create tailored follow-ups after calls
Use the latest customer call to draft an email with recap and next steps
Call ID
optional tone
optional recipient type
Retrieve call summary and action items from Jiminny.
Pull key points, commitments, and next steps.
Apply the chosen tone and structure.
Draft the email in a consistent format.
Customer-ready follow-up email draft
Summarise call
Prompt
Help users quickly extract the most important points from a conversation
Generate a concise summary of one call for internal or external use
Call ID
optional summary style
optional audience
Retrieve transcript, metadata, and structured insights.
Identify key topics, decisions, risks, and next steps.
Format output for the chosen audience.
Short or structured call summary with actions and risks
Generate deal recap
Prompt
Help reps and managers get a fast overview of a deal
Summarise the current state of a deal based on recent calls and linked CRM context
Deal ID or account name
optional date range
Retrieve calls and meetings linked to the deal.
Pull deal metadata and CRM-linked context.
Identify recent changes, blockers, risks, and next steps.
Summarise into a concise recap.
Deal recap with status, blockers, risks, and recommended next steps
Prepare weekly recap
Prompt
Help managers or reps review what changed over a time period
Weekly recap of calls, themes, and actions for one rep, team, or account
Rep ID
team ID or account ID
time period
Retrieve relevant calls and summaries for the selected time period.
Aggregate themes, action items, and changes.
Highlight notable risks, opportunities, and follow-ups.
Weekly recap with top themes, risks, opportunities, and actions
Prepare deal review
Workflow
Help reps and managers review deal status using multiple sources of context
Review a deal before pipeline review or forecast meeting
Deal ID
optional date range
Retrieve all recent calls, emails, and meetings tied to the deal.
Pull structured call summaries, score, action items, and key points.
Pull linked CRM context such as stage, contacts, and account details.
Aggregate open risks, unresolved objections, stakeholder gaps, and next steps.
Format into a review-ready structure.
Deal review document with current status, risks, stakeholders, blockers, and next steps
Weekly team recap
Workflow
Help managers monitor activity and risk across a group of reps or accounts
End-of-week team summary for sales leadership
Team ID
date range
Retrieve calls and structured insights across the team.
Group by rep, account, or deal.
Identify recurring themes, major risks, strong calls, and missed follow-ups.
Highlight calls or deals that need attention.
Team-level recap with patterns, key risks, notable wins, and action areas
Objection analysis across calls
Workflow
Help teams identify patterns across multiple conversations
Analyse pricing or competitor objections across recent calls
Account ID
deal ID
rep ID
keyword/topic
date range
Search calls matching the topic or keyword.
Retrieve summaries, transcripts, and snippets where relevant.
Identify recurring objections and how they were handled.
Assess whether objections were resolved or remain open.
Summarise patterns and examples.
Objection analysis with themes, frequency, examples, and suggested follow-up actions
Build onboarding playlist
Workflow...
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1752
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7
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2026-04-22T15:11:33.666375+00:00
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/Users/lukas/.screenpipe/data/data/2026-04-22/1776 /Users/lukas/.screenpipe/data/data/2026-04-22/1776870693666_m1.jpg...
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Firefox
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Architecture overview - Model Context Protocol — W Architecture overview - Model Context Protocol — Work...
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True
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modelcontextprotocol.io/docs/learn/architecture
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monitor_1
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Platform Sprint 2 Q2 - Platform Team - Scrum Board Platform Sprint 2 Q2 - Platform Team - Scrum Board - Jira
SevenShores\Hubspot\Exceptions\BadRequest: Client error: `POST [URL_WITH_CREDENTIALS] Graham . I made the product related changes in the table and for the rest I left them as a note in the Technical section for the team to look at when they start looking at this. I wonder about your points related to GDPR. Currently multiple customers are using the Customer API/zapier to feed this data to AI and BI tools. They are also manually exporting transcripts and other information from the platform and feeding it to AI tools. I don’t get how MCP is so much different that all of these and why it will introduce new data processors (which are already being utilised) and would require any changes to the consent provided by participants.
You said
Jiminny MCP Connector
Epic
Link to Epik in Jira
Document status
DRAFT
Objective
Enable customers to connect Jiminny data to external AI tools (Claude, OpenAI, Gemini) so it can be used as part of their broader knowledge base and workflows.
Position Jiminny as a data layer for AI-driven revenue workflows, not just a standalone product.
👤 Target user
Revenue teams using AI tools (Sales, CS, RevOps)
Companies already experimenting with Claude / OpenAI
Mid-market & Enterprise customers with multiple data sources (CRM, docs, CI tools, Support tools etc)
🤕 Pain point or problem
Jiminny data is locked in the platform
AI tools lack access to high-value conversation context
Customers must manually export/copy transcripts
No easy way to combine calls with CRM + docs + other info - using the Jiminny API is not suitable for non technical sales people
Peer pressure as almost all competitors have this
💥 Impact and benefits
For customers
Better AI outputs using real customer conversations
Ability to build automated workflows across tools
For Jiminny
Increased product stickiness (embedded in workflows)
Competitive parity with Gong / Avoma etc.
💡 Solution ideas
Build an AI Knowledge Connector (MCP-based) that:
Exposes Jiminny data (calls, transcripts, metadata) to AI tools
Provides structured insights (summaries, action items, scoring etc.)
Supports deal-level context
Allows integration into customer-owned AI stacks (Claude + Zapier, etc.)
Success metrics
List the key goals and how you will measure success. Include both qualitative and quantitative metrics (e.g., user adoption, retention rate, revenue targets).
Goal
Metric
Increase stickiness by ensuring Jiminny is embedded in the customer’s workflows
% of customers connecting external AI tools
Number of MCP/API calls per customer - and which ones are being used the most
Decrease the manual copying of transcripts
decrease by X %
User interaction and design
Simple setup flow:
Generate API key / connect MCP
Clear instructions for Claude / Zapier setup
Provide:
Example prompts for Claude
Pre-built workflow templates for Zapier
Clear documentation - with use cases
👉 Focus: usable by non-technical users
Detailed Requirements
List the functional and non-functional requirements. Prioritize them (e.g., High, Medium, Low) and add notes for clarification.
Requirement
Importance
Notes
Allow customers to connect Jiminny to their AI tools (e.g. Claude, OpenAI)
HIGH
Provide MCP endpoint so customers can easily integrate Jiminny into their AI stack
Allow customers to access call data through AI tools
HIGH
Expose Jiminny data:
list calls (filter by date, user, account, deal)
get call
get transcript (speaker-separated)
get call metadata
search calls (keyword + semantic)
Support filtering by:
account / contact/ lead / deal
jiminny user
date range
Allow customers to search and query calls using AI tools
HIGH
Support keyword and semantic search across conversations
Provide structured insights so customers can generate better outputs
HIGH
For each call, expose:
Summary
Action items
Key points
Activity type
Notes
Call Score
CRM information
Allow customers to understand deal status across multiple calls/emails
HIGH
For each deal expose:
calls/meetings/emails
Identified risks
contacts related to the deal with their job title
linked account details
all CRM field information that we have in DI + fields used for CRM filling
example - get_deal_summary
request -
{
"tool": "get_deal_summary",
"arguments": {
"deal_name": "ACME"
}
}
responce:
{
"deal_name": "ACME",
"stage": "Negotiation",
"recent_activity": [
"Demo call on 2026-04-01",
"Pricing discussion on 2026-04-03"
],
"risks": [
"Pricing concerns",
"Security review pending"
], "next_steps": [
"Send follow-up to VP Sales",
"Share security documentation"
]
}
Ensure the AI can easily understand the schema of the data coming from Jiminny
HIGH
Models perform much better when tools have:
clear names
rich descriptions
predictable schemas
Provide clear, actionable error states for customers when MCP connections fail
HIGH
Error messages should guide agents toward solutions with specific suggestions and next steps.
Expired or revoked key — “Error: Authentication failed. The API key used to access Jiminny has been revoked or has expired. Please ask your Jiminny admin to generate a new API key in Settings > Organization > General and reconnect the MCP server.”
Rate limit hit — “Error: Rate limit exceeded. Too many requests have been made to the Jiminny MCP server in a short period. Please wait 60 seconds before retrying.”
Permissions mismatch — if a user tries to access data outside their team visibility settings - “Error: Access denied. The requested call (call_id: [X]) is outside your team's visibility settings in Jiminny. Only calls within your permitted scope are accessible.”
Trying to access private meeting - “Error: Access denied. This meeting has been marked as private by the host and cannot be accessed through the MCP connector. Try requesting a different call or ask the meeting host to change the visibility settings in Jiminny.”
Downgraded/Capture account — if a customer's plan drops below Scale tier or the Customer is on Capture in the first place - “Error: MCP access unavailable. The Jiminny MCP connector is available on the Scale plan and above. Your account does not currently have an active Scale subscription.”
Jiminny-side outage — “Error:Jiminny is temporarily unavailable (status 503). This is not a data or permissions issue — please retry in a few minutes.”
No data found - “Error:No calls found matching your criteria. Try adjusting your filters — for example, widening the date range, removing the account filter, or checking the rep name is spelled correctly in Jiminny.”
Allow customers to securely control who and what data is accessible externally
HIGH
Ensure MCP only exposes data user has access to - based on team visibility settings. This means that if a user is not allow to access calls/deals in Jiminny UI then they shouldn’t be able to access those through the MCP as well.
Private meetings shouldn’t be exposed via MCP
HIGH
When a meetings is set to Private then the information about it shouldn’t be exposed through the MCP.
Ensure Jiminny data can be combined with other sources (e.g. CRM, docs) in AI workflows
HIGH
Ensure data is structured to be easily combined with:
CRM (accounts, deals)
external docs
Use consistent identifiers:
account IDs
deal IDs
MCP is available only for Scale tier and above
HIGH
Customers who are on Capture tier should be able to access any of their data through MCP.
This should also cover the scenario when a customer has been on Scale but then downgrades to Capture - their MCP access should stop working.
Provide visibility into how external AI tools access Jiminny data
HIGH
Audit logs:
what data was accessed by which external system when
identity - who made the request
specific queries/filters used
failed access attempts (especially cross-visibility-boundary attempts)
Admins should be able to access the logs from the org settings.We can start with a csv export before building a specific page for it.
example from Atlassian -
Provide customers with example prompts to get started quickly
HIGH
MCP prompts are explicitly defined as prompt templates that clients can discover and call with arguments.
See examples in table below.
Expose Jiminny as a Connector in Claude
medium
Competitors like Fathom are listed as Connectors in Claude. This will make it easier for customers to find us and to connect Jiminny
Provide customers with example workflows to get started quickly
medium
A workflow is usually multiple steps, maybe multiple tools, still focused on one outcome.
See examples in table below.
Allow customers to use predefined Jiminny skills for common workflows
medium
Anthropic describes Skills as folders that include instructions, scripts, and resources that Claude can load when relevant, and as a way to teach Claude repeatable workflows, preferences, and domain expertise once instead of re-explaining them every time. Skills - a reusable package of behavior that can include prompts, instructions, resources, and sometimes scripts/tools for a broader job.
Claude skills - https://resources.anthropic.com/hubfs/The-Complete-Guide-to-Building-Skill-for-Claude.pdf?hsLang=en&utm_source=chatgpt.com
See examples in table below.
Jiminny UI widget for OpenAI
medium
The reason to have this is to make certain Jiminny use cases much easier than pure chat.
Instead of ChatGPT only replying with text like “Here are the last 5 ACME calls,” it could also show a visual Jiminny card or mini-app inside the chat. That widget could list calls, show a deal summary, let the user filter by rep/date/account, open a transcript section, or save a snippet—while the conversation continues in normal chat alongside it.
For Jiminny, the best widget use cases are the ones where users need to browse or compare rather than ask one-off questions. A strong example is deal review: the user asks ChatGPT, “What is the status of the ACME deal?” ChatGPT calls your Jiminny MCP tools, and the widget shows a compact deal view with recent calls, risks, next steps, stakeholders, and links to transcripts/snippets. The chat can still summarize the answer in words, but the widget gives a clearer, scannable interface.
Another good Jiminny widget use case is call search and exploration. A text answer can say “I found 12 calls mentioning pricing objections,” but a widget could show a sortable list with date, rep, account, score, and objection count, then let the user click into one call to see the exact excerpt or jump to a transcript section.
Allow customers to run long-running analyses asynchronously and retrieve progress/results
low
Some requests/questions require analysis of Hugh volumes of data. For those, it may be better to:
start the job
let it run in the background
return a status like “in progress”
let the client come back for the result later
For example - User asks in Claude:
“Analyse all calls from this quarter and tell me the top 5 objections by segment.”
That might require:
searching lots of calls
pulling many summaries/transcripts
aggregating results
Instead of making Claude wait 45+ seconds, Jiminny could:
create an analysis job...
|
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Position Jiminny as a data layer for AI-driven revenue workflows, not just a standalone product. 👤 Target user Revenue teams using AI tools (Sales, CS, RevOps) Companies already experimenting with Claude / OpenAI Mid-market & Enterprise customers with multiple data sources (CRM, docs, CI tools, Support tools etc) 🤕 Pain point or problem Jiminny data is locked in the platform AI tools lack access to high-value conversation context Customers must manually export/copy transcripts No easy way to combine calls with CRM + docs + other info - using the Jiminny API is not suitable for non technical sales people Peer pressure as almost all competitors have this 💥 Impact and benefits For customers Better AI outputs using real customer conversations Ability to build automated workflows across tools For Jiminny Increased product stickiness (embedded in workflows) Competitive parity with Gong / Avoma etc. 💡 Solution ideas Build an AI Knowledge Connector (MCP-based) that: Exposes Jiminny data (calls, transcripts, metadata) to AI tools Provides structured insights (summaries, action items, scoring etc.) Supports deal-level context Allows integration into customer-owned AI stacks (Claude + Zapier, etc.) Success metrics List the key goals and how you will measure success. Include both qualitative and quantitative metrics (e.g., user adoption, retention rate, revenue targets). Goal Metric Increase stickiness by ensuring Jiminny is embedded in the customer’s workflows % of customers connecting external AI tools Number of MCP/API calls per customer - and which ones are being used the most Decrease the manual copying of transcripts decrease by X % User interaction and design Simple setup flow: Generate API key / connect MCP Clear instructions for Claude / Zapier setup Provide: Example prompts for Claude Pre-built workflow templates for Zapier Clear documentation - with use cases 👉 Focus: usable by non-technical users Detailed Requirements List the functional and non-functional requirements. Prioritize them (e.g., High, Medium, Low) and add notes for clarification. Requirement Importance Notes Allow customers to connect Jiminny to their AI tools (e.g. Claude, OpenAI) HIGH Provide MCP endpoint so customers can easily integrate Jiminny into their AI stack Allow customers to access call data through AI tools HIGH Expose Jiminny data: list calls (filter by date, user, account, deal) get call get transcript (speaker-separated) get call metadata search calls (keyword + semantic) Support filtering by: account / contact/ lead / deal jiminny user date range Allow customers to search and query calls using AI tools HIGH Support keyword and semantic search across conversations Provide structured insights so customers can generate better outputs HIGH For each call, expose: Summary Action items Key points Activity type Notes Call Score CRM information Allow customers to understand deal status across multiple calls/emails HIGH For each deal expose: calls/meetings/emails Identified risks contacts related to the deal with their job title linked account details all CRM field information that we have in DI + fields used for CRM filling example - get_deal_summary request - { \"tool\": \"get_deal_summary\", \"arguments\": { \"deal_name\": \"ACME\" } } responce: { \"deal_name\": \"ACME\", \"stage\": \"Negotiation\", \"recent_activity\": [ \"Demo call on 2026-04-01\", \"Pricing discussion on 2026-04-03\" ], \"risks\": [ \"Pricing concerns\", \"Security review pending\" ], \"next_steps\": [ \"Send follow-up to VP Sales\", \"Share security documentation\" ] } Ensure the AI can easily understand the schema of the data coming from Jiminny HIGH Models perform much better when tools have: clear names rich descriptions predictable schemas Provide clear, actionable error states for customers when MCP connections fail HIGH Error messages should guide agents toward solutions with specific suggestions and next steps. Expired or revoked key — “Error: Authentication failed. The API key used to access Jiminny has been revoked or has expired. Please ask your Jiminny admin to generate a new API key in Settings > Organization > General and reconnect the MCP server.” Rate limit hit — “Error: Rate limit exceeded. Too many requests have been made to the Jiminny MCP server in a short period. Please wait 60 seconds before retrying.” Permissions mismatch — if a user tries to access data outside their team visibility settings - “Error: Access denied. The requested call (call_id: [X]) is outside your team's visibility settings in Jiminny. Only calls within your permitted scope are accessible.” Trying to access private meeting - “Error: Access denied. This meeting has been marked as private by the host and cannot be accessed through the MCP connector. Try requesting a different call or ask the meeting host to change the visibility settings in Jiminny.” Downgraded/Capture account — if a customer's plan drops below Scale tier or the Customer is on Capture in the first place - “Error: MCP access unavailable. The Jiminny MCP connector is available on the Scale plan and above. Your account does not currently have an active Scale subscription.” Jiminny-side outage — “Error:Jiminny is temporarily unavailable (status 503). This is not a data or permissions issue — please retry in a few minutes.” No data found - “Error:No calls found matching your criteria. Try adjusting your filters — for example, widening the date range, removing the account filter, or checking the rep name is spelled correctly in Jiminny.” Allow customers to securely control who and what data is accessible externally HIGH Ensure MCP only exposes data user has access to - based on team visibility settings. This means that if a user is not allow to access calls/deals in Jiminny UI then they shouldn’t be able to access those through the MCP as well. Private meetings shouldn’t be exposed via MCP HIGH When a meetings is set to Private then the information about it shouldn’t be exposed through the MCP. Ensure Jiminny data can be combined with other sources (e.g. CRM, docs) in AI workflows HIGH Ensure data is structured to be easily combined with: CRM (accounts, deals) external docs Use consistent identifiers: account IDs deal IDs MCP is available only for Scale tier and above HIGH Customers who are on Capture tier should be able to access any of their data through MCP. This should also cover the scenario when a customer has been on Scale but then downgrades to Capture - their MCP access should stop working. Provide visibility into how external AI tools access Jiminny data HIGH Audit logs: what data was accessed by which external system when identity - who made the request specific queries/filters used failed access attempts (especially cross-visibility-boundary attempts) Admins should be able to access the logs from the org settings.We can start with a csv export before building a specific page for it. example from Atlassian - Provide customers with example prompts to get started quickly HIGH MCP prompts are explicitly defined as prompt templates that clients can discover and call with arguments. See examples in table below. Expose Jiminny as a Connector in Claude medium Competitors like Fathom are listed as Connectors in Claude. This will make it easier for customers to find us and to connect Jiminny Provide customers with example workflows to get started quickly medium A workflow is usually multiple steps, maybe multiple tools, still focused on one outcome. See examples in table below. Allow customers to use predefined Jiminny skills for common workflows medium Anthropic describes Skills as folders that include instructions, scripts, and resources that Claude can load when relevant, and as a way to teach Claude repeatable workflows, preferences, and domain expertise once instead of re-explaining them every time. Skills - a reusable package of behavior that can include prompts, instructions, resources, and sometimes scripts/tools for a broader job. Claude skills - https://resources.anthropic.com/hubfs/The-Complete-Guide-to-Building-Skill-for-Claude.pdf?hsLang=en&utm_source=chatgpt.com See examples in table below. Jiminny UI widget for OpenAI medium The reason to have this is to make certain Jiminny use cases much easier than pure chat. Instead of ChatGPT only replying with text like “Here are the last 5 ACME calls,” it could also show a visual Jiminny card or mini-app inside the chat. That widget could list calls, show a deal summary, let the user filter by rep/date/account, open a transcript section, or save a snippet—while the conversation continues in normal chat alongside it. For Jiminny, the best widget use cases are the ones where users need to browse or compare rather than ask one-off questions. A strong example is deal review: the user asks ChatGPT, “What is the status of the ACME deal?” ChatGPT calls your Jiminny MCP tools, and the widget shows a compact deal view with recent calls, risks, next steps, stakeholders, and links to transcripts/snippets. The chat can still summarize the answer in words, but the widget gives a clearer, scannable interface. Another good Jiminny widget use case is call search and exploration. A text answer can say “I found 12 calls mentioning pricing objections,” but a widget could show a sortable list with date, rep, account, score, and objection count, then let the user click into one call to see the exact excerpt or jump to a transcript section. Allow customers to run long-running analyses asynchronously and retrieve progress/results low Some requests/questions require analysis of Hugh volumes of data. For those, it may be better to: start the job let it run in the background return a status like “in progress” let the client come back for the result later For example - User asks in Claude: “Analyse all calls from this quarter and tell me the top 5 objections by segment.” That might require: searching lots of calls pulling many summaries/transcripts aggregating results Instead of making Claude wait 45+ seconds, Jiminny could: create an analysis job return: job_id = 123, status = running We need this in order to support: large-scale analysis multi-call aggregation across lots of data playlist generation across many calls heavy recap/report generation Creating a snippet through the MCP low Create a shareable snippet from a call recording by specifying a time range. Useful for highlighting key moments — objection handling, pricing discussions, competitive mentions — and sharing them with your team. example request: { \"tool\": \"create_snippet\", \"arguments\": { \"call_id\": \"call_123\", \"start_time\": \"00:18:24\", \"end_time\": \"00:19:10\", \"title\": \"Pricing objection\" } } example response: { \"snippet_id\": \"snip_987\", \"title\": \"Pricing objection\", \"share_url\": \"https://app.jiminny.com/snippets/snip_987\" } Ability to add recordings or snippets to a playlist low Allow customers to create libraries of calls automatically. They can use those for onboarding or other purposes Allow AI tools to read reusable Jiminny resources low fathom Resources are useful for data that should be read consistently rather than recomputed every time. In Jiminny terms, that could be: current deal snapshot account summary weekly rep recap approved talk tracks / objection handling guidance curated playlists or snippet libraries This is useful because an AI can consume these directly as context, instead of repeatedly stitching together many tool calls. Ability to write coaching notes in Jiminny through MCP low What we want to do for prompts/worflows and skills Capability Type User value / job to be done Example Jiminny use case Inputs Steps performed Output Draft follow-up email Prompt Help reps quickly create tailored follow-ups after calls Use the latest customer call to draft an email with recap and next steps Call ID optional tone optional recipient type Retrieve call summary and action items from Jiminny. Pull key points, commitments, and next steps. Apply the chosen tone and structure. Draft the email in a consistent format. Customer-ready follow-up email draft Summarise call Prompt Help users quickly extract the most important points from a conversation Generate a concise summary of one call for internal or external use Call ID optional summary style optional audience Retrieve transcript, metadata, and structured insights. Identify key topics, decisions, risks, and next steps. Format output for the chosen audience. Short or structured call summary with actions and risks Generate deal recap Prompt Help reps and managers get a fast overview of a deal Summarise the current state of a deal based on recent calls and linked CRM context Deal ID or account name optional date range Retrieve calls and meetings linked to the deal. Pull deal metadata and CRM-linked context. Identify recent changes, blockers, risks, and next steps. Summarise into a concise recap. Deal recap with status, blockers, risks, and recommended next steps Prepare weekly recap Prompt Help managers or reps review what changed over a time period Weekly recap of calls, themes, and actions for one rep, team, or account Rep ID team ID or account ID time period Retrieve relevant calls and summaries for the selected time period. Aggregate themes, action items, and changes. Highlight notable risks, opportunities, and follow-ups. Weekly recap with top themes, risks, opportunities, and actions Prepare deal review Workflow Help reps and managers review deal status using multiple sources of context Review a deal before pipeline review or forecast meeting Deal ID optional date range Retrieve all recent calls, emails, and meetings tied to the deal. Pull structured call summaries, score, action items, and key points. Pull linked CRM context such as stage, contacts, and account details. Aggregate open risks, unresolved objections, stakeholder gaps, and next steps. Format into a review-ready structure. Deal review document with current status, risks, stakeholders, blockers, and next steps Weekly team recap Workflow Help managers monitor activity and risk across a group of reps or accounts End-of-week team summary for sales leadership Team ID date range Retrieve calls and structured insights across the team. Group by rep, account, or deal. Identify recurring themes, major risks, strong calls, and missed follow-ups. Highlight calls or deals that need attention. Team-level recap with patterns, key risks, notable wins, and action areas Objection analysis across calls Workflow Help teams identify patterns across multiple conversations Analyse pricing or competitor objections across recent calls Account ID deal ID rep ID keyword/topic date range Search calls matching the topic or keyword. Retrieve summaries, transcripts, and snippets where relevant. Identify recurring objections and how they were handled. Assess whether objections were resolved or remain open. Summarise patterns and examples. Objection analysis with themes, frequency, examples, and suggested follow-up actions Build onboarding playlist Workflow Help enablement teams curate useful learning content faster Build a playlist of strong discovery, demo, or pricing calls for new hires Topic call type rep/team filter optional time period Search for calls matching the selected criteria. Rank or filter calls based on score, topics, or key moments. Identify useful snippets or full recordings. Add selected calls/snippets into a playlist structure. Generate short descriptions for each item. Curated onboarding playlist with selected calls/snippets and descriptions Deal Inspection Skill Skill Give users a consistent, opinionated way to assess a deal Claude reviews a deal using a repeatable Jiminny methodology Deal ID or account name optional review scope Determine whether the request is suitable for a deal inspection. Retrieve relevant calls, summaries, CRM context, stakeholders, and risks. Apply a standard Jiminny review framework to assess deal health. Look for missing next steps, unresolved objections, stakeholder gaps, and warning signs. Present findings in a consistent structure with recommended actions. Structured deal inspection with health assessment, red flags, and recommendations Manager Coaching Skill Skill Help managers review calls consistently and identify coaching moments Analyse a rep’s call and surface strengths, gaps, and examples for coaching Call ID optional rep ID optional coaching focus Retrieve transcript, score, summary, and key moments from the call. Evaluate the conversation against a coaching framework. Identify what went well and where the rep could improve. Suggest moments to clip as snippets. Recommend coaching actions or playlist additions. Coaching review with strengths, gaps, snippet suggestions, and recommended coaching actions CSM / QBR Prep Skill Skill Help CS or AM teams prepare structured customer reviews from conversations Generate an account review or QBR-style summary from recent customer interactions Account ID, optional time period Retrieve all recent calls, emails, and account-linked context. Aggregate themes, requests, blockers, sentiment shifts, and opportunities. Apply a repeatable account review structure. Summarise outcomes, open issues, and suggested next steps. Structured QBR/account review summary with themes, risks, opportunities, and actions Snippet Builder Skill Skill Help users consistently capture and label useful moments from calls Identify useful moments in a call and convert them into reusable snippets Call ID, optional focus area such as pricing, objection, competitor, discovery Retrieve transcript, recording timeline, and call insights. Detect moments matching the requested focus area. Propose snippet start/end times and titles. Tag snippets by type or theme. Optionally save them or add them to a playlist. One or more proposed or saved snippets with title, timing, and tags 💡 Technical details Auth model needs specifying. Are API keys scoped per user, per team, or per Jiminny instance? If a key is generated by an admin, does it inherit their visibility level, or provide org-wide? Are permissions evaluated at query time or frozen at key creation? Needs to be query-time, otherwise permission changes won't propagate. Key lifecycle management is missing. No mention of rotation, expiry, or revocation. A departed employee's active key is a data leak. Need: revocation, optional expiry, alerts on stale keys, and consider whether keys should be tied to service accounts rather than personal users. Rate limiting should be HIGH. A compromised key or misconfigured automation could bulk-export an entire customer's call history. Need per-key rate limits and anomaly detection on unusual access patterns. Open Questions Track unresolved issues or decisions that need to be made. Update as answers become available. Question Answer Date Answered Competitor research Competitor MCP Availability Core Capabilities Advanced Capabilities Positioning Key Strength Key Weakness Gong ✅ Mature MCP List/search calls Get transcripts get Call metadata Deal intelligence Scorecards, analytics CRM context Enterprise data layer Deep data + ecosystem integrations Limited opinionated AI workflows Avoma ✅ Mature MCP list_meetings get_meeting get_transcript key topics Deal fields/Deal level analysis Coaching/Scoring CRM context pushing insights into Notion / Confluence AI-ready meeting intelligence Strongest “outputs” layer Mostly pull-based interactions Fathom ✅ MCP list/search meetings get transcript get summary/action items Team/org context Webhooks (event-based triggers) get_weekly_recap aggregated action items across meetings creating webhooks directly from the MCP server Lightweight meeting data access Includes summaries + actions Limited analytics depth Grain ✅ Basic MCP get meetings download transcripts Notes Deals Scorecards Data access utility Simple + accessible Low sophistication, sometimes browser-based Outreach ⚠️ MCP (workflow-focused) Search sequences Emails Meetings (Kaia) account / prospect / opportunity lookups Workflow automation Multi-system orchestration Revenue workflow engine End-to-end GTM workflows Less depth in conversation data Attention ⚠️ Emerging MCP Meeting data Transcripts CRM-linked context AI insights Sales assistant workflows create snippets AI sales assistant + CRM Strong CRM linkage Less focus on external knowledge layer Planhat - Related content Ask Jiminny Anything on Call level Galya Dimitrova Hubspot app Galya Dimitrova Product Vision & Strategy Galya Dimitrova Automated CRM Filling Simona Georgieva (Deactivated) Competitive analysis Galya Dimitrova AI agent ideas Steliyan Georgiev Comments James Graham 9 Apr A few areas around Security & Compliance that need more depth before this moves beyond draft: Auth model needs specifying. Are API keys scoped per user, per team, or per Jiminny instance? If a key is generated by an admin, does it inherit their visibility level, or provide org-wide? Are permissions evaluated at query time or frozen at key creation? Needs to be query-time, otherwise permission changes won't propagate. Team visibility enforcement should be its own HIGH requirement. The current note under access control (\"ensure MCP only exposes data user has access to\") is doing too much work as a single line. Every MCP tool response (especially search_calls and deal-level aggregations) must be filtered through the same visibility engine as the UI. Semantic search is the riskiest here; it could surface results across team boundaries if not properly scoped. No data minimisation or scoping controls. We're exposing transcripts, CRM fields, contact details with job titles, deal context - significant PII and commercial data leaving the platform. Can customers configure which data types are exposed? Can transcripts be PII-stripped before they leave Jiminny? Given we position GDPR consent as a differentiator, we should be thinking about this. GDPR downstream processing is unaddressed. Piping transcripts to OpenAI/Gemini introduces new data processors. Customers need to acknowledge responsibility for downstream processing during setup. We should also consider whether call participants' recording consent covers onward sharing to third-party AI - it almost certainly doesn't by default. This is one for me to pick up. Key lifecycle management is missing. No mention of rotation, expiry, or revocation. A departed employee's active key is a data leak. Need: revocation, optional expiry, alerts on stale keys, and consider whether keys should be tied to service accounts rather than personal users. Rate limiting should be HIGH. A compromised key or misconfigured automation could bulk-export an entire customer's call history. Need per-key rate limits and anomaly detection on unusual access patterns. Audit logs should go deeper. Current spec (what data, which system, when) is a start. Add: identity behind the key, specific queries/filters used, and failed access attempts (especially cross-visibility-boundary attempts). Enterprise compliance teams will expect this. Downgrade handling. Doc says Scale tier and above, but doesn't say what happens on downgrade. Keys should auto-deactivate. Happy to help draft a dedicated Security & Compliance section if useful. Galya Dimitrova 15 Apr Thanks for the input @James Graham . I made the product related changes in the table and for the rest I left them as a note in the Technical section for the team to look at when they start looking at this. I wonder about your points related to GDPR. Currently multiple customers are using the Customer API/zapier to feed this data to AI and BI tools. They are also manually exporting transcripts and other information from the platform and feeding it to AI tools. I don’t get how MCP is so much different that all of these and why it will introduce new data processors (which are already being utilised) and would require any changes to the consent provided by participants.","depth":21,"help_text":"","role_description":"heading","subrole":"AXUnknown"},{"role":"AXStaticText","text":"You said","depth":23,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"Jiminny MCP Connector","depth":23,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"Epic","depth":23,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"Link to Epik in Jira","depth":23,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"Document status","depth":23,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"DRAFT","depth":23,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"Objective","depth":23,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"Enable customers to connect Jiminny data to external AI tools (Claude, OpenAI, Gemini) so it can be used as part of their broader knowledge base and workflows.","depth":23,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"Position Jiminny as a data layer for AI-driven revenue workflows, not just a standalone product.","depth":23,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"👤 Target user","depth":23,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"Revenue teams using AI tools (Sales, CS, RevOps)","depth":23,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"Companies already experimenting with Claude / OpenAI","depth":23,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"Mid-market & Enterprise customers with multiple data sources (CRM, docs, CI tools, Support tools etc)","depth":23,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"🤕 Pain point or problem","depth":23,"bounds":{"left":0.30868056,"top":0.125,"width":0.077430554,"height":0.054444443},"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"Jiminny data is locked in the platform","depth":23,"bounds":{"left":0.30868056,"top":0.18777777,"width":0.074652776,"height":0.085},"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"AI tools lack access to high-value conversation context","depth":23,"bounds":{"left":0.30868056,"top":0.28111112,"width":0.10555556,"height":0.085},"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"Customers must manually export/copy transcripts","depth":23,"bounds":{"left":0.30868056,"top":0.37444445,"width":0.108333334,"height":0.085},"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"No easy way to combine calls with CRM + docs + other info - 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The API key used to access Jiminny has been revoked or has expired. Please ask your Jiminny admin to generate a new API key in Settings > Organization > General and reconnect the MCP server.”","depth":23,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"Rate limit hit — “Error: Rate limit exceeded. Too many requests have been made to the Jiminny MCP server in a short period. Please wait 60 seconds before retrying.”","depth":23,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"Permissions mismatch — if a user tries to access data outside their team visibility settings - “Error: Access denied. The requested call (call_id: [X]) is outside your team's visibility settings in Jiminny. Only calls within your permitted scope are accessible.”","depth":23,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"Trying to access private meeting - “Error: Access denied. 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This is not a data or permissions issue — please retry in a few minutes.”","depth":23,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"No data found - “Error:No calls found matching your criteria. Try adjusting your filters — for example, widening the date range, removing the account filter, or checking the rep name is spelled correctly in Jiminny.”","depth":23,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"Allow customers to securely control who and what data is accessible externally","depth":23,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"HIGH","depth":23,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"Ensure MCP only exposes data user has access to - based on team visibility settings. 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This will make it easier for customers to find us and to connect Jiminny","depth":23,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"Provide customers with example workflows to get started quickly","depth":23,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"medium","depth":23,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"A workflow is usually multiple steps, maybe multiple tools, still focused on one outcome.","depth":23,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"See examples in table below.","depth":23,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"Allow customers to use predefined Jiminny skills for common workflows","depth":23,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"medium","depth":23,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"Anthropic describes Skills as folders that include instructions, scripts, and resources that Claude can load when relevant, and as a way to teach Claude repeatable workflows, preferences, and domain expertise once instead of re-explaining them every time. Skills - a reusable package of behavior that can include prompts, instructions, resources, and sometimes scripts/tools for a broader job.","depth":23,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"Claude skills - https://resources.anthropic.com/hubfs/The-Complete-Guide-to-Building-Skill-for-Claude.pdf?hsLang=en&utm_source=chatgpt.com","depth":23,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"See examples in table below.","depth":23,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"Jiminny UI widget for OpenAI","depth":23,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"medium","depth":23,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"The reason to have this is to make certain Jiminny use cases much easier than pure chat.","depth":23,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"Instead of ChatGPT only replying with text like “Here are the last 5 ACME calls,” it could also show a visual Jiminny card or mini-app inside the chat. That widget could list calls, show a deal summary, let the user filter by rep/date/account, open a transcript section, or save a snippet—while the conversation continues in normal chat alongside it.","depth":23,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"For Jiminny, the best widget use cases are the ones where users need to browse or compare rather than ask one-off questions. A strong example is deal review: the user asks ChatGPT, “What is the status of the ACME deal?” ChatGPT calls your Jiminny MCP tools, and the widget shows a compact deal view with recent calls, risks, next steps, stakeholders, and links to transcripts/snippets. The chat can still summarize the answer in words, but the widget gives a clearer, scannable interface.","depth":23,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"Another good Jiminny widget use case is call search and exploration. A text answer can say “I found 12 calls mentioning pricing objections,” but a widget could show a sortable list with date, rep, account, score, and objection count, then let the user click into one call to see the exact excerpt or jump to a transcript section.","depth":23,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"Allow customers to run long-running analyses asynchronously and retrieve progress/results","depth":23,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"low","depth":23,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"Some requests/questions require analysis of Hugh volumes of data. For those, it may be better to:","depth":23,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"start the job","depth":23,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"let it run in the background","depth":23,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"return a status like “in progress”","depth":23,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"let the client come back for the result later","depth":23,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"For example - User asks in Claude:","depth":23,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"“Analyse all calls from this quarter and tell me the top 5 objections by segment.”","depth":23,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"That might require:","depth":23,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"searching lots of calls","depth":23,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"pulling many summaries/transcripts","depth":23,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"aggregating results","depth":23,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"Instead of making Claude wait 45+ seconds, Jiminny could:","depth":23,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"create an analysis job","depth":23,"help_text":"","role_description":"text","subrole":"AXUnknown"}]...
|
-5527921122764584061
|
7411094662425498137
|
idle
|
accessibility
|
NULL
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Platform Sprint 2 Q2 - Platform Team - Scrum Board Platform Sprint 2 Q2 - Platform Team - Scrum Board - Jira
SevenShores\Hubspot\Exceptions\BadRequest: Client error: `POST [URL_WITH_CREDENTIALS] Graham . I made the product related changes in the table and for the rest I left them as a note in the Technical section for the team to look at when they start looking at this. I wonder about your points related to GDPR. Currently multiple customers are using the Customer API/zapier to feed this data to AI and BI tools. They are also manually exporting transcripts and other information from the platform and feeding it to AI tools. I don’t get how MCP is so much different that all of these and why it will introduce new data processors (which are already being utilised) and would require any changes to the consent provided by participants.
You said
Jiminny MCP Connector
Epic
Link to Epik in Jira
Document status
DRAFT
Objective
Enable customers to connect Jiminny data to external AI tools (Claude, OpenAI, Gemini) so it can be used as part of their broader knowledge base and workflows.
Position Jiminny as a data layer for AI-driven revenue workflows, not just a standalone product.
👤 Target user
Revenue teams using AI tools (Sales, CS, RevOps)
Companies already experimenting with Claude / OpenAI
Mid-market & Enterprise customers with multiple data sources (CRM, docs, CI tools, Support tools etc)
🤕 Pain point or problem
Jiminny data is locked in the platform
AI tools lack access to high-value conversation context
Customers must manually export/copy transcripts
No easy way to combine calls with CRM + docs + other info - using the Jiminny API is not suitable for non technical sales people
Peer pressure as almost all competitors have this
💥 Impact and benefits
For customers
Better AI outputs using real customer conversations
Ability to build automated workflows across tools
For Jiminny
Increased product stickiness (embedded in workflows)
Competitive parity with Gong / Avoma etc.
💡 Solution ideas
Build an AI Knowledge Connector (MCP-based) that:
Exposes Jiminny data (calls, transcripts, metadata) to AI tools
Provides structured insights (summaries, action items, scoring etc.)
Supports deal-level context
Allows integration into customer-owned AI stacks (Claude + Zapier, etc.)
Success metrics
List the key goals and how you will measure success. Include both qualitative and quantitative metrics (e.g., user adoption, retention rate, revenue targets).
Goal
Metric
Increase stickiness by ensuring Jiminny is embedded in the customer’s workflows
% of customers connecting external AI tools
Number of MCP/API calls per customer - and which ones are being used the most
Decrease the manual copying of transcripts
decrease by X %
User interaction and design
Simple setup flow:
Generate API key / connect MCP
Clear instructions for Claude / Zapier setup
Provide:
Example prompts for Claude
Pre-built workflow templates for Zapier
Clear documentation - with use cases
👉 Focus: usable by non-technical users
Detailed Requirements
List the functional and non-functional requirements. Prioritize them (e.g., High, Medium, Low) and add notes for clarification.
Requirement
Importance
Notes
Allow customers to connect Jiminny to their AI tools (e.g. Claude, OpenAI)
HIGH
Provide MCP endpoint so customers can easily integrate Jiminny into their AI stack
Allow customers to access call data through AI tools
HIGH
Expose Jiminny data:
list calls (filter by date, user, account, deal)
get call
get transcript (speaker-separated)
get call metadata
search calls (keyword + semantic)
Support filtering by:
account / contact/ lead / deal
jiminny user
date range
Allow customers to search and query calls using AI tools
HIGH
Support keyword and semantic search across conversations
Provide structured insights so customers can generate better outputs
HIGH
For each call, expose:
Summary
Action items
Key points
Activity type
Notes
Call Score
CRM information
Allow customers to understand deal status across multiple calls/emails
HIGH
For each deal expose:
calls/meetings/emails
Identified risks
contacts related to the deal with their job title
linked account details
all CRM field information that we have in DI + fields used for CRM filling
example - get_deal_summary
request -
{
"tool": "get_deal_summary",
"arguments": {
"deal_name": "ACME"
}
}
responce:
{
"deal_name": "ACME",
"stage": "Negotiation",
"recent_activity": [
"Demo call on 2026-04-01",
"Pricing discussion on 2026-04-03"
],
"risks": [
"Pricing concerns",
"Security review pending"
], "next_steps": [
"Send follow-up to VP Sales",
"Share security documentation"
]
}
Ensure the AI can easily understand the schema of the data coming from Jiminny
HIGH
Models perform much better when tools have:
clear names
rich descriptions
predictable schemas
Provide clear, actionable error states for customers when MCP connections fail
HIGH
Error messages should guide agents toward solutions with specific suggestions and next steps.
Expired or revoked key — “Error: Authentication failed. The API key used to access Jiminny has been revoked or has expired. Please ask your Jiminny admin to generate a new API key in Settings > Organization > General and reconnect the MCP server.”
Rate limit hit — “Error: Rate limit exceeded. Too many requests have been made to the Jiminny MCP server in a short period. Please wait 60 seconds before retrying.”
Permissions mismatch — if a user tries to access data outside their team visibility settings - “Error: Access denied. The requested call (call_id: [X]) is outside your team's visibility settings in Jiminny. Only calls within your permitted scope are accessible.”
Trying to access private meeting - “Error: Access denied. This meeting has been marked as private by the host and cannot be accessed through the MCP connector. Try requesting a different call or ask the meeting host to change the visibility settings in Jiminny.”
Downgraded/Capture account — if a customer's plan drops below Scale tier or the Customer is on Capture in the first place - “Error: MCP access unavailable. The Jiminny MCP connector is available on the Scale plan and above. Your account does not currently have an active Scale subscription.”
Jiminny-side outage — “Error:Jiminny is temporarily unavailable (status 503). This is not a data or permissions issue — please retry in a few minutes.”
No data found - “Error:No calls found matching your criteria. Try adjusting your filters — for example, widening the date range, removing the account filter, or checking the rep name is spelled correctly in Jiminny.”
Allow customers to securely control who and what data is accessible externally
HIGH
Ensure MCP only exposes data user has access to - based on team visibility settings. This means that if a user is not allow to access calls/deals in Jiminny UI then they shouldn’t be able to access those through the MCP as well.
Private meetings shouldn’t be exposed via MCP
HIGH
When a meetings is set to Private then the information about it shouldn’t be exposed through the MCP.
Ensure Jiminny data can be combined with other sources (e.g. CRM, docs) in AI workflows
HIGH
Ensure data is structured to be easily combined with:
CRM (accounts, deals)
external docs
Use consistent identifiers:
account IDs
deal IDs
MCP is available only for Scale tier and above
HIGH
Customers who are on Capture tier should be able to access any of their data through MCP.
This should also cover the scenario when a customer has been on Scale but then downgrades to Capture - their MCP access should stop working.
Provide visibility into how external AI tools access Jiminny data
HIGH
Audit logs:
what data was accessed by which external system when
identity - who made the request
specific queries/filters used
failed access attempts (especially cross-visibility-boundary attempts)
Admins should be able to access the logs from the org settings.We can start with a csv export before building a specific page for it.
example from Atlassian -
Provide customers with example prompts to get started quickly
HIGH
MCP prompts are explicitly defined as prompt templates that clients can discover and call with arguments.
See examples in table below.
Expose Jiminny as a Connector in Claude
medium
Competitors like Fathom are listed as Connectors in Claude. This will make it easier for customers to find us and to connect Jiminny
Provide customers with example workflows to get started quickly
medium
A workflow is usually multiple steps, maybe multiple tools, still focused on one outcome.
See examples in table below.
Allow customers to use predefined Jiminny skills for common workflows
medium
Anthropic describes Skills as folders that include instructions, scripts, and resources that Claude can load when relevant, and as a way to teach Claude repeatable workflows, preferences, and domain expertise once instead of re-explaining them every time. Skills - a reusable package of behavior that can include prompts, instructions, resources, and sometimes scripts/tools for a broader job.
Claude skills - https://resources.anthropic.com/hubfs/The-Complete-Guide-to-Building-Skill-for-Claude.pdf?hsLang=en&utm_source=chatgpt.com
See examples in table below.
Jiminny UI widget for OpenAI
medium
The reason to have this is to make certain Jiminny use cases much easier than pure chat.
Instead of ChatGPT only replying with text like “Here are the last 5 ACME calls,” it could also show a visual Jiminny card or mini-app inside the chat. That widget could list calls, show a deal summary, let the user filter by rep/date/account, open a transcript section, or save a snippet—while the conversation continues in normal chat alongside it.
For Jiminny, the best widget use cases are the ones where users need to browse or compare rather than ask one-off questions. A strong example is deal review: the user asks ChatGPT, “What is the status of the ACME deal?” ChatGPT calls your Jiminny MCP tools, and the widget shows a compact deal view with recent calls, risks, next steps, stakeholders, and links to transcripts/snippets. The chat can still summarize the answer in words, but the widget gives a clearer, scannable interface.
Another good Jiminny widget use case is call search and exploration. A text answer can say “I found 12 calls mentioning pricing objections,” but a widget could show a sortable list with date, rep, account, score, and objection count, then let the user click into one call to see the exact excerpt or jump to a transcript section.
Allow customers to run long-running analyses asynchronously and retrieve progress/results
low
Some requests/questions require analysis of Hugh volumes of data. For those, it may be better to:
start the job
let it run in the background
return a status like “in progress”
let the client come back for the result later
For example - User asks in Claude:
“Analyse all calls from this quarter and tell me the top 5 objections by segment.”
That might require:
searching lots of calls
pulling many summaries/transcripts
aggregating results
Instead of making Claude wait 45+ seconds, Jiminny could:
create an analysis job...
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2026-04-22T15:11:48.012365+00:00
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/Users/lukas/.screenpipe/data/data/2026-04-22/1776 /Users/lukas/.screenpipe/data/data/2026-04-22/1776870708012_m2.jpg...
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Firefox
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Architecture overview - Model Context Protocol — W Architecture overview - Model Context Protocol — Work...
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True
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modelcontextprotocol.io/docs/learn/architecture
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monitor_2
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NULL
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NULL
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Platform Sprint 2 Q2 - Platform Team - Scrum Board Platform Sprint 2 Q2 - Platform Team - Scrum Board - Jira
SevenShores\Hubspot\Exceptions\BadRequest: Client error: `POST [URL_WITH_CREDENTIALS] Graham . I made the product related changes in the table and for the rest I left them as a note in the Technical section for the team to look at when they start looking at this. I wonder about your points related to GDPR. Currently multiple customers are using the Customer API/zapier to feed this data to AI and BI tools. They are also manually exporting transcripts and other information from the platform and feeding it to AI tools. I don’t get how MCP is so much different that all of these and why it will introduce new data processors (which are already being utilised) and would require any changes to the consent provided by participants.
You said
Jiminny MCP Connector
Epic
Link to Epik in Jira
Document status
DRAFT
Objective
Enable customers to connect Jiminny data to external AI tools (Claude, OpenAI, Gemini) so it can be used as part of their broader knowledge base and workflows.
Position Jiminny as a data layer for AI-driven revenue workflows, not just a standalone product.
👤 Target user
Revenue teams using AI tools (Sales, CS, RevOps)
Companies already experimenting with Claude / OpenAI
Mid-market & Enterprise customers with multiple data sources (CRM, docs, CI tools, Support tools etc)
🤕 Pain point or problem
Jiminny data is locked in the platform
AI tools lack access to high-value conversation context
Customers must manually export/copy transcripts
No easy way to combine calls with CRM + docs + other info - using the Jiminny API is not suitable for non technical sales people
Peer pressure as almost all competitors have this
💥 Impact and benefits
For customers
Better AI outputs using real customer conversations
Ability to build automated workflows across tools
For Jiminny
Increased product stickiness (embedded in workflows)
Competitive parity with Gong / Avoma etc.
💡 Solution ideas
Build an AI Knowledge Connector (MCP-based) that:
Exposes Jiminny data (calls, transcripts, metadata) to AI tools
Provides structured insights (summaries, action items, scoring etc.)
Supports deal-level context
Allows integration into customer-owned AI stacks (Claude + Zapier, etc.)
Success metrics
List the key goals and how you will measure success. Include both qualitative and quantitative metrics (e.g., user adoption, retention rate, revenue targets).
Goal
Metric
Increase stickiness by ensuring Jiminny is embedded in the customer’s workflows
% of customers connecting external AI tools
Number of MCP/API calls per customer - and which ones are being used the most
Decrease the manual copying of transcripts
decrease by X %
User interaction and design
Simple setup flow:
Generate API key / connect MCP
Clear instructions for Claude / Zapier setup
Provide:
Example prompts for Claude
Pre-built workflow templates for Zapier
Clear documentation - with use cases
👉 Focus: usable by non-technical users
Detailed Requirements
List the functional and non-functional requirements. Prioritize them (e.g., High, Medium, Low) and add notes for clarification.
Requirement
Importance
Notes
Allow customers to connect Jiminny to their AI tools (e.g. Claude, OpenAI)
HIGH
Provide MCP endpoint so customers can easily integrate Jiminny into their AI stack
Allow customers to access call data through AI tools
HIGH
Expose Jiminny data:
list calls (filter by date, user, account, deal)
get call
get transcript (speaker-separated)
get call metadata
search calls (keyword + semantic)
Support filtering by:
account / contact/ lead / deal
jiminny user
date range
Allow customers to search and query calls using AI tools
HIGH
Support keyword and semantic search across conversations
Provide structured insights so customers can generate better outputs
HIGH
For each call, expose:
Summary
Action items
Key points
Activity type
Notes
Call Score
CRM information
Allow customers to understand deal status across multiple calls/emails
HIGH
For each deal expose:
calls/meetings/emails
Identified risks
contacts related to the deal with their job title
linked account details
all CRM field information that we have in DI + fields used for CRM filling
example - get_deal_summary
request -
{
"tool": "get_deal_summary",
"arguments": {
"deal_name": "ACME"
}
}
responce:
{
"deal_name": "ACME",
"stage": "Negotiation",
"recent_activity": [
"Demo call on 2026-04-01",
"Pricing discussion on 2026-04-03"
],
"risks": [
"Pricing concerns",
"Security review pending"
], "next_steps": [
"Send follow-up to VP Sales",
"Share security documentation"
]
}
Ensure the AI can easily understand the schema of the data coming from Jiminny
HIGH
Models perform much better when tools have:
clear names
rich descriptions
predictable schemas
Provide clear, actionable error states for customers when MCP connections fail
HIGH
Error messages should guide agents toward solutions with specific suggestions and next steps.
Expired or revoked key — “Error: Authentication failed. The API key used to access Jiminny has been revoked or has expired. Please ask your Jiminny admin to generate a new API key in Settings > Organization > General and reconnect the MCP server.”
Rate limit hit — “Error: Rate limit exceeded. Too many requests have been made to the Jiminny MCP server in a short period. Please wait 60 seconds before retrying.”
Permissions mismatch — if a user tries to access data outside their team visibility settings - “Error: Access denied. The requested call (call_id: [X]) is outside your team's visibility settings in Jiminny. Only calls within your permitted scope are accessible.”
Trying to access private meeting - “Error: Access denied. This meeting has been marked as private by the host and cannot be accessed through the MCP connector. Try requesting a different call or ask the meeting host to change the visibility settings in Jiminny.”
Downgraded/Capture account — if a customer's plan drops below Scale tier or the Customer is on Capture in the first place - “Error: MCP access unavailable. The Jiminny MCP connector is available on the Scale plan and above. Your account does not currently have an active Scale subscription.”
Jiminny-side outage — “Error:Jiminny is temporarily unavailable (status 503). This is not a data or permissions issue — please retry in a few minutes.”
No data found - “Error:No calls found matching your criteria. Try adjusting your filters — for example, widening the date range, removing the account filter, or checking the rep name is spelled correctly in Jiminny.”
Allow customers to securely control who and what data is accessible externally
HIGH
Ensure MCP only exposes data user has access to - based on team visibility settings. This means that if a user is not allow to access calls/deals in Jiminny UI then they shouldn’t be able to access those through the MCP as well.
Private meetings shouldn’t be exposed via MCP
HIGH
When a meetings is set to Private then the information about it shouldn’t be exposed through the MCP.
Ensure Jiminny data can be combined with other sources (e.g. CRM, docs) in AI workflows
HIGH
Ensure data is structured to be easily combined with:
CRM (accounts, deals)
external docs
Use consistent identifiers:
account IDs
deal IDs
MCP is available only for Scale tier and above
HIGH
Customers who are on Capture tier should be able to access any of their data through MCP.
This should also cover the scenario when a customer has been on Scale but then downgrades to Capture - their MCP access should stop working.
Provide visibility into how external AI tools access Jiminny data
HIGH
Audit logs:
what data was accessed by which external system when
identity - who made the request
specific queries/filters used
failed access attempts (especially cross-visibility-boundary attempts)
Admins should be able to access the logs from the org settings.We can start with a csv export before building a specific page for it.
example from Atlassian -
Provide customers with example prompts to get started quickly
HIGH
MCP prompts are explicitly defined as prompt templates that clients can discover and call with arguments.
See examples in table below.
Expose Jiminny as a Connector in Claude
medium
Competitors like Fathom are listed as Connectors in Claude. This will make it easier for customers to find us and to connect Jiminny
Provide customers with example workflows to get started quickly
medium
A workflow is usually multiple steps, maybe multiple tools, still focused on one outcome.
See examples in table below.
Allow customers to use predefined Jiminny skills for common workflows
medium
Anthropic describes Skills as folders that include instructions, scripts, and resources that Claude can load when relevant, and as a way to teach Claude repeatable workflows, preferences, and domain expertise once instead of re-explaining them every time. Skills - a reusable package of behavior that can include prompts, instructions, resources, and sometimes scripts/tools for a broader job.
Claude skills - https://resources.anthropic.com/hubfs/The-Complete-Guide-to-Building-Skill-for-Claude.pdf?hsLang=en&utm_source=chatgpt.com
See examples in table below.
Jiminny UI widget for OpenAI
medium
The reason to have this is to make certain Jiminny use cases much easier than pure chat.
Instead of ChatGPT only replying with text like “Here are the last 5 ACME calls,” it could also show a visual Jiminny card or mini-app inside the chat. That widget could list calls, show a deal summary, let the user filter by rep/date/account, open a transcript section, or save a snippet—while the conversation continues in normal chat alongside it.
For Jiminny, the best widget use cases are the ones where users need to browse or compare rather than ask one-off questions. A strong example is deal review: the user asks ChatGPT, “What is the status of the ACME deal?” ChatGPT calls your Jiminny MCP tools, and the widget shows a compact deal view with recent calls, risks, next steps, stakeholders, and links to transcripts/snippets. The chat can still summarize the answer in words, but the widget gives a clearer, scannable interface.
Another good Jiminny widget use case is call search and exploration. A text answer can say “I found 12 calls mentioning pricing objections,” but a widget could show a sortable list with date, rep, account, score, and objection count, then let the user click into one call to see the exact excerpt or jump to a transcript section.
Allow customers to run long-running analyses asynchronously and retrieve progress/results
low
Some requests/questions require analysis of Hugh volumes of data. For those, it may be better to:
start the job
let it run in the background
return a status like “in progress”
let the client come back for the result later
For example - User asks in Claude:
“Analyse all calls from this quarter and tell me the top 5 objections by segment.”
That might require:
searching lots of calls
pulling many summaries/transcripts
aggregating results
Instead of making Claude wait 45+ seconds, Jiminny could:
create an analysis job
return: job_id = 123, status = running
We need this in order to support:
large-scale analysis
multi-call aggregation across lots of data
playlist generation across many calls
heavy recap/report generation
Creating a snippet through the MCP
low
Create a shareable snippet from a call recording by specifying a time range. Useful for highlighting key moments — objection handling, pricing discussions, competitive mentions — and sharing them with your team.
example request:
{
"tool": "create_snippet",
"arguments": {
"call_id": "call_123",
"start_time": "00:18:24",
"end_time": "00:19:10",
"title": "Pricing objection"
}
}
example response:
{
"snippet_id": "snip_987",
"title": "Pricing objection",
"share_url": "https://app.jiminny.com/snippets/snip_987"
}
Ability to add recordings or snippets to a playlist
low
Allow customers to create libraries of calls automatically. They can use those for onboarding or other purposes
Allow AI tools to read reusable Jiminny resources
low
fathom
Resources are useful for data that should be read consistently rather than recomputed every time. In Jiminny terms, that could be:
current deal snapshot
account summary
weekly rep recap
approved talk tracks / objection handling guidance
curated playlists or snippet libraries
This is useful because an AI can consume these directly as context, instead of repeatedly stitching together many tool calls.
Ability to write coaching notes in Jiminny through MCP
low
What we want to do for prompts/worflows and skills
Capability
Type
User value / job to be done
Example Jiminny use case
Inputs
Steps performed
Output
Draft follow-up email
Prompt
Help reps quickly create tailored follow-ups after calls
Use the latest customer call to draft an email with recap and next steps
Call ID
optional tone
optional recipient type
Retrieve call summary and action items from Jiminny.
Pull key points, commitments, and next steps.
Apply the chosen tone and structure.
Draft the email in a consistent format.
Customer-ready follow-up email draft
Summarise call
Prompt
Help users quickly extract the most important points from a conversation
Generate a concise summary of one call for internal or external use
Call ID
optional summary style
optional audience
Retrieve transcript, metadata, and structured insights.
Identify key topics, decisions, risks, and next steps.
Format output for the chosen audience.
Short or structured call summary with actions and risks
Generate deal recap
Prompt
Help reps and managers get a fast overview of a deal
Summarise the current state of a deal based on recent calls and linked CRM context
Deal ID or account name
optional date range
Retrieve calls and meetings linked to the deal.
Pull deal metadata and CRM-linked context.
Identify recent changes, blockers, risks, and next steps.
Summarise into a concise recap.
Deal recap with status, blockers, risks, and recommended next steps
Prepare weekly recap
Prompt
Help managers or reps review what changed over a time period
Weekly recap of calls, themes, and actions for one rep, team, or account
Rep ID
team ID or account ID
time period
Retrieve relevant calls and summaries for the selected time period.
Aggregate themes, action items, and changes.
Highlight notable risks, opportunities, and follow-ups.
Weekly recap with top themes, risks, opportunities, and actions
Prepare deal review
Workflow
Help reps and managers review deal status using multiple sources of context
Review a deal before pipeline review or forecast meeting
Deal ID
optional date range
Retrieve all recent calls, emails, and meetings tied to the deal.
Pull structured call summaries, score, action items, and key points.
Pull linked CRM context such as stage, contacts, and account details.
Aggregate open risks, unresolved objections, stakeholder gaps, and next steps.
Format into a review-ready structure.
Deal review document with current status, risks, stakeholders, blockers, and next steps
Weekly team recap
Workflow
Help managers monitor activity and risk across a group of reps or accounts
End-of-week team summary for sales leadership
Team ID
date range
Retrieve calls and structured insights across the team.
Group by rep, account, or deal.
Identify recurring themes, major risks, strong calls, and missed follow-ups.
Highlight calls or deals that need attention.
Team-level recap with patterns, key risks, notable wins, and action areas
Objection analysis across calls
Workflow
Help teams identify patterns across multiple conversations
Analyse pricing or competitor objections across recent calls
Account ID
deal ID
rep ID
keyword/topic
date range
Search calls matching the topic or keyword.
Retrieve summaries, transcripts, and snippets where relevant.
Identify recurring objections and how they were handled.
Assess whether objections were resolved or remain open.
Summarise patterns and examples.
Objection analysis with themes, frequency, examples, and suggested follow-up actions
Build onboarding playlist
Workflow
Help enablement teams curate useful learning content faster
Build a playlist of strong discovery, demo, or pricing calls for new hires
Topic
call type
rep/team filter
optional time period
Search for calls matching the selected criteria.
Rank or filter calls based on score, topics, or key moments.
Identify useful snippets or full recordings.
Add selected calls/snippets into a playlist structure.
Generate short descriptions for each item.
Curated onboarding playlist with selected calls/snippets and descriptions
Deal Inspection Skill
Skill
Give users a consistent, opinionated way to assess a deal
Claude reviews a deal using a repeatable Jiminny methodology
Deal ID or account name
optional review scope
Determine whether the request is suitable for a deal inspection.
Retrieve relevant calls, summaries, CRM context, stakeholders, and risks.
Apply a standard Jiminny review framework to assess deal health.
Look for missing next steps, unresolved objections, stakeholder gaps, and warning signs.
Present findings in a consistent structure with recommended actions.
Structured deal inspection with health assessment, red flags, and recommendations
Manager Coaching Skill
Skill
Help managers review calls consistently and identify coaching moments
Analyse a rep’s call and surface strengths, gaps, and examples for coaching
Call ID
optional rep ID
optional coaching focus
Retrieve transcript, score, summary, and key moments from the call.
Evaluate the conversation against a coaching framework.
Identify what went well and where the rep could improve.
Suggest moments to clip as snippets.
Recommend coaching actions or playlist additions.
Coaching review with strengths, gaps, snippet suggestions, and recommended coaching actions
CSM / QBR Prep Skill
Skill
Help CS or AM teams prepare structured customer reviews from conversations
Generate an account review or QBR-style summary from recent customer interactions
Account ID, optional time period
Retrieve all recent calls, emails, and account-linked context.
Aggregate themes, requests, blockers, sentiment shifts, and opportunities.
Apply a repeatable account review structure.
Summarise outcomes, open issues, and suggested next steps.
Structured QBR/account review summary with themes, risks, opportunities, and actions
Snippet Builder Skill
Skill
Help users consistently capture and label useful moments from calls
Identify useful moments in a call and convert them into reusable snippets
Call ID, optional focus area such as pricing, objection, competitor, discovery
Retrieve transcript, recording timeline, and call insights.
Detect moments matching the requested focus area.
Propose snippet start/end times and titles.
Tag snippets by type or theme.
Optionally save them or add them to a playlist.
One or more proposed or saved snippets with title, timing, and tags
💡 Technical details
Auth model needs specifying. Are API keys scoped per user, per team, or per Jiminny instance? If a key is generated by an admin, does it inherit their visibility level, or provide org-wide? Are permissions evaluated at query time or frozen at key creation? Needs to be query-time, otherwise permission changes won't propagate.
Key lifecycle management is missing. No mention of rotation, expiry, or revocation. A departed employee's active key is a data leak. Need: revocation, optional expiry, alerts on stale keys, and consider whether keys should be tied to service accounts rather than personal users.
Rate limiting should be HIGH. A compromised key or misconfigured automation could bulk-export an entire customer's call history. Need per-key rate limits and anomaly detection on unusual access patterns.
Open Questions
Track unresolved issues or decisions that need to be made. Update as answers become available.
Question
Answer
Date Answered
Competitor research
Competitor
MCP Availability
Core Capabilities
Advanced Capabilities
Positioning
Key Strength
Key Weakness
Gong
✅ Mature MCP
List/search calls
Get transcripts
get Call metadata
Deal intelligence
Scorecards, analytics
CRM context
Enterprise data layer
Deep data + ecosystem integrations
Limited opinionated AI workflows
Avoma
✅ Mature MCP
list_meetings
get_meeting
get_transcript
key topics
Deal fields/Deal level analysis
Coaching/Scoring
CRM context
pushing insights into Notion / Confluence
AI-ready meeting intelligence
Strongest “outputs” layer
Mostly pull-based interactions
Fathom
✅ MCP
list/search meetings
get transcript
get summary/action items
Team/org context
Webhooks (event-based triggers)
get_weekly_recap
aggregated action items across meetings
creating webhooks directly from the MCP server
Lightweight meeting data access
Includes summaries + actions
Limited analytics depth
Grain
✅ Basic MCP
get meetings
download transcripts
Notes
Deals
Scorecards
Data access utility
Simple + accessible
Low sophistication, sometimes browser-based
Outreach
⚠️ MCP (workflow-focused)
Search sequences
Emails
Meetings (Kaia)
account / prospect / opportunity lookups
Workflow automation
Multi-system orchestration
Revenue workflow engine
End-to-end GTM workflows
Less depth in conversation data
Attention
⚠️ Emerging MCP
Meeting data
Transcripts
CRM-linked context
AI insights
Sales assistant workflows
create snippets
AI sales assistant + CRM
Strong CRM linkage
Less focus on external knowledge layer
Planhat -
Related content
Ask Jiminny Anything on Call level
Galya Dimitrova
Hubspot app
Galya Dimitrova
Product Vision & Strategy
Galya Dimitrova
Automated CRM Filling
Simona Georgieva (Deactivated)
Competitive analysis
Galya Dimitrova
AI agent ideas
Steliyan Georgiev
Comments
James Graham
9 Apr
A few areas around Security & Compliance that need more depth before this moves beyond draft:
Auth model needs specifying. Are API keys scoped per user, per team, or per Jiminny instance? If a key is generated by an admin, does it inherit their visibility level, or provide org-wide? Are permissions evaluated at query time or frozen at key creation? Needs to be query-time, otherwise permission changes won't propagate.
Team visibility enforcement should be its own HIGH requirement. The current note under access control ("ensure MCP only exposes data user has access to") is doing too much work as a single line. Every MCP tool response (especially search_calls and deal-level aggregations) must be filtered through the same visibility engine as the UI. Semantic search is the riskiest here; it could surface results across team boundaries if not properly scoped.
No data minimisation or scoping controls. We're exposing transcripts, CRM fields, contact details with job titles, deal context - significant PII and commercial data leaving the platform. Can customers configure which data types are exposed? Can transcripts be PII-stripped before they leave Jiminny? Given we position GDPR consent as a differentiator, we should be thinking about this.
GDPR downstream processing is unaddressed. Piping transcripts to OpenAI/Gemini introduces new data processors. Customers need to acknowledge responsibility for downstream processing during setup. We should also consider whether call participants' recording consent covers onward sharing to third-party AI - it almost certainly doesn't by default. This is one for me to pick up.
Key lifecycle management is missing. No mention of rotation, expiry, or revocation. A departed employee's active key is a data leak. Need: revocation, optional expiry, alerts on stale keys, and consider whether keys should be tied to service accounts rather than personal users.
Rate limiting should be HIGH. A compromised key or misconfigured automation could bulk-export an entire customer's call history. Need per-key rate limits and anomaly detection on unusual ac...
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Objective Enable customers to connect Jiminny data to external AI tools (Claude, OpenAI, Gemini) so it can be used as part of their broader knowledge base and workflows. Position Jiminny as a data layer for AI-driven revenue workflows, not just a standalone product. 👤 Target user Revenue teams using AI tools (Sales, CS, RevOps) Companies already experimenting with Claude / OpenAI Mid-market & Enterprise customers with multiple data sources (CRM, docs, CI tools, Support tools etc) 🤕 Pain point or problem Jiminny data is locked in the platform AI tools lack access to high-value conversation context Customers must manually export/copy transcripts No easy way to combine calls with CRM + docs + other info - using the Jiminny API is not suitable for non technical sales people Peer pressure as almost all competitors have this 💥 Impact and benefits For customers Better AI outputs using real customer conversations Ability to build automated workflows across tools For Jiminny Increased product stickiness (embedded in workflows) Competitive parity with Gong / Avoma etc. 💡 Solution ideas Build an AI Knowledge Connector (MCP-based) that: Exposes Jiminny data (calls, transcripts, metadata) to AI tools Provides structured insights (summaries, action items, scoring etc.) Supports deal-level context Allows integration into customer-owned AI stacks (Claude + Zapier, etc.) Success metrics List the key goals and how you will measure success. Include both qualitative and quantitative metrics (e.g., user adoption, retention rate, revenue targets). Goal Metric Increase stickiness by ensuring Jiminny is embedded in the customer’s workflows % of customers connecting external AI tools Number of MCP/API calls per customer - and which ones are being used the most Decrease the manual copying of transcripts decrease by X % User interaction and design Simple setup flow: Generate API key / connect MCP Clear instructions for Claude / Zapier setup Provide: Example prompts for Claude Pre-built workflow templates for Zapier Clear documentation - with use cases 👉 Focus: usable by non-technical users Detailed Requirements List the functional and non-functional requirements. Prioritize them (e.g., High, Medium, Low) and add notes for clarification. Requirement Importance Notes Allow customers to connect Jiminny to their AI tools (e.g. Claude, OpenAI) HIGH Provide MCP endpoint so customers can easily integrate Jiminny into their AI stack Allow customers to access call data through AI tools HIGH Expose Jiminny data: list calls (filter by date, user, account, deal) get call get transcript (speaker-separated) get call metadata search calls (keyword + semantic) Support filtering by: account / contact/ lead / deal jiminny user date range Allow customers to search and query calls using AI tools HIGH Support keyword and semantic search across conversations Provide structured insights so customers can generate better outputs HIGH For each call, expose: Summary Action items Key points Activity type Notes Call Score CRM information Allow customers to understand deal status across multiple calls/emails HIGH For each deal expose: calls/meetings/emails Identified risks contacts related to the deal with their job title linked account details all CRM field information that we have in DI + fields used for CRM filling example - get_deal_summary request - { \"tool\": \"get_deal_summary\", \"arguments\": { \"deal_name\": \"ACME\" } } responce: { \"deal_name\": \"ACME\", \"stage\": \"Negotiation\", \"recent_activity\": [ \"Demo call on 2026-04-01\", \"Pricing discussion on 2026-04-03\" ], \"risks\": [ \"Pricing concerns\", \"Security review pending\" ], \"next_steps\": [ \"Send follow-up to VP Sales\", \"Share security documentation\" ] } Ensure the AI can easily understand the schema of the data coming from Jiminny HIGH Models perform much better when tools have: clear names rich descriptions predictable schemas Provide clear, actionable error states for customers when MCP connections fail HIGH Error messages should guide agents toward solutions with specific suggestions and next steps. Expired or revoked key — “Error: Authentication failed. The API key used to access Jiminny has been revoked or has expired. Please ask your Jiminny admin to generate a new API key in Settings > Organization > General and reconnect the MCP server.” Rate limit hit — “Error: Rate limit exceeded. Too many requests have been made to the Jiminny MCP server in a short period. Please wait 60 seconds before retrying.” Permissions mismatch — if a user tries to access data outside their team visibility settings - “Error: Access denied. The requested call (call_id: [X]) is outside your team's visibility settings in Jiminny. Only calls within your permitted scope are accessible.” Trying to access private meeting - “Error: Access denied. This meeting has been marked as private by the host and cannot be accessed through the MCP connector. Try requesting a different call or ask the meeting host to change the visibility settings in Jiminny.” Downgraded/Capture account — if a customer's plan drops below Scale tier or the Customer is on Capture in the first place - “Error: MCP access unavailable. The Jiminny MCP connector is available on the Scale plan and above. Your account does not currently have an active Scale subscription.” Jiminny-side outage — “Error:Jiminny is temporarily unavailable (status 503). This is not a data or permissions issue — please retry in a few minutes.” No data found - “Error:No calls found matching your criteria. Try adjusting your filters — for example, widening the date range, removing the account filter, or checking the rep name is spelled correctly in Jiminny.” Allow customers to securely control who and what data is accessible externally HIGH Ensure MCP only exposes data user has access to - based on team visibility settings. This means that if a user is not allow to access calls/deals in Jiminny UI then they shouldn’t be able to access those through the MCP as well. Private meetings shouldn’t be exposed via MCP HIGH When a meetings is set to Private then the information about it shouldn’t be exposed through the MCP. Ensure Jiminny data can be combined with other sources (e.g. CRM, docs) in AI workflows HIGH Ensure data is structured to be easily combined with: CRM (accounts, deals) external docs Use consistent identifiers: account IDs deal IDs MCP is available only for Scale tier and above HIGH Customers who are on Capture tier should be able to access any of their data through MCP. This should also cover the scenario when a customer has been on Scale but then downgrades to Capture - their MCP access should stop working. Provide visibility into how external AI tools access Jiminny data HIGH Audit logs: what data was accessed by which external system when identity - who made the request specific queries/filters used failed access attempts (especially cross-visibility-boundary attempts) Admins should be able to access the logs from the org settings.We can start with a csv export before building a specific page for it. example from Atlassian - Provide customers with example prompts to get started quickly HIGH MCP prompts are explicitly defined as prompt templates that clients can discover and call with arguments. See examples in table below. Expose Jiminny as a Connector in Claude medium Competitors like Fathom are listed as Connectors in Claude. This will make it easier for customers to find us and to connect Jiminny Provide customers with example workflows to get started quickly medium A workflow is usually multiple steps, maybe multiple tools, still focused on one outcome. See examples in table below. Allow customers to use predefined Jiminny skills for common workflows medium Anthropic describes Skills as folders that include instructions, scripts, and resources that Claude can load when relevant, and as a way to teach Claude repeatable workflows, preferences, and domain expertise once instead of re-explaining them every time. Skills - a reusable package of behavior that can include prompts, instructions, resources, and sometimes scripts/tools for a broader job. Claude skills - https://resources.anthropic.com/hubfs/The-Complete-Guide-to-Building-Skill-for-Claude.pdf?hsLang=en&utm_source=chatgpt.com See examples in table below. Jiminny UI widget for OpenAI medium The reason to have this is to make certain Jiminny use cases much easier than pure chat. Instead of ChatGPT only replying with text like “Here are the last 5 ACME calls,” it could also show a visual Jiminny card or mini-app inside the chat. That widget could list calls, show a deal summary, let the user filter by rep/date/account, open a transcript section, or save a snippet—while the conversation continues in normal chat alongside it. For Jiminny, the best widget use cases are the ones where users need to browse or compare rather than ask one-off questions. A strong example is deal review: the user asks ChatGPT, “What is the status of the ACME deal?” ChatGPT calls your Jiminny MCP tools, and the widget shows a compact deal view with recent calls, risks, next steps, stakeholders, and links to transcripts/snippets. The chat can still summarize the answer in words, but the widget gives a clearer, scannable interface. Another good Jiminny widget use case is call search and exploration. A text answer can say “I found 12 calls mentioning pricing objections,” but a widget could show a sortable list with date, rep, account, score, and objection count, then let the user click into one call to see the exact excerpt or jump to a transcript section. Allow customers to run long-running analyses asynchronously and retrieve progress/results low Some requests/questions require analysis of Hugh volumes of data. For those, it may be better to: start the job let it run in the background return a status like “in progress” let the client come back for the result later For example - User asks in Claude: “Analyse all calls from this quarter and tell me the top 5 objections by segment.” That might require: searching lots of calls pulling many summaries/transcripts aggregating results Instead of making Claude wait 45+ seconds, Jiminny could: create an analysis job return: job_id = 123, status = running We need this in order to support: large-scale analysis multi-call aggregation across lots of data playlist generation across many calls heavy recap/report generation Creating a snippet through the MCP low Create a shareable snippet from a call recording by specifying a time range. Useful for highlighting key moments — objection handling, pricing discussions, competitive mentions — and sharing them with your team. example request: { \"tool\": \"create_snippet\", \"arguments\": { \"call_id\": \"call_123\", \"start_time\": \"00:18:24\", \"end_time\": \"00:19:10\", \"title\": \"Pricing objection\" } } example response: { \"snippet_id\": \"snip_987\", \"title\": \"Pricing objection\", \"share_url\": \"https://app.jiminny.com/snippets/snip_987\" } Ability to add recordings or snippets to a playlist low Allow customers to create libraries of calls automatically. They can use those for onboarding or other purposes Allow AI tools to read reusable Jiminny resources low fathom Resources are useful for data that should be read consistently rather than recomputed every time. In Jiminny terms, that could be: current deal snapshot account summary weekly rep recap approved talk tracks / objection handling guidance curated playlists or snippet libraries This is useful because an AI can consume these directly as context, instead of repeatedly stitching together many tool calls. Ability to write coaching notes in Jiminny through MCP low What we want to do for prompts/worflows and skills Capability Type User value / job to be done Example Jiminny use case Inputs Steps performed Output Draft follow-up email Prompt Help reps quickly create tailored follow-ups after calls Use the latest customer call to draft an email with recap and next steps Call ID optional tone optional recipient type Retrieve call summary and action items from Jiminny. Pull key points, commitments, and next steps. Apply the chosen tone and structure. Draft the email in a consistent format. Customer-ready follow-up email draft Summarise call Prompt Help users quickly extract the most important points from a conversation Generate a concise summary of one call for internal or external use Call ID optional summary style optional audience Retrieve transcript, metadata, and structured insights. Identify key topics, decisions, risks, and next steps. Format output for the chosen audience. Short or structured call summary with actions and risks Generate deal recap Prompt Help reps and managers get a fast overview of a deal Summarise the current state of a deal based on recent calls and linked CRM context Deal ID or account name optional date range Retrieve calls and meetings linked to the deal. Pull deal metadata and CRM-linked context. Identify recent changes, blockers, risks, and next steps. Summarise into a concise recap. Deal recap with status, blockers, risks, and recommended next steps Prepare weekly recap Prompt Help managers or reps review what changed over a time period Weekly recap of calls, themes, and actions for one rep, team, or account Rep ID team ID or account ID time period Retrieve relevant calls and summaries for the selected time period. Aggregate themes, action items, and changes. Highlight notable risks, opportunities, and follow-ups. Weekly recap with top themes, risks, opportunities, and actions Prepare deal review Workflow Help reps and managers review deal status using multiple sources of context Review a deal before pipeline review or forecast meeting Deal ID optional date range Retrieve all recent calls, emails, and meetings tied to the deal. Pull structured call summaries, score, action items, and key points. Pull linked CRM context such as stage, contacts, and account details. Aggregate open risks, unresolved objections, stakeholder gaps, and next steps. Format into a review-ready structure. Deal review document with current status, risks, stakeholders, blockers, and next steps Weekly team recap Workflow Help managers monitor activity and risk across a group of reps or accounts End-of-week team summary for sales leadership Team ID date range Retrieve calls and structured insights across the team. Group by rep, account, or deal. Identify recurring themes, major risks, strong calls, and missed follow-ups. Highlight calls or deals that need attention. Team-level recap with patterns, key risks, notable wins, and action areas Objection analysis across calls Workflow Help teams identify patterns across multiple conversations Analyse pricing or competitor objections across recent calls Account ID deal ID rep ID keyword/topic date range Search calls matching the topic or keyword. Retrieve summaries, transcripts, and snippets where relevant. Identify recurring objections and how they were handled. Assess whether objections were resolved or remain open. Summarise patterns and examples. Objection analysis with themes, frequency, examples, and suggested follow-up actions Build onboarding playlist Workflow Help enablement teams curate useful learning content faster Build a playlist of strong discovery, demo, or pricing calls for new hires Topic call type rep/team filter optional time period Search for calls matching the selected criteria. Rank or filter calls based on score, topics, or key moments. Identify useful snippets or full recordings. Add selected calls/snippets into a playlist structure. Generate short descriptions for each item. Curated onboarding playlist with selected calls/snippets and descriptions Deal Inspection Skill Skill Give users a consistent, opinionated way to assess a deal Claude reviews a deal using a repeatable Jiminny methodology Deal ID or account name optional review scope Determine whether the request is suitable for a deal inspection. Retrieve relevant calls, summaries, CRM context, stakeholders, and risks. Apply a standard Jiminny review framework to assess deal health. Look for missing next steps, unresolved objections, stakeholder gaps, and warning signs. Present findings in a consistent structure with recommended actions. Structured deal inspection with health assessment, red flags, and recommendations Manager Coaching Skill Skill Help managers review calls consistently and identify coaching moments Analyse a rep’s call and surface strengths, gaps, and examples for coaching Call ID optional rep ID optional coaching focus Retrieve transcript, score, summary, and key moments from the call. Evaluate the conversation against a coaching framework. Identify what went well and where the rep could improve. Suggest moments to clip as snippets. Recommend coaching actions or playlist additions. Coaching review with strengths, gaps, snippet suggestions, and recommended coaching actions CSM / QBR Prep Skill Skill Help CS or AM teams prepare structured customer reviews from conversations Generate an account review or QBR-style summary from recent customer interactions Account ID, optional time period Retrieve all recent calls, emails, and account-linked context. Aggregate themes, requests, blockers, sentiment shifts, and opportunities. Apply a repeatable account review structure. Summarise outcomes, open issues, and suggested next steps. Structured QBR/account review summary with themes, risks, opportunities, and actions Snippet Builder Skill Skill Help users consistently capture and label useful moments from calls Identify useful moments in a call and convert them into reusable snippets Call ID, optional focus area such as pricing, objection, competitor, discovery Retrieve transcript, recording timeline, and call insights. Detect moments matching the requested focus area. Propose snippet start/end times and titles. Tag snippets by type or theme. Optionally save them or add them to a playlist. One or more proposed or saved snippets with title, timing, and tags 💡 Technical details Auth model needs specifying. Are API keys scoped per user, per team, or per Jiminny instance? If a key is generated by an admin, does it inherit their visibility level, or provide org-wide? Are permissions evaluated at query time or frozen at key creation? Needs to be query-time, otherwise permission changes won't propagate. Key lifecycle management is missing. No mention of rotation, expiry, or revocation. A departed employee's active key is a data leak. Need: revocation, optional expiry, alerts on stale keys, and consider whether keys should be tied to service accounts rather than personal users. Rate limiting should be HIGH. A compromised key or misconfigured automation could bulk-export an entire customer's call history. Need per-key rate limits and anomaly detection on unusual access patterns. Open Questions Track unresolved issues or decisions that need to be made. Update as answers become available. Question Answer Date Answered Competitor research Competitor MCP Availability Core Capabilities Advanced Capabilities Positioning Key Strength Key Weakness Gong ✅ Mature MCP List/search calls Get transcripts get Call metadata Deal intelligence Scorecards, analytics CRM context Enterprise data layer Deep data + ecosystem integrations Limited opinionated AI workflows Avoma ✅ Mature MCP list_meetings get_meeting get_transcript key topics Deal fields/Deal level analysis Coaching/Scoring CRM context pushing insights into Notion / Confluence AI-ready meeting intelligence Strongest “outputs” layer Mostly pull-based interactions Fathom ✅ MCP list/search meetings get transcript get summary/action items Team/org context Webhooks (event-based triggers) get_weekly_recap aggregated action items across meetings creating webhooks directly from the MCP server Lightweight meeting data access Includes summaries + actions Limited analytics depth Grain ✅ Basic MCP get meetings download transcripts Notes Deals Scorecards Data access utility Simple + accessible Low sophistication, sometimes browser-based Outreach ⚠️ MCP (workflow-focused) Search sequences Emails Meetings (Kaia) account / prospect / opportunity lookups Workflow automation Multi-system orchestration Revenue workflow engine End-to-end GTM workflows Less depth in conversation data Attention ⚠️ Emerging MCP Meeting data Transcripts CRM-linked context AI insights Sales assistant workflows create snippets AI sales assistant + CRM Strong CRM linkage Less focus on external knowledge layer Planhat - Related content Ask Jiminny Anything on Call level Galya Dimitrova Hubspot app Galya Dimitrova Product Vision & Strategy Galya Dimitrova Automated CRM Filling Simona Georgieva (Deactivated) Competitive analysis Galya Dimitrova AI agent ideas Steliyan Georgiev Comments James Graham 9 Apr A few areas around Security & Compliance that need more depth before this moves beyond draft: Auth model needs specifying. Are API keys scoped per user, per team, or per Jiminny instance? If a key is generated by an admin, does it inherit their visibility level, or provide org-wide? Are permissions evaluated at query time or frozen at key creation? Needs to be query-time, otherwise permission changes won't propagate. Team visibility enforcement should be its own HIGH requirement. The current note under access control (\"ensure MCP only exposes data user has access to\") is doing too much work as a single line. Every MCP tool response (especially search_calls and deal-level aggregations) must be filtered through the same visibility engine as the UI. Semantic search is the riskiest here; it could surface results across team boundaries if not properly scoped. No data minimisation or scoping controls. We're exposing transcripts, CRM fields, contact details with job titles, deal context - significant PII and commercial data leaving the platform. Can customers configure which data types are exposed? Can transcripts be PII-stripped before they leave Jiminny? Given we position GDPR consent as a differentiator, we should be thinking about this. GDPR downstream processing is unaddressed. Piping transcripts to OpenAI/Gemini introduces new data processors. Customers need to acknowledge responsibility for downstream processing during setup. We should also consider whether call participants' recording consent covers onward sharing to third-party AI - it almost certainly doesn't by default. This is one for me to pick up. Key lifecycle management is missing. No mention of rotation, expiry, or revocation. A departed employee's active key is a data leak. Need: revocation, optional expiry, alerts on stale keys, and consider whether keys should be tied to service accounts rather than personal users. Rate limiting should be HIGH. A compromised key or misconfigured automation could bulk-export an entire customer's call history. Need per-key rate limits and anomaly detection on unusual access patterns. Audit logs should go deeper. Current spec (what data, which system, when) is a start. Add: identity behind the key, specific queries/filters used, and failed access attempts (especially cross-visibility-boundary attempts). Enterprise compliance teams will expect this. Downgrade handling. Doc says Scale tier and above, but doesn't say what happens on downgrade. Keys should auto-deactivate. Happy to help draft a dedicated Security & Compliance section if useful. Galya Dimitrova 15 Apr Thanks for the input @James Graham . I made the product related changes in the table and for the rest I left them as a note in the Technical section for the team to look at when they start looking at this. I wonder about your points related to GDPR. Currently multiple customers are using the Customer API/zapier to feed this data to AI and BI tools. They are also manually exporting transcripts and other information from the platform and feeding it to AI tools. I don’t get how MCP is so much different that all of these and why it will introduce new data processors (which are already being utilised) and would require any changes to the consent provided by participants.","depth":21,"bounds":{"left":0.41805187,"top":0.19313647,"width":0.051861703,"height":0.11173184},"help_text":"","role_description":"heading","subrole":"AXUnknown"},{"role":"AXStaticText","text":"You said","depth":23,"bounds":{"left":0.36053857,"top":0.19553073,"width":0.019946808,"height":0.016360734},"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"Jiminny MCP Connector","depth":23,"bounds":{"left":0.41805187,"top":0.1963288,"width":0.03125,"height":0.038707104},"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"Epic","depth":23,"bounds":{"left":0.41805187,"top":0.30806065,"width":0.010305851,"height":0.016360734},"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"Link to Epik in Jira","depth":23,"bounds":{"left":0.41805187,"top":0.33040702,"width":0.043218084,"height":0.016360734},"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"Document status","depth":23,"bounds":{"left":0.41805187,"top":0.3527534,"width":0.04105718,"height":0.016360734},"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"DRAFT","depth":23,"bounds":{"left":0.41805187,"top":0.37509975,"width":0.016289894,"height":0.016360734},"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"Objective","depth":23,"bounds":{"left":0.41805187,"top":0.39744613,"width":0.024268618,"height":0.016360734},"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"Enable customers to connect Jiminny data to external AI tools (Claude, OpenAI, Gemini) so it can be used as part of their broader knowledge base and workflows.","depth":23,"bounds":{"left":0.41805187,"top":0.4197925,"width":0.051529255,"height":0.17278531},"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"Position Jiminny as a data layer for AI-driven revenue workflows, not just a standalone product.","depth":23,"bounds":{"left":0.41805187,"top":0.59856343,"width":0.049700797,"height":0.10574621},"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"👤 Target user","depth":23,"bounds":{"left":0.41805187,"top":0.75458896,"width":0.033909574,"height":0.016759777},"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"Revenue teams using AI tools (Sales, CS, RevOps)","depth":23,"bounds":{"left":0.41805187,"top":0.7773344,"width":0.051030584,"height":0.061053474},"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"Companies already experimenting with Claude / OpenAI","depth":23,"bounds":{"left":0.41805187,"top":0.8443735,"width":0.04637633,"height":0.061053474},"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"Mid-market & Enterprise customers with multiple data sources (CRM, docs, CI tools, Support tools etc)","depth":23,"bounds":{"left":0.41805187,"top":0.9114126,"width":0.051363032,"height":0.0885874},"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"🤕 Pain point or problem","depth":23,"bounds":{"left":0.41805187,"top":1.0,"width":0.03706782,"height":-0.0897845},"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"Jiminny data is locked in the platform","depth":23,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"AI tools lack access to high-value conversation context","depth":23,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"Customers must manually export/copy transcripts","depth":23,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"No easy way to combine calls with CRM + docs + other info - 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-","depth":23,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"{","depth":23,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"\"tool\": \"get_deal_summary\",","depth":23,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"\"arguments\": {","depth":23,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"\"deal_name\": \"ACME\"","depth":23,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"}","depth":23,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"}","depth":23,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"responce:","depth":23,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"{","depth":23,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"\"deal_name\": \"ACME\",","depth":23,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"\"stage\": \"Negotiation\",","depth":23,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"\"recent_activity\": [","depth":23,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"\"Demo call on 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Sales\",","depth":23,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"\"Share security documentation\"","depth":23,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"]","depth":23,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"}","depth":23,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"Ensure the AI can easily understand the schema of the data coming from Jiminny","depth":23,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"HIGH","depth":23,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"Models perform much better when tools have:","depth":23,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"clear 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The API key used to access Jiminny has been revoked or has expired. Please ask your Jiminny admin to generate a new API key in Settings > Organization > General and reconnect the MCP server.”","depth":23,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"Rate limit hit — “Error: Rate limit exceeded. Too many requests have been made to the Jiminny MCP server in a short period. Please wait 60 seconds before retrying.”","depth":23,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"Permissions mismatch — if a user tries to access data outside their team visibility settings - “Error: Access denied. The requested call (call_id: [X]) is outside your team's visibility settings in Jiminny. Only calls within your permitted scope are accessible.”","depth":23,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"Trying to access private meeting - “Error: Access denied. This meeting has been marked as private by the host and cannot be accessed through the MCP connector. Try requesting a different call or ask the meeting host to change the visibility settings in Jiminny.”","depth":23,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"Downgraded/Capture account — if a customer's plan drops below Scale tier or the Customer is on Capture in the first place - “Error: MCP access unavailable. The Jiminny MCP connector is available on the Scale plan and above. Your account does not currently have an active Scale subscription.”","depth":23,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"Jiminny-side outage — “Error:Jiminny is temporarily unavailable (status 503). This is not a data or permissions issue — please retry in a few minutes.”","depth":23,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"No data found - “Error:No calls found matching your criteria. Try adjusting your filters — for example, widening the date range, removing the account filter, or checking the rep name is spelled correctly in Jiminny.”","depth":23,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"Allow customers to securely control who and what data is accessible externally","depth":23,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"HIGH","depth":23,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"Ensure MCP only exposes data user has access to - based on team visibility settings. This means that if a user is not allow to access calls/deals in Jiminny UI then they shouldn’t be able to access those through the MCP as well.","depth":23,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"Private meetings shouldn’t be exposed via MCP","depth":23,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"HIGH","depth":23,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"When a meetings is set to Private then the information about it shouldn’t be exposed through the MCP.","depth":23,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"Ensure Jiminny data can be combined with other sources (e.g. CRM, docs) in AI workflows","depth":23,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"HIGH","depth":23,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"Ensure data is structured to be easily combined with:","depth":23,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"CRM (accounts, deals)","depth":23,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"external docs","depth":23,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"Use consistent identifiers:","depth":23,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"account IDs","depth":23,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"deal IDs","depth":23,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"MCP is available only for Scale tier and above","depth":23,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"HIGH","depth":23,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"Customers who are on Capture tier should be able to access any of their data through MCP.","depth":23,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"This should also cover the scenario when a customer has been on Scale but then downgrades to Capture - their MCP access should stop working.","depth":23,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"Provide visibility into how external AI tools access Jiminny data","depth":23,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"HIGH","depth":23,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"Audit logs:","depth":23,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"what data was accessed by which external system when","depth":23,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"identity - who made the request","depth":23,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"specific queries/filters used","depth":23,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"failed access attempts (especially cross-visibility-boundary attempts)","depth":23,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"Admins should be able to access the logs from the org settings.We can start with a csv export before building a specific page for it.","depth":23,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"example from Atlassian -","depth":23,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"Provide customers with example prompts to get started quickly","depth":23,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"HIGH","depth":23,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"MCP prompts are explicitly defined as prompt templates that clients can discover and call with arguments.","depth":23,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"See examples in table below.","depth":23,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"Expose Jiminny as a Connector in Claude","depth":23,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"medium","depth":23,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"Competitors like Fathom are listed as Connectors in Claude. This will make it easier for customers to find us and to connect Jiminny","depth":23,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"Provide customers with example workflows to get started quickly","depth":23,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"medium","depth":23,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"A workflow is usually multiple steps, maybe multiple tools, still focused on one outcome.","depth":23,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"See examples in table below.","depth":23,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"Allow customers to use predefined Jiminny skills for common workflows","depth":23,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"medium","depth":23,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"Anthropic describes Skills as folders that include instructions, scripts, and resources that Claude can load when relevant, and as a way to teach Claude repeatable workflows, preferences, and domain expertise once instead of re-explaining them every time. Skills - a reusable package of behavior that can include prompts, instructions, resources, and sometimes scripts/tools for a broader job.","depth":23,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"Claude skills - https://resources.anthropic.com/hubfs/The-Complete-Guide-to-Building-Skill-for-Claude.pdf?hsLang=en&utm_source=chatgpt.com","depth":23,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"See examples in table below.","depth":23,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"Jiminny UI widget for OpenAI","depth":23,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"medium","depth":23,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"The reason to have this is to make certain Jiminny use cases much easier than pure chat.","depth":23,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"Instead of ChatGPT only replying with text like “Here are the last 5 ACME calls,” it could also show a visual Jiminny card or mini-app inside the chat. That widget could list calls, show a deal summary, let the user filter by rep/date/account, open a transcript section, or save a snippet—while the conversation continues in normal chat alongside it.","depth":23,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"For Jiminny, the best widget use cases are the ones where users need to browse or compare rather than ask one-off questions. A strong example is deal review: the user asks ChatGPT, “What is the status of the ACME deal?” ChatGPT calls your Jiminny MCP tools, and the widget shows a compact deal view with recent calls, risks, next steps, stakeholders, and links to transcripts/snippets. The chat can still summarize the answer in words, but the widget gives a clearer, scannable interface.","depth":23,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"Another good Jiminny widget use case is call search and exploration. A text answer can say “I found 12 calls mentioning pricing objections,” but a widget could show a sortable list with date, rep, account, score, and objection count, then let the user click into one call to see the exact excerpt or jump to a transcript section.","depth":23,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"Allow customers to run long-running analyses asynchronously and retrieve progress/results","depth":23,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"low","depth":23,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"Some requests/questions require analysis of Hugh volumes of data. 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Useful for highlighting key moments — objection handling, pricing discussions, competitive mentions — and sharing them with your team.","depth":23,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"example request:","depth":23,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"{","depth":23,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"\"tool\": \"create_snippet\",","depth":23,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"\"arguments\": {","depth":23,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"\"call_id\": \"call_123\",","depth":23,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"\"start_time\": \"00:18:24\",","depth":23,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"\"end_time\": \"00:19:10\",","depth":23,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"\"title\": \"Pricing objection\"","depth":23,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"}","depth":23,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"}","depth":23,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"example response:","depth":23,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"{","depth":23,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"\"snippet_id\": \"snip_987\",","depth":23,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"\"title\": \"Pricing objection\",","depth":23,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"\"share_url\": \"https://app.jiminny.com/snippets/snip_987\"","depth":23,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"}","depth":23,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"Ability to add recordings or snippets to a playlist","depth":23,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"low","depth":23,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"Allow customers to create libraries of calls automatically. They can use those for onboarding or other purposes","depth":23,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"Allow AI tools to read reusable Jiminny resources","depth":23,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"low","depth":23,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"fathom","depth":23,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"Resources are useful for data that should be read consistently rather than recomputed every time. In Jiminny terms, that could be:","depth":23,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"current deal snapshot","depth":23,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"account summary","depth":23,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"weekly rep recap","depth":23,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"approved talk tracks / objection handling guidance","depth":23,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"curated playlists or snippet libraries","depth":23,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"This is useful because an AI can consume these directly as context, instead of repeatedly stitching together many tool 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depth","depth":23,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"Grain","depth":23,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"✅ Basic MCP","depth":23,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"get meetings","depth":23,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"download transcripts","depth":23,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"Notes","depth":23,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"Deals","depth":23,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"Scorecards","depth":23,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"Data access utility","depth":23,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"Simple + accessible","depth":23,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"Low sophistication, sometimes browser-based","depth":23,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"Outreach","depth":23,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"⚠️ MCP (workflow-focused)","depth":23,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"Search sequences","depth":23,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"Emails","depth":23,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"Meetings (Kaia)","depth":23,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"account / prospect / opportunity lookups","depth":23,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"Workflow automation","depth":23,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"Multi-system orchestration","depth":23,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"Revenue workflow engine","depth":23,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"End-to-end GTM workflows","depth":23,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"Less depth in conversation data","depth":23,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"Attention","depth":23,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"⚠️ Emerging MCP","depth":23,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"Meeting data","depth":23,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"Transcripts","depth":23,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"CRM-linked context","depth":23,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"AI insights","depth":23,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"Sales assistant workflows","depth":23,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"create snippets","depth":23,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"AI sales assistant + CRM","depth":23,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"Strong CRM linkage","depth":23,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"Less focus on external knowledge layer","depth":23,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"Planhat -","depth":23,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"Related content","depth":23,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"Ask Jiminny Anything on Call level","depth":23,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"Galya Dimitrova","depth":23,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"Hubspot app","depth":23,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"Galya Dimitrova","depth":23,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"Product Vision & Strategy","depth":23,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"Galya Dimitrova","depth":23,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"Automated CRM Filling","depth":23,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"Simona Georgieva (Deactivated)","depth":23,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"Competitive analysis","depth":23,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"Galya Dimitrova","depth":23,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"AI agent ideas","depth":23,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"Steliyan Georgiev","depth":23,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"Comments","depth":23,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"James Graham","depth":23,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"9 Apr","depth":23,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"A few areas around Security & Compliance that need more depth before this moves beyond draft:","depth":23,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"Auth model needs specifying. Are API keys scoped per user, per team, or per Jiminny instance? If a key is generated by an admin, does it inherit their visibility level, or provide org-wide? Are permissions evaluated at query time or frozen at key creation? Needs to be query-time, otherwise permission changes won't propagate.","depth":23,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"Team visibility enforcement should be its own HIGH requirement. The current note under access control (\"ensure MCP only exposes data user has access to\") is doing too much work as a single line. Every MCP tool response (especially search_calls and deal-level aggregations) must be filtered through the same visibility engine as the UI. Semantic search is the riskiest here; it could surface results across team boundaries if not properly scoped.","depth":23,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"No data minimisation or scoping controls. We're exposing transcripts, CRM fields, contact details with job titles, deal context - significant PII and commercial data leaving the platform. Can customers configure which data types are exposed? Can transcripts be PII-stripped before they leave Jiminny? Given we position GDPR consent as a differentiator, we should be thinking about this.","depth":23,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"GDPR downstream processing is unaddressed. Piping transcripts to OpenAI/Gemini introduces new data processors. Customers need to acknowledge responsibility for downstream processing during setup. We should also consider whether call participants' recording consent covers onward sharing to third-party AI - it almost certainly doesn't by default. This is one for me to pick up.","depth":23,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"Key lifecycle management is missing. No mention of rotation, expiry, or revocation. A departed employee's active key is a data leak. Need: revocation, optional expiry, alerts on stale keys, and consider whether keys should be tied to service accounts rather than personal users.","depth":23,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"Rate limiting should be HIGH. A compromised key or misconfigured automation could bulk-export an entire customer's call history. Need per-key rate limits and anomaly detection on unusual access patterns.","depth":23,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"Audit logs should go deeper. Current spec (what data, which system, when) is a start. Add: identity behind the key, specific queries/filters used, and failed access attempts (especially cross-visibility-boundary attempts). Enterprise compliance teams will expect this.","depth":23,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"Downgrade handling. Doc says Scale tier and above, but doesn't say what happens on downgrade. Keys should auto-deactivate.","depth":23,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"Happy to help draft a dedicated Security & Compliance section if useful.","depth":23,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"Galya Dimitrova","depth":23,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"15 Apr","depth":23,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"Thanks for the input @James Graham . I made the product related changes in the table and for the rest I left them as a note in the Technical section for the team to look at when they start looking at this.","depth":23,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"I wonder about your points related to GDPR. Currently multiple customers are using the Customer API/zapier to feed this data to AI and BI tools. They are also manually exporting transcripts and other information from the platform and feeding it to AI tools. I don’t get how MCP is so much different that all of these and why it will introduce new data processors (which are already being utilised) and would require any changes to the consent provided by participants.","depth":23,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXButton","text":"Expand","depth":21,"bounds":{"left":0.46991357,"top":0.19313647,"width":0.013297873,"height":0.031923383},"role_description":"button","subrole":"AXUnknown","is_enabled":true,"is_focused":false,"is_selected":false},{"role":"AXButton","text":"Listen","depth":22,"bounds":{"left":0.47523272,"top":0.3367917,"width":0.013297873,"height":0.031923383},"help_text":"","role_description":"button","subrole":"AXUnknown","is_enabled":true,"is_focused":false,"is_selected":false}]...
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Platform Sprint 2 Q2 - Platform Team - Scrum Board Platform Sprint 2 Q2 - Platform Team - Scrum Board - Jira
SevenShores\Hubspot\Exceptions\BadRequest: Client error: `POST [URL_WITH_CREDENTIALS] Graham . I made the product related changes in the table and for the rest I left them as a note in the Technical section for the team to look at when they start looking at this. I wonder about your points related to GDPR. Currently multiple customers are using the Customer API/zapier to feed this data to AI and BI tools. They are also manually exporting transcripts and other information from the platform and feeding it to AI tools. I don’t get how MCP is so much different that all of these and why it will introduce new data processors (which are already being utilised) and would require any changes to the consent provided by participants.
You said
Jiminny MCP Connector
Epic
Link to Epik in Jira
Document status
DRAFT
Objective
Enable customers to connect Jiminny data to external AI tools (Claude, OpenAI, Gemini) so it can be used as part of their broader knowledge base and workflows.
Position Jiminny as a data layer for AI-driven revenue workflows, not just a standalone product.
👤 Target user
Revenue teams using AI tools (Sales, CS, RevOps)
Companies already experimenting with Claude / OpenAI
Mid-market & Enterprise customers with multiple data sources (CRM, docs, CI tools, Support tools etc)
🤕 Pain point or problem
Jiminny data is locked in the platform
AI tools lack access to high-value conversation context
Customers must manually export/copy transcripts
No easy way to combine calls with CRM + docs + other info - using the Jiminny API is not suitable for non technical sales people
Peer pressure as almost all competitors have this
💥 Impact and benefits
For customers
Better AI outputs using real customer conversations
Ability to build automated workflows across tools
For Jiminny
Increased product stickiness (embedded in workflows)
Competitive parity with Gong / Avoma etc.
💡 Solution ideas
Build an AI Knowledge Connector (MCP-based) that:
Exposes Jiminny data (calls, transcripts, metadata) to AI tools
Provides structured insights (summaries, action items, scoring etc.)
Supports deal-level context
Allows integration into customer-owned AI stacks (Claude + Zapier, etc.)
Success metrics
List the key goals and how you will measure success. Include both qualitative and quantitative metrics (e.g., user adoption, retention rate, revenue targets).
Goal
Metric
Increase stickiness by ensuring Jiminny is embedded in the customer’s workflows
% of customers connecting external AI tools
Number of MCP/API calls per customer - and which ones are being used the most
Decrease the manual copying of transcripts
decrease by X %
User interaction and design
Simple setup flow:
Generate API key / connect MCP
Clear instructions for Claude / Zapier setup
Provide:
Example prompts for Claude
Pre-built workflow templates for Zapier
Clear documentation - with use cases
👉 Focus: usable by non-technical users
Detailed Requirements
List the functional and non-functional requirements. Prioritize them (e.g., High, Medium, Low) and add notes for clarification.
Requirement
Importance
Notes
Allow customers to connect Jiminny to their AI tools (e.g. Claude, OpenAI)
HIGH
Provide MCP endpoint so customers can easily integrate Jiminny into their AI stack
Allow customers to access call data through AI tools
HIGH
Expose Jiminny data:
list calls (filter by date, user, account, deal)
get call
get transcript (speaker-separated)
get call metadata
search calls (keyword + semantic)
Support filtering by:
account / contact/ lead / deal
jiminny user
date range
Allow customers to search and query calls using AI tools
HIGH
Support keyword and semantic search across conversations
Provide structured insights so customers can generate better outputs
HIGH
For each call, expose:
Summary
Action items
Key points
Activity type
Notes
Call Score
CRM information
Allow customers to understand deal status across multiple calls/emails
HIGH
For each deal expose:
calls/meetings/emails
Identified risks
contacts related to the deal with their job title
linked account details
all CRM field information that we have in DI + fields used for CRM filling
example - get_deal_summary
request -
{
"tool": "get_deal_summary",
"arguments": {
"deal_name": "ACME"
}
}
responce:
{
"deal_name": "ACME",
"stage": "Negotiation",
"recent_activity": [
"Demo call on 2026-04-01",
"Pricing discussion on 2026-04-03"
],
"risks": [
"Pricing concerns",
"Security review pending"
], "next_steps": [
"Send follow-up to VP Sales",
"Share security documentation"
]
}
Ensure the AI can easily understand the schema of the data coming from Jiminny
HIGH
Models perform much better when tools have:
clear names
rich descriptions
predictable schemas
Provide clear, actionable error states for customers when MCP connections fail
HIGH
Error messages should guide agents toward solutions with specific suggestions and next steps.
Expired or revoked key — “Error: Authentication failed. The API key used to access Jiminny has been revoked or has expired. Please ask your Jiminny admin to generate a new API key in Settings > Organization > General and reconnect the MCP server.”
Rate limit hit — “Error: Rate limit exceeded. Too many requests have been made to the Jiminny MCP server in a short period. Please wait 60 seconds before retrying.”
Permissions mismatch — if a user tries to access data outside their team visibility settings - “Error: Access denied. The requested call (call_id: [X]) is outside your team's visibility settings in Jiminny. Only calls within your permitted scope are accessible.”
Trying to access private meeting - “Error: Access denied. This meeting has been marked as private by the host and cannot be accessed through the MCP connector. Try requesting a different call or ask the meeting host to change the visibility settings in Jiminny.”
Downgraded/Capture account — if a customer's plan drops below Scale tier or the Customer is on Capture in the first place - “Error: MCP access unavailable. The Jiminny MCP connector is available on the Scale plan and above. Your account does not currently have an active Scale subscription.”
Jiminny-side outage — “Error:Jiminny is temporarily unavailable (status 503). This is not a data or permissions issue — please retry in a few minutes.”
No data found - “Error:No calls found matching your criteria. Try adjusting your filters — for example, widening the date range, removing the account filter, or checking the rep name is spelled correctly in Jiminny.”
Allow customers to securely control who and what data is accessible externally
HIGH
Ensure MCP only exposes data user has access to - based on team visibility settings. This means that if a user is not allow to access calls/deals in Jiminny UI then they shouldn’t be able to access those through the MCP as well.
Private meetings shouldn’t be exposed via MCP
HIGH
When a meetings is set to Private then the information about it shouldn’t be exposed through the MCP.
Ensure Jiminny data can be combined with other sources (e.g. CRM, docs) in AI workflows
HIGH
Ensure data is structured to be easily combined with:
CRM (accounts, deals)
external docs
Use consistent identifiers:
account IDs
deal IDs
MCP is available only for Scale tier and above
HIGH
Customers who are on Capture tier should be able to access any of their data through MCP.
This should also cover the scenario when a customer has been on Scale but then downgrades to Capture - their MCP access should stop working.
Provide visibility into how external AI tools access Jiminny data
HIGH
Audit logs:
what data was accessed by which external system when
identity - who made the request
specific queries/filters used
failed access attempts (especially cross-visibility-boundary attempts)
Admins should be able to access the logs from the org settings.We can start with a csv export before building a specific page for it.
example from Atlassian -
Provide customers with example prompts to get started quickly
HIGH
MCP prompts are explicitly defined as prompt templates that clients can discover and call with arguments.
See examples in table below.
Expose Jiminny as a Connector in Claude
medium
Competitors like Fathom are listed as Connectors in Claude. This will make it easier for customers to find us and to connect Jiminny
Provide customers with example workflows to get started quickly
medium
A workflow is usually multiple steps, maybe multiple tools, still focused on one outcome.
See examples in table below.
Allow customers to use predefined Jiminny skills for common workflows
medium
Anthropic describes Skills as folders that include instructions, scripts, and resources that Claude can load when relevant, and as a way to teach Claude repeatable workflows, preferences, and domain expertise once instead of re-explaining them every time. Skills - a reusable package of behavior that can include prompts, instructions, resources, and sometimes scripts/tools for a broader job.
Claude skills - https://resources.anthropic.com/hubfs/The-Complete-Guide-to-Building-Skill-for-Claude.pdf?hsLang=en&utm_source=chatgpt.com
See examples in table below.
Jiminny UI widget for OpenAI
medium
The reason to have this is to make certain Jiminny use cases much easier than pure chat.
Instead of ChatGPT only replying with text like “Here are the last 5 ACME calls,” it could also show a visual Jiminny card or mini-app inside the chat. That widget could list calls, show a deal summary, let the user filter by rep/date/account, open a transcript section, or save a snippet—while the conversation continues in normal chat alongside it.
For Jiminny, the best widget use cases are the ones where users need to browse or compare rather than ask one-off questions. A strong example is deal review: the user asks ChatGPT, “What is the status of the ACME deal?” ChatGPT calls your Jiminny MCP tools, and the widget shows a compact deal view with recent calls, risks, next steps, stakeholders, and links to transcripts/snippets. The chat can still summarize the answer in words, but the widget gives a clearer, scannable interface.
Another good Jiminny widget use case is call search and exploration. A text answer can say “I found 12 calls mentioning pricing objections,” but a widget could show a sortable list with date, rep, account, score, and objection count, then let the user click into one call to see the exact excerpt or jump to a transcript section.
Allow customers to run long-running analyses asynchronously and retrieve progress/results
low
Some requests/questions require analysis of Hugh volumes of data. For those, it may be better to:
start the job
let it run in the background
return a status like “in progress”
let the client come back for the result later
For example - User asks in Claude:
“Analyse all calls from this quarter and tell me the top 5 objections by segment.”
That might require:
searching lots of calls
pulling many summaries/transcripts
aggregating results
Instead of making Claude wait 45+ seconds, Jiminny could:
create an analysis job
return: job_id = 123, status = running
We need this in order to support:
large-scale analysis
multi-call aggregation across lots of data
playlist generation across many calls
heavy recap/report generation
Creating a snippet through the MCP
low
Create a shareable snippet from a call recording by specifying a time range. Useful for highlighting key moments — objection handling, pricing discussions, competitive mentions — and sharing them with your team.
example request:
{
"tool": "create_snippet",
"arguments": {
"call_id": "call_123",
"start_time": "00:18:24",
"end_time": "00:19:10",
"title": "Pricing objection"
}
}
example response:
{
"snippet_id": "snip_987",
"title": "Pricing objection",
"share_url": "https://app.jiminny.com/snippets/snip_987"
}
Ability to add recordings or snippets to a playlist
low
Allow customers to create libraries of calls automatically. They can use those for onboarding or other purposes
Allow AI tools to read reusable Jiminny resources
low
fathom
Resources are useful for data that should be read consistently rather than recomputed every time. In Jiminny terms, that could be:
current deal snapshot
account summary
weekly rep recap
approved talk tracks / objection handling guidance
curated playlists or snippet libraries
This is useful because an AI can consume these directly as context, instead of repeatedly stitching together many tool calls.
Ability to write coaching notes in Jiminny through MCP
low
What we want to do for prompts/worflows and skills
Capability
Type
User value / job to be done
Example Jiminny use case
Inputs
Steps performed
Output
Draft follow-up email
Prompt
Help reps quickly create tailored follow-ups after calls
Use the latest customer call to draft an email with recap and next steps
Call ID
optional tone
optional recipient type
Retrieve call summary and action items from Jiminny.
Pull key points, commitments, and next steps.
Apply the chosen tone and structure.
Draft the email in a consistent format.
Customer-ready follow-up email draft
Summarise call
Prompt
Help users quickly extract the most important points from a conversation
Generate a concise summary of one call for internal or external use
Call ID
optional summary style
optional audience
Retrieve transcript, metadata, and structured insights.
Identify key topics, decisions, risks, and next steps.
Format output for the chosen audience.
Short or structured call summary with actions and risks
Generate deal recap
Prompt
Help reps and managers get a fast overview of a deal
Summarise the current state of a deal based on recent calls and linked CRM context
Deal ID or account name
optional date range
Retrieve calls and meetings linked to the deal.
Pull deal metadata and CRM-linked context.
Identify recent changes, blockers, risks, and next steps.
Summarise into a concise recap.
Deal recap with status, blockers, risks, and recommended next steps
Prepare weekly recap
Prompt
Help managers or reps review what changed over a time period
Weekly recap of calls, themes, and actions for one rep, team, or account
Rep ID
team ID or account ID
time period
Retrieve relevant calls and summaries for the selected time period.
Aggregate themes, action items, and changes.
Highlight notable risks, opportunities, and follow-ups.
Weekly recap with top themes, risks, opportunities, and actions
Prepare deal review
Workflow
Help reps and managers review deal status using multiple sources of context
Review a deal before pipeline review or forecast meeting
Deal ID
optional date range
Retrieve all recent calls, emails, and meetings tied to the deal.
Pull structured call summaries, score, action items, and key points.
Pull linked CRM context such as stage, contacts, and account details.
Aggregate open risks, unresolved objections, stakeholder gaps, and next steps.
Format into a review-ready structure.
Deal review document with current status, risks, stakeholders, blockers, and next steps
Weekly team recap
Workflow
Help managers monitor activity and risk across a group of reps or accounts
End-of-week team summary for sales leadership
Team ID
date range
Retrieve calls and structured insights across the team.
Group by rep, account, or deal.
Identify recurring themes, major risks, strong calls, and missed follow-ups.
Highlight calls or deals that need attention.
Team-level recap with patterns, key risks, notable wins, and action areas
Objection analysis across calls
Workflow
Help teams identify patterns across multiple conversations
Analyse pricing or competitor objections across recent calls
Account ID
deal ID
rep ID
keyword/topic
date range
Search calls matching the topic or keyword.
Retrieve summaries, transcripts, and snippets where relevant.
Identify recurring objections and how they were handled.
Assess whether objections were resolved or remain open.
Summarise patterns and examples.
Objection analysis with themes, frequency, examples, and suggested follow-up actions
Build onboarding playlist
Workflow
Help enablement teams curate useful learning content faster
Build a playlist of strong discovery, demo, or pricing calls for new hires
Topic
call type
rep/team filter
optional time period
Search for calls matching the selected criteria.
Rank or filter calls based on score, topics, or key moments.
Identify useful snippets or full recordings.
Add selected calls/snippets into a playlist structure.
Generate short descriptions for each item.
Curated onboarding playlist with selected calls/snippets and descriptions
Deal Inspection Skill
Skill
Give users a consistent, opinionated way to assess a deal
Claude reviews a deal using a repeatable Jiminny methodology
Deal ID or account name
optional review scope
Determine whether the request is suitable for a deal inspection.
Retrieve relevant calls, summaries, CRM context, stakeholders, and risks.
Apply a standard Jiminny review framework to assess deal health.
Look for missing next steps, unresolved objections, stakeholder gaps, and warning signs.
Present findings in a consistent structure with recommended actions.
Structured deal inspection with health assessment, red flags, and recommendations
Manager Coaching Skill
Skill
Help managers review calls consistently and identify coaching moments
Analyse a rep’s call and surface strengths, gaps, and examples for coaching
Call ID
optional rep ID
optional coaching focus
Retrieve transcript, score, summary, and key moments from the call.
Evaluate the conversation against a coaching framework.
Identify what went well and where the rep could improve.
Suggest moments to clip as snippets.
Recommend coaching actions or playlist additions.
Coaching review with strengths, gaps, snippet suggestions, and recommended coaching actions
CSM / QBR Prep Skill
Skill
Help CS or AM teams prepare structured customer reviews from conversations
Generate an account review or QBR-style summary from recent customer interactions
Account ID, optional time period
Retrieve all recent calls, emails, and account-linked context.
Aggregate themes, requests, blockers, sentiment shifts, and opportunities.
Apply a repeatable account review structure.
Summarise outcomes, open issues, and suggested next steps.
Structured QBR/account review summary with themes, risks, opportunities, and actions
Snippet Builder Skill
Skill
Help users consistently capture and label useful moments from calls
Identify useful moments in a call and convert them into reusable snippets
Call ID, optional focus area such as pricing, objection, competitor, discovery
Retrieve transcript, recording timeline, and call insights.
Detect moments matching the requested focus area.
Propose snippet start/end times and titles.
Tag snippets by type or theme.
Optionally save them or add them to a playlist.
One or more proposed or saved snippets with title, timing, and tags
💡 Technical details
Auth model needs specifying. Are API keys scoped per user, per team, or per Jiminny instance? If a key is generated by an admin, does it inherit their visibility level, or provide org-wide? Are permissions evaluated at query time or frozen at key creation? Needs to be query-time, otherwise permission changes won't propagate.
Key lifecycle management is missing. No mention of rotation, expiry, or revocation. A departed employee's active key is a data leak. Need: revocation, optional expiry, alerts on stale keys, and consider whether keys should be tied to service accounts rather than personal users.
Rate limiting should be HIGH. A compromised key or misconfigured automation could bulk-export an entire customer's call history. Need per-key rate limits and anomaly detection on unusual access patterns.
Open Questions
Track unresolved issues or decisions that need to be made. Update as answers become available.
Question
Answer
Date Answered
Competitor research
Competitor
MCP Availability
Core Capabilities
Advanced Capabilities
Positioning
Key Strength
Key Weakness
Gong
✅ Mature MCP
List/search calls
Get transcripts
get Call metadata
Deal intelligence
Scorecards, analytics
CRM context
Enterprise data layer
Deep data + ecosystem integrations
Limited opinionated AI workflows
Avoma
✅ Mature MCP
list_meetings
get_meeting
get_transcript
key topics
Deal fields/Deal level analysis
Coaching/Scoring
CRM context
pushing insights into Notion / Confluence
AI-ready meeting intelligence
Strongest “outputs” layer
Mostly pull-based interactions
Fathom
✅ MCP
list/search meetings
get transcript
get summary/action items
Team/org context
Webhooks (event-based triggers)
get_weekly_recap
aggregated action items across meetings
creating webhooks directly from the MCP server
Lightweight meeting data access
Includes summaries + actions
Limited analytics depth
Grain
✅ Basic MCP
get meetings
download transcripts
Notes
Deals
Scorecards
Data access utility
Simple + accessible
Low sophistication, sometimes browser-based
Outreach
⚠️ MCP (workflow-focused)
Search sequences
Emails
Meetings (Kaia)
account / prospect / opportunity lookups
Workflow automation
Multi-system orchestration
Revenue workflow engine
End-to-end GTM workflows
Less depth in conversation data
Attention
⚠️ Emerging MCP
Meeting data
Transcripts
CRM-linked context
AI insights
Sales assistant workflows
create snippets
AI sales assistant + CRM
Strong CRM linkage
Less focus on external knowledge layer
Planhat -
Related content
Ask Jiminny Anything on Call level
Galya Dimitrova
Hubspot app
Galya Dimitrova
Product Vision & Strategy
Galya Dimitrova
Automated CRM Filling
Simona Georgieva (Deactivated)
Competitive analysis
Galya Dimitrova
AI agent ideas
Steliyan Georgiev
Comments
James Graham
9 Apr
A few areas around Security & Compliance that need more depth before this moves beyond draft:
Auth model needs specifying. Are API keys scoped per user, per team, or per Jiminny instance? If a key is generated by an admin, does it inherit their visibility level, or provide org-wide? Are permissions evaluated at query time or frozen at key creation? Needs to be query-time, otherwise permission changes won't propagate.
Team visibility enforcement should be its own HIGH requirement. The current note under access control ("ensure MCP only exposes data user has access to") is doing too much work as a single line. Every MCP tool response (especially search_calls and deal-level aggregations) must be filtered through the same visibility engine as the UI. Semantic search is the riskiest here; it could surface results across team boundaries if not properly scoped.
No data minimisation or scoping controls. We're exposing transcripts, CRM fields, contact details with job titles, deal context - significant PII and commercial data leaving the platform. Can customers configure which data types are exposed? Can transcripts be PII-stripped before they leave Jiminny? Given we position GDPR consent as a differentiator, we should be thinking about this.
GDPR downstream processing is unaddressed. Piping transcripts to OpenAI/Gemini introduces new data processors. Customers need to acknowledge responsibility for downstream processing during setup. We should also consider whether call participants' recording consent covers onward sharing to third-party AI - it almost certainly doesn't by default. This is one for me to pick up.
Key lifecycle management is missing. No mention of rotation, expiry, or revocation. A departed employee's active key is a data leak. Need: revocation, optional expiry, alerts on stale keys, and consider whether keys should be tied to service accounts rather than personal users.
Rate limiting should be HIGH. A compromised key or misconfigured automation could bulk-export an entire customer's call history. Need per-key rate limits and anomaly detection on unusual ac...
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Platform Sprint 2 Q2 - Platform Team - Scrum Board Platform Sprint 2 Q2 - Platform Team - Scrum Board - Jira
SevenShores\Hubspot\Exceptions\BadRequest: Client error: `POST [URL_WITH_CREDENTIALS] Graham . I made the product related changes in the table and for the rest I left them as a note in the Technical section for the team to look at when they start looking at this. I wonder about your points related to GDPR. Currently multiple customers are using the Customer API/zapier to feed this data to AI and BI tools. They are also manually exporting transcripts and other information from the platform and feeding it to AI tools. I don’t get how MCP is so much different that all of these and why it will introduce new data processors (which are already being utilised) and would require any changes to the consent provided by participants.
You said
Jiminny MCP Connector
Epic
Link to Epik in Jira
Document status
DRAFT
Objective
Enable customers to connect Jiminny data to external AI tools (Claude, OpenAI, Gemini) so it can be used as part of their broader knowledge base and workflows.
Position Jiminny as a data layer for AI-driven revenue workflows, not just a standalone product.
👤 Target user
Revenue teams using AI tools (Sales, CS, RevOps)
Companies already experimenting with Claude / OpenAI
Mid-market & Enterprise customers with multiple data sources (CRM, docs, CI tools, Support tools etc)
🤕 Pain point or problem
Jiminny data is locked in the platform
AI tools lack access to high-value conversation context
Customers must manually export/copy transcripts
No easy way to combine calls with CRM + docs + other info - using the Jiminny API is not suitable for non technical sales people
Peer pressure as almost all competitors have this
💥 Impact and benefits
For customers
Better AI outputs using real customer conversations
Ability to build automated workflows across tools
For Jiminny
Increased product stickiness (embedded in workflows)
Competitive parity with Gong / Avoma etc.
💡 Solution ideas
Build an AI Knowledge Connector (MCP-based) that:
Exposes Jiminny data (calls, transcripts, metadata) to AI tools
Provides structured insights (summaries, action items, scoring etc.)
Supports deal-level context
Allows integration into customer-owned AI stacks (Claude + Zapier, etc.)
Success metrics
List the key goals and how you will measure success. Include both qualitative and quantitative metrics (e.g., user adoption, retention rate, revenue targets).
Goal
Metric
Increase stickiness by ensuring Jiminny is embedded in the customer’s workflows
% of customers connecting external AI tools
Number of MCP/API calls per customer - and which ones are being used the most
Decrease the manual copying of transcripts
decrease by X %
User interaction and design
Simple setup flow:
Generate API key / connect MCP
Clear instructions for Claude / Zapier setup
Provide:
Example prompts for Claude
Pre-built workflow templates for Zapier
Clear documentation - with use cases
👉 Focus: usable by non-technical users
Detailed Requirements
List the functional and non-functional requirements. Prioritize them (e.g., High, Medium, Low) and add notes for clarification.
Requirement
Importance
Notes
Allow customers to connect Jiminny to their AI tools (e.g. Claude, OpenAI)
HIGH
Provide MCP endpoint so customers can easily integrate Jiminny into their AI stack
Allow customers to access call data through AI tools
HIGH
Expose Jiminny data:
list calls (filter by date, user, account, deal)
get call
get transcript (speaker-separated)
get call metadata
search calls (keyword + semantic)
Support filtering by:
account / contact/ lead / deal
jiminny user
date range
Allow customers to search and query calls using AI tools
HIGH
Support keyword and semantic search across conversations
Provide structured insights so customers can generate better outputs
HIGH
For each call, expose:
Summary
Action items
Key points
Activity type
Notes
Call Score
CRM information
Allow customers to understand deal status across multiple calls/emails
HIGH
For each deal expose:
calls/meetings/emails
Identified risks
contacts related to the deal with their job title
linked account details
all CRM field information that we have in DI + fields used for CRM filling
example - get_deal_summary
request -
{
"tool": "get_deal_summary",
"arguments": {
"deal_name": "ACME"
}
}
responce:
{
"deal_name": "ACME",
"stage": "Negotiation",
"recent_activity": [
"Demo call on 2026-04-01",
"Pricing discussion on 2026-04-03"
],
"risks": [
"Pricing concerns",
"Security review pending"
], "next_steps": [
"Send follow-up to VP Sales",
"Share security documentation"
]
}
Ensure the AI can easily understand the schema of the data coming from Jiminny
HIGH
Models perform much better when tools have:
clear names
rich descriptions
predictable schemas
Provide clear, actionable error states for customers when MCP connections fail
HIGH
Error messages should guide agents toward solutions with specific suggestions and next steps.
Expired or revoked key — “Error: Authentication failed. The API key used to access Jiminny has been revoked or has expired. Please ask your Jiminny admin to generate a new API key in Settings > Organization > General and reconnect the MCP server.”
Rate limit hit — “Error: Rate limit exceeded. Too many requests have been made to the Jiminny MCP server in a short period. Please wait 60 seconds before retrying.”
Permissions mismatch — if a user tries to access data outside their team visibility settings - “Error: Access denied. The requested call (call_id: [X]) is outside your team's visibility settings in Jiminny. Only calls within your permitted scope are accessible.”
Trying to access private meeting - “Error: Access denied. This meeting has been marked as private by the host and cannot be accessed through the MCP connector. Try requesting a different call or ask the meeting host to change the visibility settings in Jiminny.”
Downgraded/Capture account — if a customer's plan drops below Scale tier or the Customer is on Capture in the first place - “Error: MCP access unavailable. The Jiminny MCP connector is available on the Scale plan and above. Your account does not currently have an active Scale subscription.”
Jiminny-side outage — “Error:Jiminny is temporarily unavailable (status 503). This is not a data or permissions issue — please retry in a few minutes.”
No data found - “Error:No calls found matching your criteria. Try adjusting your filters — for example, widening the date range, removing the account filter, or checking the rep name is spelled correctly in Jiminny.”
Allow customers to securely control who and what data is accessible externally
HIGH
Ensure MCP only exposes data user has access to - based on team visibility settings. This means that if a user is not allow to access calls/deals in Jiminny UI then they shouldn’t be able to access those through the MCP as well.
Private meetings shouldn’t be exposed via MCP
HIGH
When a meetings is set to Private then the information about it shouldn’t be exposed through the MCP.
Ensure Jiminny data can be combined with other sources (e.g. CRM, docs) in AI workflows
HIGH
Ensure data is structured to be easily combined with:
CRM (accounts, deals)
external docs
Use consistent identifiers:
account IDs
deal IDs
MCP is available only for Scale tier and above
HIGH
Customers who are on Capture tier should be able to access any of their data through MCP.
This should also cover the scenario when a customer has been on Scale but then downgrades to Capture - their MCP access should stop working.
Provide visibility into how external AI tools access Jiminny data
HIGH
Audit logs:
what data was accessed by which external system when
identity - who made the request
specific queries/filters used
failed access attempts (especially cross-visibility-boundary attempts)
Admins should be able to access the logs from the org settings.We can start with a csv export before building a specific page for it.
example from Atlassian -
Provide customers with example prompts to get started quickly
HIGH
MCP prompts are explicitly defined as prompt templates that clients can discover and call with arguments.
See examples in table below.
Expose Jiminny as a Connector in Claude
medium
Competitors like Fathom are listed as Connectors in Claude. This will make it easier for customers to find us and to connect Jiminny
Provide customers with example workflows to get started quickly
medium
A workflow is usually multiple steps, maybe multiple tools, still focused on one outcome.
See examples in table below.
Allow customers to use predefined Jiminny skills for common workflows
medium
Anthropic describes Skills as folders that include instructions, scripts, and resources that Claude can load when relevant, and as a way to teach Claude repeatable workflows, preferences, and domain expertise once instead of re-explaining them every time. Skills - a reusable package of behavior that can include prompts, instructions, resources, and sometimes scripts/tools for a broader job.
Claude skills - https://resources.anthropic.com/hubfs/The-Complete-Guide-to-Building-Skill-for-Claude.pdf?hsLang=en&utm_source=chatgpt.com
See examples in table below.
Jiminny UI widget for OpenAI
medium
The reason to have this is to make certain Jiminny use cases much easier than pure chat.
Instead of ChatGPT only replying with text like “Here are the last 5 ACME calls,” it could also show a visual Jiminny card or mini-app inside the chat. That widget could list calls, show a deal summary, let the user filter by rep/date/account, open a transcript section, or save a snippet—while the conversation continues in normal chat alongside it.
For Jiminny, the best widget use cases are the ones where users need to browse or compare rather than ask one-off questions. A strong example is deal review: the user asks ChatGPT, “What is the status of the ACME deal?” ChatGPT calls your Jiminny MCP tools, and the widget shows a compact deal view with recent calls, risks, next steps, stakeholders, and links to transcripts/snippets. The chat can still summarize the answer in words, but the widget gives a clearer, scannable interface.
Another good Jiminny widget use case is call search and exploration. A text answer can say “I found 12 calls mentioning pricing objections,” but a widget could show a sortable list with date, rep, account, score, and objection count, then let the user click into one call to see the exact excerpt or jump to a transcript section.
Allow customers to run long-running analyses asynchronously and retrieve progress/results
low
Some requests/questions require analysis of Hugh volumes of data. For those, it may be better to:
start the job
let it run in the background
return a status like “in progress”
let the client come back for the result later
For example - User asks in Claude:
“Analyse all calls from this quarter and tell me the top 5 objections by segment.”
That might require:
searching lots of calls
pulling many summaries/transcripts
aggregating results
Instead of making Claude wait 45+ seconds, Jiminny could:
create an analysis job
return: job_id = 123, status = running
We need this in order to support:
large-scale analysis
multi-call aggregation across lots of data
playlist generation across many calls
heavy recap/report generation
Creating a snippet through the MCP
low
Create a shareable snippet from a call recording by specifying a time range. Useful for highlighting key moments — objection handling, pricing discussions, competitive mentions — and sharing them with your team.
example request:
{
"tool": "create_snippet",
"arguments": {
"call_id": "call_123",
"start_time": "00:18:24",
"end_time": "00:19:10",
"title": "Pricing objection"
}
}
example response:
{
"snippet_id": "snip_987",
"title": "Pricing objection",
"share_url": "https://app.jiminny.com/snippets/snip_987"
}
Ability to add recordings or snippets to a playlist
low
Allow customers to create libraries of calls automatically. They can use those for onboarding or other purposes
Allow AI tools to read reusable Jiminny resources
low
fathom
Resources are useful for data that should be read consistently rather than recomputed every time. In Jiminny terms, that could be:
current deal snapshot
account summary
weekly rep recap
approved talk tracks / objection handling guidance
curated playlists or snippet libraries
This is useful because an AI can consume these directly as context, instead of repeatedly stitching together many tool calls.
Ability to write coaching notes in Jiminny through MCP
low
What we want to do for prompts/worflows and skills
Capability
Type
User value / job to be done
Example Jiminny use case
Inputs
Steps performed
Output
Draft follow-up email
Prompt
Help reps quickly create tailored follow-ups after calls
Use the latest customer call to draft an email with recap and next steps
Call ID
optional tone
optional recipient type
Retrieve call summary and action items from Jiminny.
Pull key points, commitments, and next steps.
Apply the chosen tone and structure.
Draft the email in a consistent format.
Customer-ready follow-up email draft
Summarise call
Prompt
Help users quickly extract the most important points from a conversation
Generate a concise summary of one call for internal or external use
Call ID
optional summary style
optional audience
Retrieve transcript, metadata, and structured insights.
Identify key topics, decisions, risks, and next steps.
Format output for the chosen audience.
Short or structured call summary with actions and risks
Generate deal recap
Prompt
Help reps and managers get a fast overview of a deal
Summarise the current state of a deal based on recent calls and linked CRM context
Deal ID or account name
optional date range
Retrieve calls and meetings linked to the deal.
Pull deal metadata and CRM-linked context.
Identify recent changes, blockers, risks, and next steps.
Summarise into a concise recap.
Deal recap with status, blockers, risks, and recommended next steps
Prepare weekly recap
Prompt
Help managers or reps review what changed over a time period
Weekly recap of calls, themes, and actions for one rep, team, or account
Rep ID
team ID or account ID
time period
Retrieve relevant calls and summaries for the selected time period.
Aggregate themes, action items, and changes.
Highlight notable risks, opportunities, and follow-ups.
Weekly recap with top themes, risks, opportunities, and actions
Prepare deal review
Workflow
Help reps and managers review deal status using multiple sources of context
Review a deal before pipeline review or forecast meeting
Deal ID
optional date range
Retrieve all recent calls, emails, and meetings tied to the deal.
Pull structured call summaries, score, action items, and key points.
Pull linked CRM context such as stage, contacts, and account details.
Aggregate open risks, unresolved objections, stakeholder gaps, and next steps.
Format into a review-ready structure.
Deal review document with current status, risks, stakeholders, blockers, and next steps
Weekly team recap
Workflow
Help managers monitor activity and risk across a group of reps or accounts
End-of-week team summary for sales leadership
Team ID
date range
Retrieve calls and structured insights across the team.
Group by rep, account, or deal.
Identify recurring themes, major risks, strong calls, and missed follow-ups.
Highlight calls or deals that need attention.
Team-level recap with patterns, key risks, notable wins, and action areas
Objection analysis across calls
Workflow
Help teams identify patterns across multiple conversations
Analyse pricing or competitor objections across recent calls
Account ID
deal ID
rep ID
keyword/topic
date range
Search calls matching the topic or keyword.
Retrieve summaries, transcripts, and snippets where relevant.
Identify recurring objections and how they were handled.
Assess whether objections were resolved or remain open.
Summarise patterns and examples.
Objection analysis with themes, frequency, examples, and suggested follow-up actions
Build onboarding playlist
Workflow
Help enablement teams curate useful learning content faster
Build a playlist of strong discovery, demo, or pricing calls for new hires
Topic
call type
rep/team filter
optional time period
Search for calls matching the selected criteria.
Rank or filter calls based on score, topics, or key moments.
Identify useful snippets or full recordings.
Add selected calls/snippets into a playlist structure.
Generate short descriptions for each item.
Curated onboarding playlist with selected calls/snippets and descriptions
Deal Inspection Skill
Skill
Give users a consistent, opinionated way to assess a deal
Claude reviews a deal using a repeatable Jiminny methodology
Deal ID or account name
optional review scope
Determine whether the request is suitable for a deal inspection.
Retrieve relevant calls, summaries, CRM context, stakeholders, and risks.
Apply a standard Jiminny review framework to assess deal health.
Look for missing next steps, unresolved objections, stakeholder gaps, and warning signs.
Present findings in a consistent structure with recommended actions.
Structured deal inspection with health assessment, red flags, and recommendations
Manager Coaching Skill
Skill
Help managers review calls consistently and identify coaching moments
Analyse a rep’s call and surface strengths, gaps, and examples for coaching
Call ID
optional rep ID
optional coaching focus
Retrieve transcript, score, summary, and key moments from the call.
Evaluate the conversation against a coaching framework.
Identify what went well and where the rep could improve.
Suggest moments to clip as snippets.
Recommend coaching actions or playlist additions.
Coaching review with strengths, gaps, snippet suggestions, and recommended coaching actions
CSM / QBR Prep Skill
Skill
Help CS or AM teams prepare structured customer reviews from conversations
Generate an account review or QBR-style summary from recent customer interactions
Account ID, optional time period
Retrieve all recent calls, emails, and account-linked context.
Aggregate themes, requests, blockers, sentiment shifts, and opportunities.
Apply a repeatable account review structure.
Summarise outcomes, open issues, and suggested next steps.
Structured QBR/account review summary with themes, risks, opportunities, and actions
Snippet Builder Skill
Skill
Help users consistently capture and label useful moments from calls
Identify useful moments in a call and convert them into reusable snippets
Call ID, optional focus area such as pricing, objection, competitor, discovery
Retrieve transcript, recording timeline, and call insights.
Detect moments matching the requested focus area.
Propose snippet start/end times and titles.
Tag snippets by type or theme.
Optionally save them or add them to a playlist.
One or more proposed or saved snippets with title, timing, and tags
💡 Technical details
Auth model needs specifying. Are API keys scoped per user, per team, or per Jiminny instance? If a key is generated by an admin, does it inherit their visibility level, or provide org-wide? Are permissions evaluated at query time or frozen at key creation? Needs to be query-time, otherwise permission changes won't propagate.
Key lifecycle management is missing. No mention of rotation, expiry, or revocation. A departed employee's active key is a data leak. Need: revocation, optional expiry, alerts on stale keys, and consider whether keys should be tied to service accounts rather than personal users.
Rate limiting should be HIGH. A compromised key or misconfigured automation could bulk-export an entire customer's call history. Need per-key rate limits and anomaly detection on unusual access patterns.
Open Questions
Track unresolved issues or decisions that need to be made. Update as answers become available.
Question
Answer
Date Answered
Competitor research
Competitor
MCP Availability
Core Capabilities
Advanced Capabilities
Positioning
Key Strength
Key Weakness
Gong
✅ Mature MCP
List/search calls
Get transcripts
get Call metadata
Deal intelligence
Scorecards, analytics
CRM context
Enterprise data layer
Deep data + ecosystem integrations
Limited opinionated AI workflows
Avoma
✅ Mature MCP
list_meetings
get_meeting
get_transcript
key topics
Deal fields/Deal level analysis
Coaching/Scoring
CRM context
pushing insights into Notion / Confluence
AI-ready meeting intelligence
Strongest “outputs” layer
Mostly pull-based interactions
Fathom
✅ MCP
list/search meetings
get transcript
get summary/action items
Team/org context
Webhooks (event-based triggers)
get_weekly_recap
aggregated action items across meetings
creating webhooks directly from the MCP server
Lightweight meeting data access
Includes summaries + actions
Limited analytics depth
Grain
✅ Basic MCP
get meetings
download transcripts
Notes
Deals
Scorecards
Data access utility
Simple + accessible
Low sophistication, sometimes browser-based
Outreach
⚠️ MCP (workflow-focused)
Search sequences
Emails
Meetings (Kaia)
account / prospect / opportunity lookups
Workflow automation
Multi-system orchestration
Revenue workflow engine
End-to-end GTM workflows
Less depth in conversation data
Attention
⚠️ Emerging MCP
Meeting data
Transcripts
CRM-linked context
AI insights
Sales assistant workflows
create snippets
AI sales assistant + CRM
Strong CRM linkage
Less focus on external knowledge layer
Planhat -
Related content
Ask Jiminny Anything on Call level
Galya Dimitrova
Hubspot app
Galya Dimitrova
Product Vision & Strategy
Galya Dimitrova
Automated CRM Filling
Simona Georgieva (Deactivated)...
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Position Jiminny as a data layer for AI-driven revenue workflows, not just a standalone product. 👤 Target user Revenue teams using AI tools (Sales, CS, RevOps) Companies already experimenting with Claude / OpenAI Mid-market & Enterprise customers with multiple data sources (CRM, docs, CI tools, Support tools etc) 🤕 Pain point or problem Jiminny data is locked in the platform AI tools lack access to high-value conversation context Customers must manually export/copy transcripts No easy way to combine calls with CRM + docs + other info - using the Jiminny API is not suitable for non technical sales people Peer pressure as almost all competitors have this 💥 Impact and benefits For customers Better AI outputs using real customer conversations Ability to build automated workflows across tools For Jiminny Increased product stickiness (embedded in workflows) Competitive parity with Gong / Avoma etc. 💡 Solution ideas Build an AI Knowledge Connector (MCP-based) that: Exposes Jiminny data (calls, transcripts, metadata) to AI tools Provides structured insights (summaries, action items, scoring etc.) Supports deal-level context Allows integration into customer-owned AI stacks (Claude + Zapier, etc.) Success metrics List the key goals and how you will measure success. Include both qualitative and quantitative metrics (e.g., user adoption, retention rate, revenue targets). Goal Metric Increase stickiness by ensuring Jiminny is embedded in the customer’s workflows % of customers connecting external AI tools Number of MCP/API calls per customer - and which ones are being used the most Decrease the manual copying of transcripts decrease by X % User interaction and design Simple setup flow: Generate API key / connect MCP Clear instructions for Claude / Zapier setup Provide: Example prompts for Claude Pre-built workflow templates for Zapier Clear documentation - with use cases 👉 Focus: usable by non-technical users Detailed Requirements List the functional and non-functional requirements. Prioritize them (e.g., High, Medium, Low) and add notes for clarification. Requirement Importance Notes Allow customers to connect Jiminny to their AI tools (e.g. Claude, OpenAI) HIGH Provide MCP endpoint so customers can easily integrate Jiminny into their AI stack Allow customers to access call data through AI tools HIGH Expose Jiminny data: list calls (filter by date, user, account, deal) get call get transcript (speaker-separated) get call metadata search calls (keyword + semantic) Support filtering by: account / contact/ lead / deal jiminny user date range Allow customers to search and query calls using AI tools HIGH Support keyword and semantic search across conversations Provide structured insights so customers can generate better outputs HIGH For each call, expose: Summary Action items Key points Activity type Notes Call Score CRM information Allow customers to understand deal status across multiple calls/emails HIGH For each deal expose: calls/meetings/emails Identified risks contacts related to the deal with their job title linked account details all CRM field information that we have in DI + fields used for CRM filling example - get_deal_summary request - { \"tool\": \"get_deal_summary\", \"arguments\": { \"deal_name\": \"ACME\" } } responce: { \"deal_name\": \"ACME\", \"stage\": \"Negotiation\", \"recent_activity\": [ \"Demo call on 2026-04-01\", \"Pricing discussion on 2026-04-03\" ], \"risks\": [ \"Pricing concerns\", \"Security review pending\" ], \"next_steps\": [ \"Send follow-up to VP Sales\", \"Share security documentation\" ] } Ensure the AI can easily understand the schema of the data coming from Jiminny HIGH Models perform much better when tools have: clear names rich descriptions predictable schemas Provide clear, actionable error states for customers when MCP connections fail HIGH Error messages should guide agents toward solutions with specific suggestions and next steps. Expired or revoked key — “Error: Authentication failed. The API key used to access Jiminny has been revoked or has expired. Please ask your Jiminny admin to generate a new API key in Settings > Organization > General and reconnect the MCP server.” Rate limit hit — “Error: Rate limit exceeded. Too many requests have been made to the Jiminny MCP server in a short period. Please wait 60 seconds before retrying.” Permissions mismatch — if a user tries to access data outside their team visibility settings - “Error: Access denied. The requested call (call_id: [X]) is outside your team's visibility settings in Jiminny. Only calls within your permitted scope are accessible.” Trying to access private meeting - “Error: Access denied. This meeting has been marked as private by the host and cannot be accessed through the MCP connector. Try requesting a different call or ask the meeting host to change the visibility settings in Jiminny.” Downgraded/Capture account — if a customer's plan drops below Scale tier or the Customer is on Capture in the first place - “Error: MCP access unavailable. The Jiminny MCP connector is available on the Scale plan and above. Your account does not currently have an active Scale subscription.” Jiminny-side outage — “Error:Jiminny is temporarily unavailable (status 503). This is not a data or permissions issue — please retry in a few minutes.” No data found - “Error:No calls found matching your criteria. Try adjusting your filters — for example, widening the date range, removing the account filter, or checking the rep name is spelled correctly in Jiminny.” Allow customers to securely control who and what data is accessible externally HIGH Ensure MCP only exposes data user has access to - based on team visibility settings. This means that if a user is not allow to access calls/deals in Jiminny UI then they shouldn’t be able to access those through the MCP as well. Private meetings shouldn’t be exposed via MCP HIGH When a meetings is set to Private then the information about it shouldn’t be exposed through the MCP. Ensure Jiminny data can be combined with other sources (e.g. CRM, docs) in AI workflows HIGH Ensure data is structured to be easily combined with: CRM (accounts, deals) external docs Use consistent identifiers: account IDs deal IDs MCP is available only for Scale tier and above HIGH Customers who are on Capture tier should be able to access any of their data through MCP. This should also cover the scenario when a customer has been on Scale but then downgrades to Capture - their MCP access should stop working. Provide visibility into how external AI tools access Jiminny data HIGH Audit logs: what data was accessed by which external system when identity - who made the request specific queries/filters used failed access attempts (especially cross-visibility-boundary attempts) Admins should be able to access the logs from the org settings.We can start with a csv export before building a specific page for it. example from Atlassian - Provide customers with example prompts to get started quickly HIGH MCP prompts are explicitly defined as prompt templates that clients can discover and call with arguments. See examples in table below. Expose Jiminny as a Connector in Claude medium Competitors like Fathom are listed as Connectors in Claude. This will make it easier for customers to find us and to connect Jiminny Provide customers with example workflows to get started quickly medium A workflow is usually multiple steps, maybe multiple tools, still focused on one outcome. See examples in table below. Allow customers to use predefined Jiminny skills for common workflows medium Anthropic describes Skills as folders that include instructions, scripts, and resources that Claude can load when relevant, and as a way to teach Claude repeatable workflows, preferences, and domain expertise once instead of re-explaining them every time. Skills - a reusable package of behavior that can include prompts, instructions, resources, and sometimes scripts/tools for a broader job. Claude skills - https://resources.anthropic.com/hubfs/The-Complete-Guide-to-Building-Skill-for-Claude.pdf?hsLang=en&utm_source=chatgpt.com See examples in table below. Jiminny UI widget for OpenAI medium The reason to have this is to make certain Jiminny use cases much easier than pure chat. Instead of ChatGPT only replying with text like “Here are the last 5 ACME calls,” it could also show a visual Jiminny card or mini-app inside the chat. That widget could list calls, show a deal summary, let the user filter by rep/date/account, open a transcript section, or save a snippet—while the conversation continues in normal chat alongside it. For Jiminny, the best widget use cases are the ones where users need to browse or compare rather than ask one-off questions. A strong example is deal review: the user asks ChatGPT, “What is the status of the ACME deal?” ChatGPT calls your Jiminny MCP tools, and the widget shows a compact deal view with recent calls, risks, next steps, stakeholders, and links to transcripts/snippets. The chat can still summarize the answer in words, but the widget gives a clearer, scannable interface. Another good Jiminny widget use case is call search and exploration. A text answer can say “I found 12 calls mentioning pricing objections,” but a widget could show a sortable list with date, rep, account, score, and objection count, then let the user click into one call to see the exact excerpt or jump to a transcript section. Allow customers to run long-running analyses asynchronously and retrieve progress/results low Some requests/questions require analysis of Hugh volumes of data. For those, it may be better to: start the job let it run in the background return a status like “in progress” let the client come back for the result later For example - User asks in Claude: “Analyse all calls from this quarter and tell me the top 5 objections by segment.” That might require: searching lots of calls pulling many summaries/transcripts aggregating results Instead of making Claude wait 45+ seconds, Jiminny could: create an analysis job return: job_id = 123, status = running We need this in order to support: large-scale analysis multi-call aggregation across lots of data playlist generation across many calls heavy recap/report generation Creating a snippet through the MCP low Create a shareable snippet from a call recording by specifying a time range. Useful for highlighting key moments — objection handling, pricing discussions, competitive mentions — and sharing them with your team. example request: { \"tool\": \"create_snippet\", \"arguments\": { \"call_id\": \"call_123\", \"start_time\": \"00:18:24\", \"end_time\": \"00:19:10\", \"title\": \"Pricing objection\" } } example response: { \"snippet_id\": \"snip_987\", \"title\": \"Pricing objection\", \"share_url\": \"https://app.jiminny.com/snippets/snip_987\" } Ability to add recordings or snippets to a playlist low Allow customers to create libraries of calls automatically. They can use those for onboarding or other purposes Allow AI tools to read reusable Jiminny resources low fathom Resources are useful for data that should be read consistently rather than recomputed every time. In Jiminny terms, that could be: current deal snapshot account summary weekly rep recap approved talk tracks / objection handling guidance curated playlists or snippet libraries This is useful because an AI can consume these directly as context, instead of repeatedly stitching together many tool calls. Ability to write coaching notes in Jiminny through MCP low What we want to do for prompts/worflows and skills Capability Type User value / job to be done Example Jiminny use case Inputs Steps performed Output Draft follow-up email Prompt Help reps quickly create tailored follow-ups after calls Use the latest customer call to draft an email with recap and next steps Call ID optional tone optional recipient type Retrieve call summary and action items from Jiminny. Pull key points, commitments, and next steps. Apply the chosen tone and structure. Draft the email in a consistent format. Customer-ready follow-up email draft Summarise call Prompt Help users quickly extract the most important points from a conversation Generate a concise summary of one call for internal or external use Call ID optional summary style optional audience Retrieve transcript, metadata, and structured insights. Identify key topics, decisions, risks, and next steps. Format output for the chosen audience. Short or structured call summary with actions and risks Generate deal recap Prompt Help reps and managers get a fast overview of a deal Summarise the current state of a deal based on recent calls and linked CRM context Deal ID or account name optional date range Retrieve calls and meetings linked to the deal. Pull deal metadata and CRM-linked context. Identify recent changes, blockers, risks, and next steps. Summarise into a concise recap. Deal recap with status, blockers, risks, and recommended next steps Prepare weekly recap Prompt Help managers or reps review what changed over a time period Weekly recap of calls, themes, and actions for one rep, team, or account Rep ID team ID or account ID time period Retrieve relevant calls and summaries for the selected time period. Aggregate themes, action items, and changes. Highlight notable risks, opportunities, and follow-ups. Weekly recap with top themes, risks, opportunities, and actions Prepare deal review Workflow Help reps and managers review deal status using multiple sources of context Review a deal before pipeline review or forecast meeting Deal ID optional date range Retrieve all recent calls, emails, and meetings tied to the deal. Pull structured call summaries, score, action items, and key points. Pull linked CRM context such as stage, contacts, and account details. Aggregate open risks, unresolved objections, stakeholder gaps, and next steps. Format into a review-ready structure. Deal review document with current status, risks, stakeholders, blockers, and next steps Weekly team recap Workflow Help managers monitor activity and risk across a group of reps or accounts End-of-week team summary for sales leadership Team ID date range Retrieve calls and structured insights across the team. Group by rep, account, or deal. Identify recurring themes, major risks, strong calls, and missed follow-ups. Highlight calls or deals that need attention. Team-level recap with patterns, key risks, notable wins, and action areas Objection analysis across calls Workflow Help teams identify patterns across multiple conversations Analyse pricing or competitor objections across recent calls Account ID deal ID rep ID keyword/topic date range Search calls matching the topic or keyword. Retrieve summaries, transcripts, and snippets where relevant. Identify recurring objections and how they were handled. Assess whether objections were resolved or remain open. Summarise patterns and examples. Objection analysis with themes, frequency, examples, and suggested follow-up actions Build onboarding playlist Workflow Help enablement teams curate useful learning content faster Build a playlist of strong discovery, demo, or pricing calls for new hires Topic call type rep/team filter optional time period Search for calls matching the selected criteria. Rank or filter calls based on score, topics, or key moments. Identify useful snippets or full recordings. Add selected calls/snippets into a playlist structure. Generate short descriptions for each item. Curated onboarding playlist with selected calls/snippets and descriptions Deal Inspection Skill Skill Give users a consistent, opinionated way to assess a deal Claude reviews a deal using a repeatable Jiminny methodology Deal ID or account name optional review scope Determine whether the request is suitable for a deal inspection. Retrieve relevant calls, summaries, CRM context, stakeholders, and risks. Apply a standard Jiminny review framework to assess deal health. Look for missing next steps, unresolved objections, stakeholder gaps, and warning signs. Present findings in a consistent structure with recommended actions. Structured deal inspection with health assessment, red flags, and recommendations Manager Coaching Skill Skill Help managers review calls consistently and identify coaching moments Analyse a rep’s call and surface strengths, gaps, and examples for coaching Call ID optional rep ID optional coaching focus Retrieve transcript, score, summary, and key moments from the call. Evaluate the conversation against a coaching framework. Identify what went well and where the rep could improve. Suggest moments to clip as snippets. Recommend coaching actions or playlist additions. Coaching review with strengths, gaps, snippet suggestions, and recommended coaching actions CSM / QBR Prep Skill Skill Help CS or AM teams prepare structured customer reviews from conversations Generate an account review or QBR-style summary from recent customer interactions Account ID, optional time period Retrieve all recent calls, emails, and account-linked context. Aggregate themes, requests, blockers, sentiment shifts, and opportunities. Apply a repeatable account review structure. Summarise outcomes, open issues, and suggested next steps. Structured QBR/account review summary with themes, risks, opportunities, and actions Snippet Builder Skill Skill Help users consistently capture and label useful moments from calls Identify useful moments in a call and convert them into reusable snippets Call ID, optional focus area such as pricing, objection, competitor, discovery Retrieve transcript, recording timeline, and call insights. Detect moments matching the requested focus area. Propose snippet start/end times and titles. Tag snippets by type or theme. Optionally save them or add them to a playlist. One or more proposed or saved snippets with title, timing, and tags 💡 Technical details Auth model needs specifying. Are API keys scoped per user, per team, or per Jiminny instance? If a key is generated by an admin, does it inherit their visibility level, or provide org-wide? Are permissions evaluated at query time or frozen at key creation? Needs to be query-time, otherwise permission changes won't propagate. Key lifecycle management is missing. No mention of rotation, expiry, or revocation. A departed employee's active key is a data leak. Need: revocation, optional expiry, alerts on stale keys, and consider whether keys should be tied to service accounts rather than personal users. Rate limiting should be HIGH. A compromised key or misconfigured automation could bulk-export an entire customer's call history. Need per-key rate limits and anomaly detection on unusual access patterns. Open Questions Track unresolved issues or decisions that need to be made. Update as answers become available. Question Answer Date Answered Competitor research Competitor MCP Availability Core Capabilities Advanced Capabilities Positioning Key Strength Key Weakness Gong ✅ Mature MCP List/search calls Get transcripts get Call metadata Deal intelligence Scorecards, analytics CRM context Enterprise data layer Deep data + ecosystem integrations Limited opinionated AI workflows Avoma ✅ Mature MCP list_meetings get_meeting get_transcript key topics Deal fields/Deal level analysis Coaching/Scoring CRM context pushing insights into Notion / Confluence AI-ready meeting intelligence Strongest “outputs” layer Mostly pull-based interactions Fathom ✅ MCP list/search meetings get transcript get summary/action items Team/org context Webhooks (event-based triggers) get_weekly_recap aggregated action items across meetings creating webhooks directly from the MCP server Lightweight meeting data access Includes summaries + actions Limited analytics depth Grain ✅ Basic MCP get meetings download transcripts Notes Deals Scorecards Data access utility Simple + accessible Low sophistication, sometimes browser-based Outreach ⚠️ MCP (workflow-focused) Search sequences Emails Meetings (Kaia) account / prospect / opportunity lookups Workflow automation Multi-system orchestration Revenue workflow engine End-to-end GTM workflows Less depth in conversation data Attention ⚠️ Emerging MCP Meeting data Transcripts CRM-linked context AI insights Sales assistant workflows create snippets AI sales assistant + CRM Strong CRM linkage Less focus on external knowledge layer Planhat - Related content Ask Jiminny Anything on Call level Galya Dimitrova Hubspot app Galya Dimitrova Product Vision & Strategy Galya Dimitrova Automated CRM Filling Simona Georgieva (Deactivated) Competitive analysis Galya Dimitrova AI agent ideas Steliyan Georgiev Comments James Graham 9 Apr A few areas around Security & Compliance that need more depth before this moves beyond draft: Auth model needs specifying. Are API keys scoped per user, per team, or per Jiminny instance? If a key is generated by an admin, does it inherit their visibility level, or provide org-wide? Are permissions evaluated at query time or frozen at key creation? Needs to be query-time, otherwise permission changes won't propagate. Team visibility enforcement should be its own HIGH requirement. The current note under access control (\"ensure MCP only exposes data user has access to\") is doing too much work as a single line. Every MCP tool response (especially search_calls and deal-level aggregations) must be filtered through the same visibility engine as the UI. Semantic search is the riskiest here; it could surface results across team boundaries if not properly scoped. No data minimisation or scoping controls. We're exposing transcripts, CRM fields, contact details with job titles, deal context - significant PII and commercial data leaving the platform. Can customers configure which data types are exposed? Can transcripts be PII-stripped before they leave Jiminny? Given we position GDPR consent as a differentiator, we should be thinking about this. GDPR downstream processing is unaddressed. Piping transcripts to OpenAI/Gemini introduces new data processors. Customers need to acknowledge responsibility for downstream processing during setup. We should also consider whether call participants' recording consent covers onward sharing to third-party AI - it almost certainly doesn't by default. This is one for me to pick up. Key lifecycle management is missing. No mention of rotation, expiry, or revocation. A departed employee's active key is a data leak. Need: revocation, optional expiry, alerts on stale keys, and consider whether keys should be tied to service accounts rather than personal users. Rate limiting should be HIGH. A compromised key or misconfigured automation could bulk-export an entire customer's call history. Need per-key rate limits and anomaly detection on unusual access patterns. Audit logs should go deeper. Current spec (what data, which system, when) is a start. Add: identity behind the key, specific queries/filters used, and failed access attempts (especially cross-visibility-boundary attempts). Enterprise compliance teams will expect this. Downgrade handling. Doc says Scale tier and above, but doesn't say what happens on downgrade. Keys should auto-deactivate. Happy to help draft a dedicated Security & Compliance section if useful. Galya Dimitrova 15 Apr Thanks for the input @James Graham . I made the product related changes in the table and for the rest I left them as a note in the Technical section for the team to look at when they start looking at this. I wonder about your points related to GDPR. Currently multiple customers are using the Customer API/zapier to feed this data to AI and BI tools. They are also manually exporting transcripts and other information from the platform and feeding it to AI tools. I don’t get how MCP is so much different that all of these and why it will introduce new data processors (which are already being utilised) and would require any changes to the consent provided by participants.","depth":21,"help_text":"","role_description":"heading","subrole":"AXUnknown"},{"role":"AXStaticText","text":"You said","depth":23,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"Jiminny MCP Connector","depth":23,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"Epic","depth":23,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"Link to Epik in Jira","depth":23,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"Document status","depth":23,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"DRAFT","depth":23,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"Objective","depth":23,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"Enable customers to connect Jiminny data to external AI tools (Claude, OpenAI, Gemini) so it can be used as part of their broader knowledge base and workflows.","depth":23,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"Position Jiminny as a data layer for AI-driven revenue workflows, not just a standalone product.","depth":23,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"👤 Target user","depth":23,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"Revenue teams using AI tools (Sales, CS, RevOps)","depth":23,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"Companies already experimenting with Claude / OpenAI","depth":23,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"Mid-market & Enterprise customers with multiple data sources (CRM, docs, CI tools, Support tools etc)","depth":23,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"🤕 Pain point or problem","depth":23,"bounds":{"left":0.30868056,"top":0.125,"width":0.077430554,"height":0.054444443},"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"Jiminny data is locked in the platform","depth":23,"bounds":{"left":0.30868056,"top":0.18777777,"width":0.074652776,"height":0.085},"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"AI tools lack access to high-value conversation context","depth":23,"bounds":{"left":0.30868056,"top":0.28111112,"width":0.10555556,"height":0.085},"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"Customers must manually export/copy transcripts","depth":23,"bounds":{"left":0.30868056,"top":0.37444445,"width":0.108333334,"height":0.085},"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"No easy way to combine calls with CRM + docs + other info - 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The API key used to access Jiminny has been revoked or has expired. Please ask your Jiminny admin to generate a new API key in Settings > Organization > General and reconnect the MCP server.”","depth":23,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"Rate limit hit — “Error: Rate limit exceeded. Too many requests have been made to the Jiminny MCP server in a short period. Please wait 60 seconds before retrying.”","depth":23,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"Permissions mismatch — if a user tries to access data outside their team visibility settings - “Error: Access denied. The requested call (call_id: [X]) is outside your team's visibility settings in Jiminny. Only calls within your permitted scope are accessible.”","depth":23,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"Trying to access private meeting - “Error: Access denied. 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This is not a data or permissions issue — please retry in a few minutes.”","depth":23,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"No data found - “Error:No calls found matching your criteria. Try adjusting your filters — for example, widening the date range, removing the account filter, or checking the rep name is spelled correctly in Jiminny.”","depth":23,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"Allow customers to securely control who and what data is accessible externally","depth":23,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"HIGH","depth":23,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"Ensure MCP only exposes data user has access to - based on team visibility settings. 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This will make it easier for customers to find us and to connect Jiminny","depth":23,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"Provide customers with example workflows to get started quickly","depth":23,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"medium","depth":23,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"A workflow is usually multiple steps, maybe multiple tools, still focused on one outcome.","depth":23,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"See examples in table below.","depth":23,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"Allow customers to use predefined Jiminny skills for common workflows","depth":23,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"medium","depth":23,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"Anthropic describes Skills as folders that include instructions, scripts, and resources that Claude can load when relevant, and as a way to teach Claude repeatable workflows, preferences, and domain expertise once instead of re-explaining them every time. Skills - a reusable package of behavior that can include prompts, instructions, resources, and sometimes scripts/tools for a broader job.","depth":23,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"Claude skills - https://resources.anthropic.com/hubfs/The-Complete-Guide-to-Building-Skill-for-Claude.pdf?hsLang=en&utm_source=chatgpt.com","depth":23,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"See examples in table below.","depth":23,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"Jiminny UI widget for OpenAI","depth":23,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"medium","depth":23,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"The reason to have this is to make certain Jiminny use cases much easier than pure chat.","depth":23,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"Instead of ChatGPT only replying with text like “Here are the last 5 ACME calls,” it could also show a visual Jiminny card or mini-app inside the chat. That widget could list calls, show a deal summary, let the user filter by rep/date/account, open a transcript section, or save a snippet—while the conversation continues in normal chat alongside it.","depth":23,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"For Jiminny, the best widget use cases are the ones where users need to browse or compare rather than ask one-off questions. A strong example is deal review: the user asks ChatGPT, “What is the status of the ACME deal?” ChatGPT calls your Jiminny MCP tools, and the widget shows a compact deal view with recent calls, risks, next steps, stakeholders, and links to transcripts/snippets. The chat can still summarize the answer in words, but the widget gives a clearer, scannable interface.","depth":23,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"Another good Jiminny widget use case is call search and exploration. A text answer can say “I found 12 calls mentioning pricing objections,” but a widget could show a sortable list with date, rep, account, score, and objection count, then let the user click into one call to see the exact excerpt or jump to a transcript section.","depth":23,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"Allow customers to run long-running analyses asynchronously and retrieve progress/results","depth":23,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"low","depth":23,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"Some requests/questions require analysis of Hugh volumes of data. 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Useful for highlighting key moments — objection handling, pricing discussions, competitive mentions — and sharing them with your team.","depth":23,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"example request:","depth":23,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"{","depth":23,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"\"tool\": \"create_snippet\",","depth":23,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"\"arguments\": {","depth":23,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"\"call_id\": \"call_123\",","depth":23,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"\"start_time\": \"00:18:24\",","depth":23,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"\"end_time\": \"00:19:10\",","depth":23,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"\"title\": \"Pricing objection\"","depth":23,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"}","depth":23,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"}","depth":23,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"example response:","depth":23,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"{","depth":23,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"\"snippet_id\": \"snip_987\",","depth":23,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"\"title\": \"Pricing objection\",","depth":23,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"\"share_url\": \"https://app.jiminny.com/snippets/snip_987\"","depth":23,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"}","depth":23,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"Ability to add recordings or snippets to a playlist","depth":23,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"low","depth":23,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"Allow customers to create libraries of calls automatically. They can use those for onboarding or other purposes","depth":23,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"Allow AI tools to read reusable Jiminny resources","depth":23,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"low","depth":23,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"fathom","depth":23,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"Resources are useful for data that should be read consistently rather than recomputed every time. In Jiminny terms, that could be:","depth":23,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"current deal snapshot","depth":23,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"account summary","depth":23,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"weekly rep recap","depth":23,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"approved talk tracks / objection handling guidance","depth":23,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"curated playlists or snippet libraries","depth":23,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"This is useful because an AI can consume these directly as context, instead of repeatedly stitching together many tool calls.","depth":23,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"Ability to write coaching notes in Jiminny through MCP","depth":23,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"low","depth":23,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"What we want to do for prompts/worflows and skills","depth":23,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"Capability","depth":23,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"Type","depth":23,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"User value / job to be done","depth":23,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"Example Jiminny use 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Skill","depth":23,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"Skill","depth":23,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"Help CS or AM teams prepare structured customer reviews from conversations","depth":23,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"Generate an account review or QBR-style summary from recent customer interactions","depth":23,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"Account ID, optional time period","depth":23,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"Retrieve all recent calls, emails, and account-linked context.","depth":23,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"Aggregate themes, requests, blockers, sentiment shifts, and opportunities.","depth":23,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"Apply a repeatable account review structure.","depth":23,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"Summarise outcomes, open issues, and suggested next steps.","depth":23,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"Structured QBR/account review summary with themes, risks, opportunities, and actions","depth":23,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"Snippet Builder Skill","depth":23,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"Skill","depth":23,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"Help users consistently capture and label useful moments from 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theme.","depth":23,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"Optionally save them or add them to a playlist.","depth":23,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"One or more proposed or saved snippets with title, timing, and tags","depth":23,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"💡 Technical details","depth":23,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"Auth model needs specifying. Are API keys scoped per user, per team, or per Jiminny instance? If a key is generated by an admin, does it inherit their visibility level, or provide org-wide? Are permissions evaluated at query time or frozen at key creation? Needs to be query-time, otherwise permission changes won't propagate.","depth":23,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"Key lifecycle management is missing. No mention of rotation, expiry, or revocation. A departed employee's active key is a data leak. Need: revocation, optional expiry, alerts on stale keys, and consider whether keys should be tied to service accounts rather than personal users.","depth":23,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"Rate limiting should be HIGH. A compromised key or misconfigured automation could bulk-export an entire customer's call history. Need per-key rate limits and anomaly detection on unusual access patterns.","depth":23,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"Open Questions","depth":23,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"Track unresolved issues or decisions that need to be made. Update as answers become available.","depth":23,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"Question","depth":23,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"Answer","depth":23,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"Date Answered","depth":23,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"Competitor research","depth":23,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"Competitor","depth":23,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"MCP Availability","depth":23,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"Core Capabilities","depth":23,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"Advanced 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Dimitrova","depth":23,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"Hubspot app","depth":23,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"Galya Dimitrova","depth":23,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"Product Vision & Strategy","depth":23,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"Galya Dimitrova","depth":23,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"Automated CRM Filling","depth":23,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"Simona Georgieva (Deactivated)","depth":23,"help_text":"","role_description":"text","subrole":"AXUnknown"}]...
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Platform Sprint 2 Q2 - Platform Team - Scrum Board Platform Sprint 2 Q2 - Platform Team - Scrum Board - Jira
SevenShores\Hubspot\Exceptions\BadRequest: Client error: `POST [URL_WITH_CREDENTIALS] Graham . I made the product related changes in the table and for the rest I left them as a note in the Technical section for the team to look at when they start looking at this. I wonder about your points related to GDPR. Currently multiple customers are using the Customer API/zapier to feed this data to AI and BI tools. They are also manually exporting transcripts and other information from the platform and feeding it to AI tools. I don’t get how MCP is so much different that all of these and why it will introduce new data processors (which are already being utilised) and would require any changes to the consent provided by participants.
You said
Jiminny MCP Connector
Epic
Link to Epik in Jira
Document status
DRAFT
Objective
Enable customers to connect Jiminny data to external AI tools (Claude, OpenAI, Gemini) so it can be used as part of their broader knowledge base and workflows.
Position Jiminny as a data layer for AI-driven revenue workflows, not just a standalone product.
👤 Target user
Revenue teams using AI tools (Sales, CS, RevOps)
Companies already experimenting with Claude / OpenAI
Mid-market & Enterprise customers with multiple data sources (CRM, docs, CI tools, Support tools etc)
🤕 Pain point or problem
Jiminny data is locked in the platform
AI tools lack access to high-value conversation context
Customers must manually export/copy transcripts
No easy way to combine calls with CRM + docs + other info - using the Jiminny API is not suitable for non technical sales people
Peer pressure as almost all competitors have this
💥 Impact and benefits
For customers
Better AI outputs using real customer conversations
Ability to build automated workflows across tools
For Jiminny
Increased product stickiness (embedded in workflows)
Competitive parity with Gong / Avoma etc.
💡 Solution ideas
Build an AI Knowledge Connector (MCP-based) that:
Exposes Jiminny data (calls, transcripts, metadata) to AI tools
Provides structured insights (summaries, action items, scoring etc.)
Supports deal-level context
Allows integration into customer-owned AI stacks (Claude + Zapier, etc.)
Success metrics
List the key goals and how you will measure success. Include both qualitative and quantitative metrics (e.g., user adoption, retention rate, revenue targets).
Goal
Metric
Increase stickiness by ensuring Jiminny is embedded in the customer’s workflows
% of customers connecting external AI tools
Number of MCP/API calls per customer - and which ones are being used the most
Decrease the manual copying of transcripts
decrease by X %
User interaction and design
Simple setup flow:
Generate API key / connect MCP
Clear instructions for Claude / Zapier setup
Provide:
Example prompts for Claude
Pre-built workflow templates for Zapier
Clear documentation - with use cases
👉 Focus: usable by non-technical users
Detailed Requirements
List the functional and non-functional requirements. Prioritize them (e.g., High, Medium, Low) and add notes for clarification.
Requirement
Importance
Notes
Allow customers to connect Jiminny to their AI tools (e.g. Claude, OpenAI)
HIGH
Provide MCP endpoint so customers can easily integrate Jiminny into their AI stack
Allow customers to access call data through AI tools
HIGH
Expose Jiminny data:
list calls (filter by date, user, account, deal)
get call
get transcript (speaker-separated)
get call metadata
search calls (keyword + semantic)
Support filtering by:
account / contact/ lead / deal
jiminny user
date range
Allow customers to search and query calls using AI tools
HIGH
Support keyword and semantic search across conversations
Provide structured insights so customers can generate better outputs
HIGH
For each call, expose:
Summary
Action items
Key points
Activity type
Notes
Call Score
CRM information
Allow customers to understand deal status across multiple calls/emails
HIGH
For each deal expose:
calls/meetings/emails
Identified risks
contacts related to the deal with their job title
linked account details
all CRM field information that we have in DI + fields used for CRM filling
example - get_deal_summary
request -
{
"tool": "get_deal_summary",
"arguments": {
"deal_name": "ACME"
}
}
responce:
{
"deal_name": "ACME",
"stage": "Negotiation",
"recent_activity": [
"Demo call on 2026-04-01",
"Pricing discussion on 2026-04-03"
],
"risks": [
"Pricing concerns",
"Security review pending"
], "next_steps": [
"Send follow-up to VP Sales",
"Share security documentation"
]
}
Ensure the AI can easily understand the schema of the data coming from Jiminny
HIGH
Models perform much better when tools have:
clear names
rich descriptions
predictable schemas
Provide clear, actionable error states for customers when MCP connections fail
HIGH
Error messages should guide agents toward solutions with specific suggestions and next steps.
Expired or revoked key — “Error: Authentication failed. The API key used to access Jiminny has been revoked or has expired. Please ask your Jiminny admin to generate a new API key in Settings > Organization > General and reconnect the MCP server.”
Rate limit hit — “Error: Rate limit exceeded. Too many requests have been made to the Jiminny MCP server in a short period. Please wait 60 seconds before retrying.”
Permissions mismatch — if a user tries to access data outside their team visibility settings - “Error: Access denied. The requested call (call_id: [X]) is outside your team's visibility settings in Jiminny. Only calls within your permitted scope are accessible.”
Trying to access private meeting - “Error: Access denied. This meeting has been marked as private by the host and cannot be accessed through the MCP connector. Try requesting a different call or ask the meeting host to change the visibility settings in Jiminny.”
Downgraded/Capture account — if a customer's plan drops below Scale tier or the Customer is on Capture in the first place - “Error: MCP access unavailable. The Jiminny MCP connector is available on the Scale plan and above. Your account does not currently have an active Scale subscription.”
Jiminny-side outage — “Error:Jiminny is temporarily unavailable (status 503). This is not a data or permissions issue — please retry in a few minutes.”
No data found - “Error:No calls found matching your criteria. Try adjusting your filters — for example, widening the date range, removing the account filter, or checking the rep name is spelled correctly in Jiminny.”
Allow customers to securely control who and what data is accessible externally
HIGH
Ensure MCP only exposes data user has access to - based on team visibility settings. This means that if a user is not allow to access calls/deals in Jiminny UI then they shouldn’t be able to access those through the MCP as well.
Private meetings shouldn’t be exposed via MCP
HIGH
When a meetings is set to Private then the information about it shouldn’t be exposed through the MCP.
Ensure Jiminny data can be combined with other sources (e.g. CRM, docs) in AI workflows
HIGH
Ensure data is structured to be easily combined with:
CRM (accounts, deals)
external docs
Use consistent identifiers:
account IDs
deal IDs
MCP is available only for Scale tier and above
HIGH
Customers who are on Capture tier should be able to access any of their data through MCP.
This should also cover the scenario when a customer has been on Scale but then downgrades to Capture - their MCP access should stop working.
Provide visibility into how external AI tools access Jiminny data
HIGH
Audit logs:
what data was accessed by which external system when
identity - who made the request
specific queries/filters used
failed access attempts (especially cross-visibility-boundary attempts)
Admins should be able to access the logs from the org settings.We can start with a csv export before building a specific page for it.
example from Atlassian -
Provide customers with example prompts to get started quickly
HIGH
MCP prompts are explicitly defined as prompt templates that clients can discover and call with arguments.
See examples in table below.
Expose Jiminny as a Connector in Claude
medium
Competitors like Fathom are listed as Connectors in Claude. This will make it easier for customers to find us and to connect Jiminny
Provide customers with example workflows to get started quickly
medium
A workflow is usually multiple steps, maybe multiple tools, still focused on one outcome.
See examples in table below.
Allow customers to use predefined Jiminny skills for common workflows
medium
Anthropic describes Skills as folders that include instructions, scripts, and resources that Claude can load when relevant, and as a way to teach Claude repeatable workflows, preferences, and domain expertise once instead of re-explaining them every time. Skills - a reusable package of behavior that can include prompts, instructions, resources, and sometimes scripts/tools for a broader job.
Claude skills - https://resources.anthropic.com/hubfs/The-Complete-Guide-to-Building-Skill-for-Claude.pdf?hsLang=en&utm_source=chatgpt.com
See examples in table below.
Jiminny UI widget for OpenAI
medium
The reason to have this is to make certain Jiminny use cases much easier than pure chat.
Instead of ChatGPT only replying with text like “Here are the last 5 ACME calls,” it could also show a visual Jiminny card or mini-app inside the chat. That widget could list calls, show a deal summary, let the user filter by rep/date/account, open a transcript section, or save a snippet—while the conversation continues in normal chat alongside it.
For Jiminny, the best widget use cases are the ones where users need to browse or compare rather than ask one-off questions. A strong example is deal review: the user asks ChatGPT, “What is the status of the ACME deal?” ChatGPT calls your Jiminny MCP tools, and the widget shows a compact deal view with recent calls, risks, next steps, stakeholders, and links to transcripts/snippets. The chat can still summarize the answer in words, but the widget gives a clearer, scannable interface.
Another good Jiminny widget use case is call search and exploration. A text answer can say “I found 12 calls mentioning pricing objections,” but a widget could show a sortable list with date, rep, account, score, and objection count, then let the user click into one call to see the exact excerpt or jump to a transcript section.
Allow customers to run long-running analyses asynchronously and retrieve progress/results
low
Some requests/questions require analysis of Hugh volumes of data. For those, it may be better to:
start the job
let it run in the background
return a status like “in progress”
let the client come back for the result later
For example - User asks in Claude:
“Analyse all calls from this quarter and tell me the top 5 objections by segment.”
That might require:
searching lots of calls
pulling many summaries/transcripts
aggregating results
Instead of making Claude wait 45+ seconds, Jiminny could:
create an analysis job
return: job_id = 123, status = running
We need this in order to support:
large-scale analysis
multi-call aggregation across lots of data
playlist generation across many calls
heavy recap/report generation
Creating a snippet through the MCP
low
Create a shareable snippet from a call recording by specifying a time range. Useful for highlighting key moments — objection handling, pricing discussions, competitive mentions — and sharing them with your team.
example request:
{
"tool": "create_snippet",
"arguments": {
"call_id": "call_123",
"start_time": "00:18:24",
"end_time": "00:19:10",
"title": "Pricing objection"
}
}
example response:
{
"snippet_id": "snip_987",
"title": "Pricing objection",
"share_url": "https://app.jiminny.com/snippets/snip_987"
}
Ability to add recordings or snippets to a playlist
low
Allow customers to create libraries of calls automatically. They can use those for onboarding or other purposes
Allow AI tools to read reusable Jiminny resources
low
fathom
Resources are useful for data that should be read consistently rather than recomputed every time. In Jiminny terms, that could be:
current deal snapshot
account summary
weekly rep recap
approved talk tracks / objection handling guidance
curated playlists or snippet libraries
This is useful because an AI can consume these directly as context, instead of repeatedly stitching together many tool calls.
Ability to write coaching notes in Jiminny through MCP
low
What we want to do for prompts/worflows and skills
Capability
Type
User value / job to be done
Example Jiminny use case
Inputs
Steps performed
Output
Draft follow-up email
Prompt
Help reps quickly create tailored follow-ups after calls
Use the latest customer call to draft an email with recap and next steps
Call ID
optional tone
optional recipient type
Retrieve call summary and action items from Jiminny.
Pull key points, commitments, and next steps.
Apply the chosen tone and structure.
Draft the email in a consistent format.
Customer-ready follow-up email draft
Summarise call
Prompt
Help users quickly extract the most important points from a conversation
Generate a concise summary of one call for internal or external use
Call ID
optional summary style
optional audience
Retrieve transcript, metadata, and structured insights.
Identify key topics, decisions, risks, and next steps.
Format output for the chosen audience.
Short or structured call summary with actions and risks
Generate deal recap
Prompt
Help reps and managers get a fast overview of a deal
Summarise the current state of a deal based on recent calls and linked CRM context
Deal ID or account name
optional date range
Retrieve calls and meetings linked to the deal.
Pull deal metadata and CRM-linked context.
Identify recent changes, blockers, risks, and next steps.
Summarise into a concise recap.
Deal recap with status, blockers, risks, and recommended next steps
Prepare weekly recap
Prompt
Help managers or reps review what changed over a time period
Weekly recap of calls, themes, and actions for one rep, team, or account
Rep ID
team ID or account ID
time period
Retrieve relevant calls and summaries for the selected time period.
Aggregate themes, action items, and changes.
Highlight notable risks, opportunities, and follow-ups.
Weekly recap with top themes, risks, opportunities, and actions
Prepare deal review
Workflow
Help reps and managers review deal status using multiple sources of context
Review a deal before pipeline review or forecast meeting
Deal ID
optional date range
Retrieve all recent calls, emails, and meetings tied to the deal.
Pull structured call summaries, score, action items, and key points.
Pull linked CRM context such as stage, contacts, and account details.
Aggregate open risks, unresolved objections, stakeholder gaps, and next steps.
Format into a review-ready structure.
Deal review document with current status, risks, stakeholders, blockers, and next steps
Weekly team recap
Workflow
Help managers monitor activity and risk across a group of reps or accounts
End-of-week team summary for sales leadership
Team ID
date range
Retrieve calls and structured insights across the team.
Group by rep, account, or deal.
Identify recurring themes, major risks, strong calls, and missed follow-ups.
Highlight calls or deals that need attention.
Team-level recap with patterns, key risks, notable wins, and action areas
Objection analysis across calls
Workflow
Help teams identify patterns across multiple conversations
Analyse pricing or competitor objections across recent calls
Account ID
deal ID
rep ID
keyword/topic
date range
Search calls matching the topic or keyword.
Retrieve summaries, transcripts, and snippets where relevant.
Identify recurring objections and how they were handled.
Assess whether objections were resolved or remain open.
Summarise patterns and examples.
Objection analysis with themes, frequency, examples, and suggested follow-up actions
Build onboarding playlist
Workflow
Help enablement teams curate useful learning content faster
Build a playlist of strong discovery, demo, or pricing calls for new hires
Topic
call type
rep/team filter
optional time period
Search for calls matching the selected criteria.
Rank or filter calls based on score, topics, or key moments.
Identify useful snippets or full recordings.
Add selected calls/snippets into a playlist structure.
Generate short descriptions for each item.
Curated onboarding playlist with selected calls/snippets and descriptions
Deal Inspection Skill
Skill
Give users a consistent, opinionated way to assess a deal
Claude reviews a deal using a repeatable Jiminny methodology
Deal ID or account name
optional review scope
Determine whether the request is suitable for a deal inspection.
Retrieve relevant calls, summaries, CRM context, stakeholders, and risks.
Apply a standard Jiminny review framework to assess deal health.
Look for missing next steps, unresolved objections, stakeholder gaps, and warning signs.
Present findings in a consistent structure with recommended actions.
Structured deal inspection with health assessment, red flags, and recommendations
Manager Coaching Skill
Skill
Help managers review calls consistently and identify coaching moments
Analyse a rep’s call and surface strengths, gaps, and examples for coaching
Call ID
optional rep ID
optional coaching focus
Retrieve transcript, score, summary, and key moments from the call.
Evaluate the conversation against a coaching framework.
Identify what went well and where the rep could improve.
Suggest moments to clip as snippets.
Recommend coaching actions or playlist additions.
Coaching review with strengths, gaps, snippet suggestions, and recommended coaching actions
CSM / QBR Prep Skill
Skill
Help CS or AM teams prepare structured customer reviews from conversations
Generate an account review or QBR-style summary from recent customer interactions
Account ID, optional time period
Retrieve all recent calls, emails, and account-linked context.
Aggregate themes, requests, blockers, sentiment shifts, and opportunities.
Apply a repeatable account review structure.
Summarise outcomes, open issues, and suggested next steps.
Structured QBR/account review summary with themes, risks, opportunities, and actions
Snippet Builder Skill
Skill
Help users consistently capture and label useful moments from calls
Identify useful moments in a call and convert them into reusable snippets
Call ID, optional focus area such as pricing, objection, competitor, discovery
Retrieve transcript, recording timeline, and call insights.
Detect moments matching the requested focus area.
Propose snippet start/end times and titles.
Tag snippets by type or theme.
Optionally save them or add them to a playlist.
One or more proposed or saved snippets with title, timing, and tags
💡 Technical details
Auth model needs specifying. Are API keys scoped per user, per team, or per Jiminny instance? If a key is generated by an admin, does it inherit their visibility level, or provide org-wide? Are permissions evaluated at query time or frozen at key creation? Needs to be query-time, otherwise permission changes won't propagate.
Key lifecycle management is missing. No mention of rotation, expiry, or revocation. A departed employee's active key is a data leak. Need: revocation, optional expiry, alerts on stale keys, and consider whether keys should be tied to service accounts rather than personal users.
Rate limiting should be HIGH. A compromised key or misconfigured automation could bulk-export an entire customer's call history. Need per-key rate limits and anomaly detection on unusual access patterns.
Open Questions
Track unresolved issues or decisions that need to be made. Update as answers become available.
Question
Answer
Date Answered
Competitor research
Competitor
MCP Availability
Core Capabilities
Advanced Capabilities
Positioning
Key Strength
Key Weakness
Gong
✅ Mature MCP
List/search calls
Get transcripts
get Call metadata
Deal intelligence
Scorecards, analytics
CRM context
Enterprise data layer
Deep data + ecosystem integrations
Limited opinionated AI workflows
Avoma
✅ Mature MCP
list_meetings
get_meeting
get_transcript
key topics
Deal fields/Deal level analysis
Coaching/Scoring
CRM context
pushing insights into Notion / Confluence
AI-ready meeting intelligence
Strongest “outputs” layer
Mostly pull-based interactions
Fathom
✅ MCP
list/search meetings
get transcript
get summary/action items
Team/org context
Webhooks (event-based triggers)
get_weekly_recap
aggregated action items across meetings
creating webhooks directly from the MCP server
Lightweight meeting data access
Includes summaries + actions
Limited analytics depth
Grain
✅ Basic MCP
get meetings
download transcripts
Notes
Deals
Scorecards
Data access utility
Simple + accessible
Low sophistication, sometimes browser-based
Outreach
⚠️ MCP (workflow-focused)
Search sequences
Emails
Meetings (Kaia)
account / prospect / opportunity lookups
Workflow automation
Multi-system orchestration
Revenue workflow engine
End-to-end GTM workflows
Less depth in conversation data
Attention
⚠️ Emerging MCP
Meeting data
Transcripts
CRM-linked context
AI insights
Sales assistant workflows
create snippets
AI sales assistant + CRM
Strong CRM linkage
Less focus on external knowledge layer
Planhat -
Related content
Ask Jiminny Anything on Call level
Galya Dimitrova
Hubspot app
Galya Dimitrova
Product Vision & Strategy
Galya Dimitrova
Automated CRM Filling
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Platform Sprint 2 Q2 - Platform Team - Scrum Board Platform Sprint 2 Q2 - Platform Team - Scrum Board - Jira
SevenShores\Hubspot\Exceptions\BadRequest: Client error: `POST [URL_WITH_CREDENTIALS] Graham . I made the product related changes in the table and for the rest I left them as a note in the Technical section for the team to look at when they start looking at this. I wonder about your points related to GDPR. Currently multiple customers are using the Customer API/zapier to feed this data to AI and BI tools. They are also manually exporting transcripts and other information from the platform and feeding it to AI tools. I don’t get how MCP is so much different that all of these and why it will introduce new data processors (which are already being utilised) and would require any changes to the consent provided by participants.
You said
Jiminny MCP Connector
Epic
Link to Epik in Jira
Document status
DRAFT
Objective
Enable customers to connect Jiminny data to external AI tools (Claude, OpenAI, Gemini) so it can be used as part of their broader knowledge base and workflows.
Position Jiminny as a data layer for AI-driven revenue workflows, not just a standalone product.
👤 Target user
Revenue teams using AI tools (Sales, CS, RevOps)
Companies already experimenting with Claude / OpenAI
Mid-market & Enterprise customers with multiple data sources (CRM, docs, CI tools, Support tools etc)
🤕 Pain point or problem
Jiminny data is locked in the platform
AI tools lack access to high-value conversation context
Customers must manually export/copy transcripts
No easy way to combine calls with CRM + docs + other info - using the Jiminny API is not suitable for non technical sales people
Peer pressure as almost all competitors have this
💥 Impact and benefits
For customers
Better AI outputs using real customer conversations
Ability to build automated workflows across tools
For Jiminny
Increased product stickiness (embedded in workflows)
Competitive parity with Gong / Avoma etc.
💡 Solution ideas
Build an AI Knowledge Connector (MCP-based) that:
Exposes Jiminny data (calls, transcripts, metadata) to AI tools
Provides structured insights (summaries, action items, scoring etc.)
Supports deal-level context
Allows integration into customer-owned AI stacks (Claude + Zapier, etc.)
Success metrics
List the key goals and how you will measure success. Include both qualitative and quantitative metrics (e.g., user adoption, retention rate, revenue targets).
Goal
Metric
Increase stickiness by ensuring Jiminny is embedded in the customer’s workflows
% of customers connecting external AI tools
Number of MCP/API calls per customer - and which ones are being used the most
Decrease the manual copying of transcripts
decrease by X %
User interaction and design
Simple setup flow:
Generate API key / connect MCP
Clear instructions for Claude / Zapier setup
Provide:
Example prompts for Claude
Pre-built workflow templates for Zapier
Clear documentation - with use cases
👉 Focus: usable by non-technical users
Detailed Requirements
List the functional and non-functional requirements. Prioritize them (e.g., High, Medium, Low) and add notes for clarification.
Requirement
Importance
Notes
Allow customers to connect Jiminny to their AI tools (e.g. Claude, OpenAI)
HIGH
Provide MCP endpoint so customers can easily integrate Jiminny into their AI stack
Allow customers to access call data through AI tools
HIGH
Expose Jiminny data:
list calls (filter by date, user, account, deal)
get call
get transcript (speaker-separated)
get call metadata
search calls (keyword + semantic)
Support filtering by:
account / contact/ lead / deal
jiminny user
date range
Allow customers to search and query calls using AI tools
HIGH
Support keyword and semantic search across conversations
Provide structured insights so customers can generate better outputs
HIGH
For each call, expose:
Summary
Action items
Key points
Activity type
Notes
Call Score
CRM information
Allow customers to understand deal status across multiple calls/emails
HIGH
For each deal expose:
calls/meetings/emails
Identified risks
contacts related to the deal with their job title
linked account details
all CRM field information that we have in DI + fields used for CRM filling
example - get_deal_summary
request -
{
"tool": "get_deal_summary",
"arguments": {
"deal_name": "ACME"
}
}
responce:
{
"deal_name": "ACME",
"stage": "Negotiation",
"recent_activity": [
"Demo call on 2026-04-01",
"Pricing discussion on 2026-04-03"
],
"risks": [
"Pricing concerns",
"Security review pending"
], "next_steps": [
"Send follow-up to VP Sales",
"Share security documentation"
]
}
Ensure the AI can easily understand the schema of the data coming from Jiminny
HIGH
Models perform much better when tools have:
clear names
rich descriptions
predictable schemas
Provide clear, actionable error states for customers when MCP connections fail
HIGH
Error messages should guide agents toward solutions with specific suggestions and next steps.
Expired or revoked key — “Error: Authentication failed. The API key used to access Jiminny has been revoked or has expired. Please ask your Jiminny admin to generate a new API key in Settings > Organization > General and reconnect the MCP server.”
Rate limit hit — “Error: Rate limit exceeded. Too many requests have been made to the Jiminny MCP server in a short period. Please wait 60 seconds before retrying.”
Permissions mismatch — if a user tries to access data outside their team visibility settings - “Error: Access denied. The requested call (call_id: [X]) is outside your team's visibility settings in Jiminny. Only calls within your permitted scope are accessible.”
Trying to access private meeting - “Error: Access denied. This meeting has been marked as private by the host and cannot be accessed through the MCP connector. Try requesting a different call or ask the meeting host to change the visibility settings in Jiminny.”
Downgraded/Capture account — if a customer's plan drops below Scale tier or the Customer is on Capture in the first place - “Error: MCP access unavailable. The Jiminny MCP connector is available on the Scale plan and above. Your account does not currently have an active Scale subscription.”
Jiminny-side outage — “Error:Jiminny is temporarily unavailable (status 503). This is not a data or permissions issue — please retry in a few minutes.”
No data found - “Error:No calls found matching your criteria. Try adjusting your filters — for example, widening the date range, removing the account filter, or checking the rep name is spelled correctly in Jiminny.”
Allow customers to securely control who and what data is accessible externally
HIGH
Ensure MCP only exposes data user has access to - based on team visibility settings. This means that if a user is not allow to access calls/deals in Jiminny UI then they shouldn’t be able to access those through the MCP as well.
Private meetings shouldn’t be exposed via MCP
HIGH
When a meetings is set to Private then the information about it shouldn’t be exposed through the MCP.
Ensure Jiminny data can be combined with other sources (e.g. CRM, docs) in AI workflows
HIGH
Ensure data is structured to be easily combined with:
CRM (accounts, deals)
external docs
Use consistent identifiers:
account IDs
deal IDs
MCP is available only for Scale tier and above
HIGH
Customers who are on Capture tier should be able to access any of their data through MCP.
This should also cover the scenario when a customer has been on Scale but then downgrades to Capture - their MCP access should stop working.
Provide visibility into how external AI tools access Jiminny data
HIGH
Audit logs:
what data was accessed by which external system when
identity - who made the request
specific queries/filters used
failed access attempts (especially cross-visibility-boundary attempts)
Admins should be able to access the logs from the org settings.We can start with a csv export before building a specific page for it.
example from Atlassian -
Provide customers with example prompts to get started quickly
HIGH
MCP prompts are explicitly defined as prompt templates that clients can discover and call with arguments.
See examples in table below.
Expose Jiminny as a Connector in Claude
medium
Competitors like Fathom are listed as Connectors in Claude. This will make it easier for customers to find us and to connect Jiminny
Provide customers with example workflows to get started quickly
medium
A workflow is usually multiple steps, maybe multiple tools, still focused on one outcome.
See examples in table below.
Allow customers to use predefined Jiminny skills for common workflows
medium
Anthropic describes Skills as folders that include instructions, scripts, and resources that Claude can load when relevant, and as a way to teach Claude repeatable workflows, preferences, and domain expertise once instead of re-explaining them every time. Skills - a reusable package of behavior that can include prompts, instructions, resources, and sometimes scripts/tools for a broader job.
Claude skills - https://resources.anthropic.com/hubfs/The-Complete-Guide-to-Building-Skill-for-Claude.pdf?hsLang=en&utm_source=chatgpt.com
See examples in table below.
Jiminny UI widget for OpenAI
medium
The reason to have this is to make certain Jiminny use cases much easier than pure chat.
Instead of ChatGPT only replying with text like “Here are the last 5 ACME calls,” it could also show a visual Jiminny card or mini-app inside the chat. That widget could list calls, show a deal summary, let the user filter by rep/date/account, open a transcript section, or save a snippet—while the conversation continues in normal chat alongside it.
For Jiminny, the best widget use cases are the ones where users need to browse or compare rather than ask one-off questions. A strong example is deal review: the user asks ChatGPT, “What is the status of the ACME deal?” ChatGPT calls your Jiminny MCP tools, and the widget shows a compact deal view with recent calls, risks, next steps, stakeholders, and links to transcripts/snippets. The chat can still summarize the answer in words, but the widget gives a clearer, scannable interface.
Another good Jiminny widget use case is call search and exploration. A text answer can say “I found 12 calls mentioning pricing objections,” but a widget could show a sortable list with date, rep, account, score, and objection count, then let the user click into one call to see the exact excerpt or jump to a transcript section.
Allow customers to run long-running analyses asynchronously and retrieve progress/results
low
Some requests/questions require analysis of Hugh volumes of data. For those, it may be better to:
start the job
let it run in the background
return a status like “in progress”
let the client come back for the result later
For example - User asks in Claude:
“Analyse all calls from this quarter and tell me the top 5 objections by segment.”
That might require:
searching lots of calls
pulling many summaries/transcripts
aggregating results
Instead of making Claude wait 45+ seconds, Jiminny could:
create an analysis job
return: job_id = 123, status = running
We need this in order to support:
large-scale analysis
multi-call aggregation across lots of data
playlist generation across many calls
heavy recap/report generation
Creating a snippet through the MCP
low
Create a shareable snippet from a call recording by specifying a time range. Useful for highlighting key moments — objection handling, pricing discussions, competitive mentions — and sharing them with your team.
example request:
{
"tool": "create_snippet",
"arguments": {
"call_id": "call_123",
"start_time": "00:18:24",
"end_time": "00:19:10",
"title": "Pricing objection"
}
}
example response:
{
"snippet_id": "snip_987",
"title": "Pricing objection",
"share_url": "https://app.jiminny.com/snippets/snip_987"
}
Ability to add recordings or snippets to a playlist
low
Allow customers to create libraries of calls automatically. They can use those for onboarding or other purposes
Allow AI tools to read reusable Jiminny resources
low
fathom
Resources are useful for data that should be read consistently rather than recomputed every time. In Jiminny terms, that could be:
current deal snapshot
account summary
weekly rep recap
approved talk tracks / objection handling guidance
curated playlists or snippet libraries
This is useful because an AI can consume these directly as context, instead of repeatedly stitching together many tool calls.
Ability to write coaching notes in Jiminny through MCP
low
What we want to do for prompts/worflows and skills
Capability
Type
User value / job to be done
Example Jiminny use case
Inputs
Steps performed
Output
Draft follow-up email
Prompt
Help reps quickly create tailored follow-ups after calls
Use the latest customer call to draft an email with recap and next steps
Call ID
optional tone
optional recipient type
Retrieve call summary and action items from Jiminny.
Pull key points, commitments, and next steps.
Apply the chosen tone and structure.
Draft the email in a consistent format.
Customer-ready follow-up email draft
Summarise call
Prompt
Help users quickly extract the most important points from a conversation
Generate a concise summary of one call for internal or external use
Call ID
optional summary style
optional audience
Retrieve transcript, metadata, and structured insights.
Identify key topics, decisions, risks, and next steps.
Format output for the chosen audience.
Short or structured call summary with actions and risks
Generate deal recap
Prompt
Help reps and managers get a fast overview of a deal
Summarise the current state of a deal based on recent calls and linked CRM context
Deal ID or account name
optional date range
Retrieve calls and meetings linked to the deal.
Pull deal metadata and CRM-linked context.
Identify recent changes, blockers, risks, and next steps.
Summarise into a concise recap.
Deal recap with status, blockers, risks, and recommended next steps
Prepare weekly recap
Prompt
Help managers or reps review what changed over a time period
Weekly recap of calls, themes, and actions for one rep, team, or account
Rep ID
team ID or account ID
time period
Retrieve relevant calls and summaries for the selected time period.
Aggregate themes, action items, and changes.
Highlight notable risks, opportunities, and follow-ups.
Weekly recap with top themes, risks, opportunities, and actions
Prepare deal review
Workflow
Help reps and managers review deal status using multiple sources of context
Review a deal before pipeline review or forecast meeting
Deal ID
optional date range
Retrieve all recent calls, emails, and meetings tied to the deal.
Pull structured call summaries, score, action items, and key points.
Pull linked CRM context such as stage, contacts, and account details.
Aggregate open risks, unresolved objections, stakeholder gaps, and next steps.
Format into a review-ready structure.
Deal review document with current status, risks, stakeholders, blockers, and next steps
Weekly team recap
Workflow
Help managers monitor activity and risk across a group of reps or accounts
End-of-week team summary for sales leadership
Team ID
date range
Retrieve calls and structured insights across the team.
Group by rep, account, or deal.
Identify recurring themes, major risks, strong calls, and missed follow-ups.
Highlight calls or deals that need attention.
Team-level recap with patterns, key risks, notable wins, and action areas
Objection analysis across calls
Workflow
Help teams identify patterns across multiple conversations
Analyse pricing or competitor objections across recent calls
Account ID
deal ID
rep ID
keyword/topic
date range
Search calls matching the topic or keyword.
Retrieve summaries, transcripts, and snippets where relevant.
Identify recurring objections and how they were handled.
Assess whether objections were resolved or remain open.
Summarise patterns and examples.
Objection analysis with themes, frequency, examples, and suggested follow-up actions
Build onboarding playlist
Workflow
Help enablement teams curate useful learning content faster
Build a playlist of strong discovery, demo, or pricing calls for new hires
Topic
call type
rep/team filter
optional time period
Search for calls matching the selected criteria.
Rank or filter calls based on score, topics, or key moments.
Identify useful snippets or full recordings.
Add selected calls/snippets into a playlist structure.
Generate short descriptions for each item.
Curated onboarding playlist with selected calls/snippets and descriptions
Deal Inspection Skill
Skill
Give users a consistent, opinionated way to assess a deal
Claude reviews a deal using a repeatable Jiminny methodology
Deal ID or account name
optional review scope
Determine whether the request is suitable for a deal inspection.
Retrieve relevant calls, summaries, CRM context, stakeholders, and risks.
Apply a standard Jiminny review framework to assess deal health.
Look for missing next steps, unresolved objections, stakeholder gaps, and warning signs.
Present findings in a consistent structure with recommended actions.
Structured deal inspection with health assessment, red flags, and recommendations
Manager Coaching Skill
Skill
Help managers review calls consistently and identify coaching moments
Analyse a rep’s call and surface strengths, gaps, and examples for coaching
Call ID
optional rep ID
optional coaching focus
Retrieve transcript, score, summary, and key moments from the call.
Evaluate the conversation against a coaching framework.
Identify what went well and where the rep could improve.
Suggest moments to clip as snippets.
Recommend coaching actions or playlist additions.
Coaching review with strengths, gaps, snippet suggestions, and recommended coaching actions
CSM / QBR Prep Skill
Skill
Help CS or AM teams prepare structured customer reviews from conversations
Generate an account review or QBR-style summary from recent customer interactions
Account ID, optional time period
Retrieve all recent calls, emails, and account-linked context.
Aggregate themes, requests, blockers, sentiment shifts, and opportunities.
Apply a repeatable account review structure.
Summarise outcomes, open issues, and suggested next steps.
Structured QBR/account review summary with themes, risks, opportunities, and actions
Snippet Builder Skill
Skill
Help users consistently capture and label useful moments from calls
Identify useful moments in a call and convert them into reusable snippets
Call ID, optional focus area such as pricing, objection, competitor, discovery
Retrieve transcript, recording timeline, and call insights.
Detect moments matching the requested focus area.
Propose snippet start/end times and titles.
Tag snippets by type or theme.
Optionally save them or add them to a playlist.
One or more proposed or saved snippets with title, timing, and tags
💡 Technical details
Auth model needs specifying. Are API keys scoped per user, per team, or per Jiminny instance? If a key is generated by an admin, does it inherit their visibility level, or provide org-wide? Are permissions evaluated at query time or frozen at key creation? Needs to be query-time, otherwise permission changes won't propagate.
Key lifecycle management is missing. No mention of rotation, expiry, or revocation. A departed employee's active key is a data leak. Need: revocation, optional expiry, alerts on stale keys, and consider whether keys should be tied to service accounts rather than personal users.
Rate limiting should be HIGH. A compromised key or misconfigured automation could bulk-export an entire customer's call history. Need per-key rate limits and anomaly detection on unusual access patterns.
Open Questions
Track unresolved issues or decisions that need to be made. Update as answers become available.
Question
Answer
Date Answered
Competitor research
Competitor
MCP Availability
Core Capabilities
Advanced Capabilities
Positioning
Key Strength
Key Weakness
Gong
✅ Mature MCP
List/search calls
Get transcripts
get Call metadata
Deal intelligence
Scorecards, analytics
CRM context
Enterprise data layer
Deep data + ecosystem integrations
Limited opinionated AI workflows
Avoma
✅ Mature MCP
list_meetings
get_meeting
get_transcript
key topics
Deal fields/Deal level analysis
Coaching/Scoring
CRM context
pushing insights into Notion / Confluence
AI-ready meeting intelligence
Strongest “outputs” layer
Mostly pull-based interactions
Fathom
✅ MCP
list/search meetings
get transcript
get summary/action items
Team/org context
Webhooks (event-based triggers)
get_weekly_recap
aggregated action items across meetings
creating webhooks directly from the MCP server
Lightweight meeting data access
Includes summaries + actions
Limited analytics depth
Grain
✅ Basic MCP
get meetings
download transcripts
Notes
Deals
Scorecards
Data access utility
Simple + accessible
Low sophistication, sometimes browser-based
Outreach
⚠️ MCP (workflow-focused)...
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Objective Enable customers to connect Jiminny data to external AI tools (Claude, OpenAI, Gemini) so it can be used as part of their broader knowledge base and workflows. Position Jiminny as a data layer for AI-driven revenue workflows, not just a standalone product. 👤 Target user Revenue teams using AI tools (Sales, CS, RevOps) Companies already experimenting with Claude / OpenAI Mid-market & Enterprise customers with multiple data sources (CRM, docs, CI tools, Support tools etc) 🤕 Pain point or problem Jiminny data is locked in the platform AI tools lack access to high-value conversation context Customers must manually export/copy transcripts No easy way to combine calls with CRM + docs + other info - using the Jiminny API is not suitable for non technical sales people Peer pressure as almost all competitors have this 💥 Impact and benefits For customers Better AI outputs using real customer conversations Ability to build automated workflows across tools For Jiminny Increased product stickiness (embedded in workflows) Competitive parity with Gong / Avoma etc. 💡 Solution ideas Build an AI Knowledge Connector (MCP-based) that: Exposes Jiminny data (calls, transcripts, metadata) to AI tools Provides structured insights (summaries, action items, scoring etc.) Supports deal-level context Allows integration into customer-owned AI stacks (Claude + Zapier, etc.) Success metrics List the key goals and how you will measure success. Include both qualitative and quantitative metrics (e.g., user adoption, retention rate, revenue targets). Goal Metric Increase stickiness by ensuring Jiminny is embedded in the customer’s workflows % of customers connecting external AI tools Number of MCP/API calls per customer - and which ones are being used the most Decrease the manual copying of transcripts decrease by X % User interaction and design Simple setup flow: Generate API key / connect MCP Clear instructions for Claude / Zapier setup Provide: Example prompts for Claude Pre-built workflow templates for Zapier Clear documentation - with use cases 👉 Focus: usable by non-technical users Detailed Requirements List the functional and non-functional requirements. Prioritize them (e.g., High, Medium, Low) and add notes for clarification. Requirement Importance Notes Allow customers to connect Jiminny to their AI tools (e.g. Claude, OpenAI) HIGH Provide MCP endpoint so customers can easily integrate Jiminny into their AI stack Allow customers to access call data through AI tools HIGH Expose Jiminny data: list calls (filter by date, user, account, deal) get call get transcript (speaker-separated) get call metadata search calls (keyword + semantic) Support filtering by: account / contact/ lead / deal jiminny user date range Allow customers to search and query calls using AI tools HIGH Support keyword and semantic search across conversations Provide structured insights so customers can generate better outputs HIGH For each call, expose: Summary Action items Key points Activity type Notes Call Score CRM information Allow customers to understand deal status across multiple calls/emails HIGH For each deal expose: calls/meetings/emails Identified risks contacts related to the deal with their job title linked account details all CRM field information that we have in DI + fields used for CRM filling example - get_deal_summary request - { \"tool\": \"get_deal_summary\", \"arguments\": { \"deal_name\": \"ACME\" } } responce: { \"deal_name\": \"ACME\", \"stage\": \"Negotiation\", \"recent_activity\": [ \"Demo call on 2026-04-01\", \"Pricing discussion on 2026-04-03\" ], \"risks\": [ \"Pricing concerns\", \"Security review pending\" ], \"next_steps\": [ \"Send follow-up to VP Sales\", \"Share security documentation\" ] } Ensure the AI can easily understand the schema of the data coming from Jiminny HIGH Models perform much better when tools have: clear names rich descriptions predictable schemas Provide clear, actionable error states for customers when MCP connections fail HIGH Error messages should guide agents toward solutions with specific suggestions and next steps. Expired or revoked key — “Error: Authentication failed. The API key used to access Jiminny has been revoked or has expired. Please ask your Jiminny admin to generate a new API key in Settings > Organization > General and reconnect the MCP server.” Rate limit hit — “Error: Rate limit exceeded. Too many requests have been made to the Jiminny MCP server in a short period. Please wait 60 seconds before retrying.” Permissions mismatch — if a user tries to access data outside their team visibility settings - “Error: Access denied. The requested call (call_id: [X]) is outside your team's visibility settings in Jiminny. Only calls within your permitted scope are accessible.” Trying to access private meeting - “Error: Access denied. This meeting has been marked as private by the host and cannot be accessed through the MCP connector. Try requesting a different call or ask the meeting host to change the visibility settings in Jiminny.” Downgraded/Capture account — if a customer's plan drops below Scale tier or the Customer is on Capture in the first place - “Error: MCP access unavailable. The Jiminny MCP connector is available on the Scale plan and above. Your account does not currently have an active Scale subscription.” Jiminny-side outage — “Error:Jiminny is temporarily unavailable (status 503). This is not a data or permissions issue — please retry in a few minutes.” No data found - “Error:No calls found matching your criteria. Try adjusting your filters — for example, widening the date range, removing the account filter, or checking the rep name is spelled correctly in Jiminny.” Allow customers to securely control who and what data is accessible externally HIGH Ensure MCP only exposes data user has access to - based on team visibility settings. This means that if a user is not allow to access calls/deals in Jiminny UI then they shouldn’t be able to access those through the MCP as well. Private meetings shouldn’t be exposed via MCP HIGH When a meetings is set to Private then the information about it shouldn’t be exposed through the MCP. Ensure Jiminny data can be combined with other sources (e.g. CRM, docs) in AI workflows HIGH Ensure data is structured to be easily combined with: CRM (accounts, deals) external docs Use consistent identifiers: account IDs deal IDs MCP is available only for Scale tier and above HIGH Customers who are on Capture tier should be able to access any of their data through MCP. This should also cover the scenario when a customer has been on Scale but then downgrades to Capture - their MCP access should stop working. Provide visibility into how external AI tools access Jiminny data HIGH Audit logs: what data was accessed by which external system when identity - who made the request specific queries/filters used failed access attempts (especially cross-visibility-boundary attempts) Admins should be able to access the logs from the org settings.We can start with a csv export before building a specific page for it. example from Atlassian - Provide customers with example prompts to get started quickly HIGH MCP prompts are explicitly defined as prompt templates that clients can discover and call with arguments. See examples in table below. Expose Jiminny as a Connector in Claude medium Competitors like Fathom are listed as Connectors in Claude. This will make it easier for customers to find us and to connect Jiminny Provide customers with example workflows to get started quickly medium A workflow is usually multiple steps, maybe multiple tools, still focused on one outcome. See examples in table below. Allow customers to use predefined Jiminny skills for common workflows medium Anthropic describes Skills as folders that include instructions, scripts, and resources that Claude can load when relevant, and as a way to teach Claude repeatable workflows, preferences, and domain expertise once instead of re-explaining them every time. Skills - a reusable package of behavior that can include prompts, instructions, resources, and sometimes scripts/tools for a broader job. Claude skills - https://resources.anthropic.com/hubfs/The-Complete-Guide-to-Building-Skill-for-Claude.pdf?hsLang=en&utm_source=chatgpt.com See examples in table below. Jiminny UI widget for OpenAI medium The reason to have this is to make certain Jiminny use cases much easier than pure chat. Instead of ChatGPT only replying with text like “Here are the last 5 ACME calls,” it could also show a visual Jiminny card or mini-app inside the chat. That widget could list calls, show a deal summary, let the user filter by rep/date/account, open a transcript section, or save a snippet—while the conversation continues in normal chat alongside it. For Jiminny, the best widget use cases are the ones where users need to browse or compare rather than ask one-off questions. A strong example is deal review: the user asks ChatGPT, “What is the status of the ACME deal?” ChatGPT calls your Jiminny MCP tools, and the widget shows a compact deal view with recent calls, risks, next steps, stakeholders, and links to transcripts/snippets. The chat can still summarize the answer in words, but the widget gives a clearer, scannable interface. Another good Jiminny widget use case is call search and exploration. A text answer can say “I found 12 calls mentioning pricing objections,” but a widget could show a sortable list with date, rep, account, score, and objection count, then let the user click into one call to see the exact excerpt or jump to a transcript section. Allow customers to run long-running analyses asynchronously and retrieve progress/results low Some requests/questions require analysis of Hugh volumes of data. For those, it may be better to: start the job let it run in the background return a status like “in progress” let the client come back for the result later For example - User asks in Claude: “Analyse all calls from this quarter and tell me the top 5 objections by segment.” That might require: searching lots of calls pulling many summaries/transcripts aggregating results Instead of making Claude wait 45+ seconds, Jiminny could: create an analysis job return: job_id = 123, status = running We need this in order to support: large-scale analysis multi-call aggregation across lots of data playlist generation across many calls heavy recap/report generation Creating a snippet through the MCP low Create a shareable snippet from a call recording by specifying a time range. Useful for highlighting key moments — objection handling, pricing discussions, competitive mentions — and sharing them with your team. example request: { \"tool\": \"create_snippet\", \"arguments\": { \"call_id\": \"call_123\", \"start_time\": \"00:18:24\", \"end_time\": \"00:19:10\", \"title\": \"Pricing objection\" } } example response: { \"snippet_id\": \"snip_987\", \"title\": \"Pricing objection\", \"share_url\": \"https://app.jiminny.com/snippets/snip_987\" } Ability to add recordings or snippets to a playlist low Allow customers to create libraries of calls automatically. They can use those for onboarding or other purposes Allow AI tools to read reusable Jiminny resources low fathom Resources are useful for data that should be read consistently rather than recomputed every time. In Jiminny terms, that could be: current deal snapshot account summary weekly rep recap approved talk tracks / objection handling guidance curated playlists or snippet libraries This is useful because an AI can consume these directly as context, instead of repeatedly stitching together many tool calls. Ability to write coaching notes in Jiminny through MCP low What we want to do for prompts/worflows and skills Capability Type User value / job to be done Example Jiminny use case Inputs Steps performed Output Draft follow-up email Prompt Help reps quickly create tailored follow-ups after calls Use the latest customer call to draft an email with recap and next steps Call ID optional tone optional recipient type Retrieve call summary and action items from Jiminny. Pull key points, commitments, and next steps. Apply the chosen tone and structure. Draft the email in a consistent format. Customer-ready follow-up email draft Summarise call Prompt Help users quickly extract the most important points from a conversation Generate a concise summary of one call for internal or external use Call ID optional summary style optional audience Retrieve transcript, metadata, and structured insights. Identify key topics, decisions, risks, and next steps. Format output for the chosen audience. Short or structured call summary with actions and risks Generate deal recap Prompt Help reps and managers get a fast overview of a deal Summarise the current state of a deal based on recent calls and linked CRM context Deal ID or account name optional date range Retrieve calls and meetings linked to the deal. Pull deal metadata and CRM-linked context. Identify recent changes, blockers, risks, and next steps. Summarise into a concise recap. Deal recap with status, blockers, risks, and recommended next steps Prepare weekly recap Prompt Help managers or reps review what changed over a time period Weekly recap of calls, themes, and actions for one rep, team, or account Rep ID team ID or account ID time period Retrieve relevant calls and summaries for the selected time period. Aggregate themes, action items, and changes. Highlight notable risks, opportunities, and follow-ups. Weekly recap with top themes, risks, opportunities, and actions Prepare deal review Workflow Help reps and managers review deal status using multiple sources of context Review a deal before pipeline review or forecast meeting Deal ID optional date range Retrieve all recent calls, emails, and meetings tied to the deal. Pull structured call summaries, score, action items, and key points. Pull linked CRM context such as stage, contacts, and account details. Aggregate open risks, unresolved objections, stakeholder gaps, and next steps. Format into a review-ready structure. Deal review document with current status, risks, stakeholders, blockers, and next steps Weekly team recap Workflow Help managers monitor activity and risk across a group of reps or accounts End-of-week team summary for sales leadership Team ID date range Retrieve calls and structured insights across the team. Group by rep, account, or deal. Identify recurring themes, major risks, strong calls, and missed follow-ups. Highlight calls or deals that need attention. Team-level recap with patterns, key risks, notable wins, and action areas Objection analysis across calls Workflow Help teams identify patterns across multiple conversations Analyse pricing or competitor objections across recent calls Account ID deal ID rep ID keyword/topic date range Search calls matching the topic or keyword. Retrieve summaries, transcripts, and snippets where relevant. Identify recurring objections and how they were handled. Assess whether objections were resolved or remain open. Summarise patterns and examples. Objection analysis with themes, frequency, examples, and suggested follow-up actions Build onboarding playlist Workflow Help enablement teams curate useful learning content faster Build a playlist of strong discovery, demo, or pricing calls for new hires Topic call type rep/team filter optional time period Search for calls matching the selected criteria. Rank or filter calls based on score, topics, or key moments. Identify useful snippets or full recordings. Add selected calls/snippets into a playlist structure. Generate short descriptions for each item. Curated onboarding playlist with selected calls/snippets and descriptions Deal Inspection Skill Skill Give users a consistent, opinionated way to assess a deal Claude reviews a deal using a repeatable Jiminny methodology Deal ID or account name optional review scope Determine whether the request is suitable for a deal inspection. Retrieve relevant calls, summaries, CRM context, stakeholders, and risks. Apply a standard Jiminny review framework to assess deal health. Look for missing next steps, unresolved objections, stakeholder gaps, and warning signs. Present findings in a consistent structure with recommended actions. Structured deal inspection with health assessment, red flags, and recommendations Manager Coaching Skill Skill Help managers review calls consistently and identify coaching moments Analyse a rep’s call and surface strengths, gaps, and examples for coaching Call ID optional rep ID optional coaching focus Retrieve transcript, score, summary, and key moments from the call. Evaluate the conversation against a coaching framework. Identify what went well and where the rep could improve. Suggest moments to clip as snippets. Recommend coaching actions or playlist additions. Coaching review with strengths, gaps, snippet suggestions, and recommended coaching actions CSM / QBR Prep Skill Skill Help CS or AM teams prepare structured customer reviews from conversations Generate an account review or QBR-style summary from recent customer interactions Account ID, optional time period Retrieve all recent calls, emails, and account-linked context. Aggregate themes, requests, blockers, sentiment shifts, and opportunities. Apply a repeatable account review structure. Summarise outcomes, open issues, and suggested next steps. Structured QBR/account review summary with themes, risks, opportunities, and actions Snippet Builder Skill Skill Help users consistently capture and label useful moments from calls Identify useful moments in a call and convert them into reusable snippets Call ID, optional focus area such as pricing, objection, competitor, discovery Retrieve transcript, recording timeline, and call insights. Detect moments matching the requested focus area. Propose snippet start/end times and titles. Tag snippets by type or theme. Optionally save them or add them to a playlist. One or more proposed or saved snippets with title, timing, and tags 💡 Technical details Auth model needs specifying. Are API keys scoped per user, per team, or per Jiminny instance? If a key is generated by an admin, does it inherit their visibility level, or provide org-wide? Are permissions evaluated at query time or frozen at key creation? Needs to be query-time, otherwise permission changes won't propagate. Key lifecycle management is missing. No mention of rotation, expiry, or revocation. A departed employee's active key is a data leak. Need: revocation, optional expiry, alerts on stale keys, and consider whether keys should be tied to service accounts rather than personal users. Rate limiting should be HIGH. A compromised key or misconfigured automation could bulk-export an entire customer's call history. Need per-key rate limits and anomaly detection on unusual access patterns. Open Questions Track unresolved issues or decisions that need to be made. Update as answers become available. Question Answer Date Answered Competitor research Competitor MCP Availability Core Capabilities Advanced Capabilities Positioning Key Strength Key Weakness Gong ✅ Mature MCP List/search calls Get transcripts get Call metadata Deal intelligence Scorecards, analytics CRM context Enterprise data layer Deep data + ecosystem integrations Limited opinionated AI workflows Avoma ✅ Mature MCP list_meetings get_meeting get_transcript key topics Deal fields/Deal level analysis Coaching/Scoring CRM context pushing insights into Notion / Confluence AI-ready meeting intelligence Strongest “outputs” layer Mostly pull-based interactions Fathom ✅ MCP list/search meetings get transcript get summary/action items Team/org context Webhooks (event-based triggers) get_weekly_recap aggregated action items across meetings creating webhooks directly from the MCP server Lightweight meeting data access Includes summaries + actions Limited analytics depth Grain ✅ Basic MCP get meetings download transcripts Notes Deals Scorecards Data access utility Simple + accessible Low sophistication, sometimes browser-based Outreach ⚠️ MCP (workflow-focused) Search sequences Emails Meetings (Kaia) account / prospect / opportunity lookups Workflow automation Multi-system orchestration Revenue workflow engine End-to-end GTM workflows Less depth in conversation data Attention ⚠️ Emerging MCP Meeting data Transcripts CRM-linked context AI insights Sales assistant workflows create snippets AI sales assistant + CRM Strong CRM linkage Less focus on external knowledge layer Planhat - Related content Ask Jiminny Anything on Call level Galya Dimitrova Hubspot app Galya Dimitrova Product Vision & Strategy Galya Dimitrova Automated CRM Filling Simona Georgieva (Deactivated) Competitive analysis Galya Dimitrova AI agent ideas Steliyan Georgiev Comments James Graham 9 Apr A few areas around Security & Compliance that need more depth before this moves beyond draft: Auth model needs specifying. Are API keys scoped per user, per team, or per Jiminny instance? If a key is generated by an admin, does it inherit their visibility level, or provide org-wide? Are permissions evaluated at query time or frozen at key creation? Needs to be query-time, otherwise permission changes won't propagate. Team visibility enforcement should be its own HIGH requirement. The current note under access control (\"ensure MCP only exposes data user has access to\") is doing too much work as a single line. Every MCP tool response (especially search_calls and deal-level aggregations) must be filtered through the same visibility engine as the UI. Semantic search is the riskiest here; it could surface results across team boundaries if not properly scoped. No data minimisation or scoping controls. We're exposing transcripts, CRM fields, contact details with job titles, deal context - significant PII and commercial data leaving the platform. Can customers configure which data types are exposed? Can transcripts be PII-stripped before they leave Jiminny? Given we position GDPR consent as a differentiator, we should be thinking about this. GDPR downstream processing is unaddressed. Piping transcripts to OpenAI/Gemini introduces new data processors. Customers need to acknowledge responsibility for downstream processing during setup. We should also consider whether call participants' recording consent covers onward sharing to third-party AI - it almost certainly doesn't by default. This is one for me to pick up. Key lifecycle management is missing. No mention of rotation, expiry, or revocation. A departed employee's active key is a data leak. Need: revocation, optional expiry, alerts on stale keys, and consider whether keys should be tied to service accounts rather than personal users. Rate limiting should be HIGH. A compromised key or misconfigured automation could bulk-export an entire customer's call history. Need per-key rate limits and anomaly detection on unusual access patterns. Audit logs should go deeper. Current spec (what data, which system, when) is a start. Add: identity behind the key, specific queries/filters used, and failed access attempts (especially cross-visibility-boundary attempts). Enterprise compliance teams will expect this. Downgrade handling. Doc says Scale tier and above, but doesn't say what happens on downgrade. Keys should auto-deactivate. Happy to help draft a dedicated Security & Compliance section if useful. Galya Dimitrova 15 Apr Thanks for the input @James Graham . I made the product related changes in the table and for the rest I left them as a note in the Technical section for the team to look at when they start looking at this. I wonder about your points related to GDPR. Currently multiple customers are using the Customer API/zapier to feed this data to AI and BI tools. They are also manually exporting transcripts and other information from the platform and feeding it to AI tools. I don’t get how MCP is so much different that all of these and why it will introduce new data processors (which are already being utilised) and would require any changes to the consent provided by participants.","depth":21,"bounds":{"left":0.41805187,"top":0.19313647,"width":0.051861703,"height":0.11173184},"help_text":"","role_description":"heading","subrole":"AXUnknown"},{"role":"AXStaticText","text":"You said","depth":23,"bounds":{"left":0.36053857,"top":0.19553073,"width":0.019946808,"height":0.016360734},"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"Jiminny MCP Connector","depth":23,"bounds":{"left":0.41805187,"top":0.1963288,"width":0.03125,"height":0.038707104},"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"Epic","depth":23,"bounds":{"left":0.41805187,"top":0.30806065,"width":0.010305851,"height":0.016360734},"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"Link to Epik in Jira","depth":23,"bounds":{"left":0.41805187,"top":0.33040702,"width":0.043218084,"height":0.016360734},"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"Document status","depth":23,"bounds":{"left":0.41805187,"top":0.3527534,"width":0.04105718,"height":0.016360734},"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"DRAFT","depth":23,"bounds":{"left":0.41805187,"top":0.37509975,"width":0.016289894,"height":0.016360734},"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"Objective","depth":23,"bounds":{"left":0.41805187,"top":0.39744613,"width":0.024268618,"height":0.016360734},"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"Enable customers to connect Jiminny data to external AI tools (Claude, OpenAI, Gemini) so it can be used as part of their broader knowledge base and workflows.","depth":23,"bounds":{"left":0.41805187,"top":0.4197925,"width":0.051529255,"height":0.17278531},"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"Position Jiminny as a data layer for AI-driven revenue workflows, not just a standalone product.","depth":23,"bounds":{"left":0.41805187,"top":0.59856343,"width":0.049700797,"height":0.10574621},"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"👤 Target user","depth":23,"bounds":{"left":0.41805187,"top":0.75458896,"width":0.033909574,"height":0.016759777},"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"Revenue teams using AI tools (Sales, CS, RevOps)","depth":23,"bounds":{"left":0.41805187,"top":0.7773344,"width":0.051030584,"height":0.061053474},"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"Companies already experimenting with Claude / OpenAI","depth":23,"bounds":{"left":0.41805187,"top":0.8443735,"width":0.04637633,"height":0.061053474},"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"Mid-market & Enterprise customers with multiple data sources (CRM, docs, CI tools, Support tools etc)","depth":23,"bounds":{"left":0.41805187,"top":0.9114126,"width":0.051363032,"height":0.0885874},"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"🤕 Pain point or problem","depth":23,"bounds":{"left":0.41805187,"top":1.0,"width":0.03706782,"height":-0.0897845},"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"Jiminny data is locked in the platform","depth":23,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"AI tools lack access to high-value conversation context","depth":23,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"Customers must manually export/copy transcripts","depth":23,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"No easy way to combine calls with CRM + docs + other info - 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This is not a data or permissions issue — please retry in a few minutes.”","depth":23,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"No data found - “Error:No calls found matching your criteria. Try adjusting your filters — for example, widening the date range, removing the account filter, or checking the rep name is spelled correctly in Jiminny.”","depth":23,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"Allow customers to securely control who and what data is accessible externally","depth":23,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"HIGH","depth":23,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"Ensure MCP only exposes data user has access to - based on team visibility settings. This means that if a user is not allow to access calls/deals in Jiminny UI then they shouldn’t be able to access those through the MCP as well.","depth":23,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"Private meetings shouldn’t be exposed via MCP","depth":23,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"HIGH","depth":23,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"When a meetings is set to Private then the information about it shouldn’t be exposed through the MCP.","depth":23,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"Ensure Jiminny data can be combined with other sources (e.g. CRM, docs) in AI workflows","depth":23,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"HIGH","depth":23,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"Ensure data is structured to be easily combined with:","depth":23,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"CRM (accounts, deals)","depth":23,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"external docs","depth":23,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"Use consistent identifiers:","depth":23,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"account IDs","depth":23,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"deal IDs","depth":23,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"MCP is available only for Scale tier and above","depth":23,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"HIGH","depth":23,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"Customers who are on Capture tier should be able to access any of their data through MCP.","depth":23,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"This should also cover the scenario when a customer has been on Scale but then downgrades to Capture - their MCP access should stop working.","depth":23,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"Provide visibility into how external AI tools access Jiminny data","depth":23,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"HIGH","depth":23,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"Audit logs:","depth":23,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"what data was accessed by which external system when","depth":23,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"identity - who made the request","depth":23,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"specific queries/filters used","depth":23,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"failed access attempts (especially cross-visibility-boundary attempts)","depth":23,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"Admins should be able to access the logs from the org settings.We can start with a csv export before building a specific page for it.","depth":23,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"example from Atlassian -","depth":23,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"Provide customers with example prompts to get started quickly","depth":23,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"HIGH","depth":23,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"MCP prompts are explicitly defined as prompt templates that clients can discover and call with arguments.","depth":23,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"See examples in table below.","depth":23,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"Expose Jiminny as a Connector in Claude","depth":23,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"medium","depth":23,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"Competitors like Fathom are listed as Connectors in Claude. This will make it easier for customers to find us and to connect Jiminny","depth":23,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"Provide customers with example workflows to get started quickly","depth":23,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"medium","depth":23,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"A workflow is usually multiple steps, maybe multiple tools, still focused on one outcome.","depth":23,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"See examples in table below.","depth":23,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"Allow customers to use predefined Jiminny skills for common workflows","depth":23,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"medium","depth":23,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"Anthropic describes Skills as folders that include instructions, scripts, and resources that Claude can load when relevant, and as a way to teach Claude repeatable workflows, preferences, and domain expertise once instead of re-explaining them every time. Skills - a reusable package of behavior that can include prompts, instructions, resources, and sometimes scripts/tools for a broader job.","depth":23,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"Claude skills - https://resources.anthropic.com/hubfs/The-Complete-Guide-to-Building-Skill-for-Claude.pdf?hsLang=en&utm_source=chatgpt.com","depth":23,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"See examples in table below.","depth":23,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"Jiminny UI widget for OpenAI","depth":23,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"medium","depth":23,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"The reason to have this is to make certain Jiminny use cases much easier than pure chat.","depth":23,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"Instead of ChatGPT only replying with text like “Here are the last 5 ACME calls,” it could also show a visual Jiminny card or mini-app inside the chat. That widget could list calls, show a deal summary, let the user filter by rep/date/account, open a transcript section, or save a snippet—while the conversation continues in normal chat alongside it.","depth":23,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"For Jiminny, the best widget use cases are the ones where users need to browse or compare rather than ask one-off questions. A strong example is deal review: the user asks ChatGPT, “What is the status of the ACME deal?” ChatGPT calls your Jiminny MCP tools, and the widget shows a compact deal view with recent calls, risks, next steps, stakeholders, and links to transcripts/snippets. The chat can still summarize the answer in words, but the widget gives a clearer, scannable interface.","depth":23,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"Another good Jiminny widget use case is call search and exploration. A text answer can say “I found 12 calls mentioning pricing objections,” but a widget could show a sortable list with date, rep, account, score, and objection count, then let the user click into one call to see the exact excerpt or jump to a transcript section.","depth":23,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"Allow customers to run long-running analyses asynchronously and retrieve progress/results","depth":23,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"low","depth":23,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"Some requests/questions require analysis of Hugh volumes of data. For those, it may be better to:","depth":23,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"start the job","depth":23,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"let it run in the background","depth":23,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"return a status like “in progress”","depth":23,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"let the client come back for the result later","depth":23,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"For example - User asks in Claude:","depth":23,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"“Analyse all calls from this quarter and tell me the top 5 objections by segment.”","depth":23,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"That might require:","depth":23,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"searching lots of calls","depth":23,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"pulling many summaries/transcripts","depth":23,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"aggregating results","depth":23,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"Instead of making Claude wait 45+ seconds, Jiminny could:","depth":23,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"create an analysis job","depth":23,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"return: job_id = 123, status = running","depth":23,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"We need this in order to support:","depth":23,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"large-scale analysis","depth":23,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"multi-call aggregation across lots of data","depth":23,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"playlist generation across many calls","depth":23,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"heavy recap/report generation","depth":23,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"Creating a snippet through the MCP","depth":23,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"low","depth":23,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"Create a shareable snippet from a call recording by specifying a time range. Useful for highlighting key moments — objection handling, pricing discussions, competitive mentions — and sharing them with your team.","depth":23,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"example request:","depth":23,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"{","depth":23,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"\"tool\": \"create_snippet\",","depth":23,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"\"arguments\": {","depth":23,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"\"call_id\": \"call_123\",","depth":23,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"\"start_time\": \"00:18:24\",","depth":23,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"\"end_time\": \"00:19:10\",","depth":23,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"\"title\": \"Pricing objection\"","depth":23,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"}","depth":23,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"}","depth":23,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"example response:","depth":23,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"{","depth":23,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"\"snippet_id\": \"snip_987\",","depth":23,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"\"title\": \"Pricing objection\",","depth":23,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"\"share_url\": \"https://app.jiminny.com/snippets/snip_987\"","depth":23,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"}","depth":23,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"Ability to add recordings or snippets to a playlist","depth":23,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"low","depth":23,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"Allow customers to create libraries of calls automatically. They can use those for onboarding or other purposes","depth":23,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"Allow AI tools to read reusable Jiminny resources","depth":23,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"low","depth":23,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"fathom","depth":23,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"Resources are useful for data that should be read consistently rather than recomputed every time. In Jiminny terms, that could be:","depth":23,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"current deal snapshot","depth":23,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"account summary","depth":23,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"weekly rep recap","depth":23,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"approved talk tracks / objection handling guidance","depth":23,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"curated playlists or snippet libraries","depth":23,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"This is useful because an AI can consume these directly as context, instead of repeatedly stitching together many tool calls.","depth":23,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"Ability to write coaching notes in Jiminny through MCP","depth":23,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"low","depth":23,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"What we want to do for prompts/worflows and skills","depth":23,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"Capability","depth":23,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"Type","depth":23,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"User value / job to be done","depth":23,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"Example Jiminny use 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Platform Sprint 2 Q2 - Platform Team - Scrum Board Platform Sprint 2 Q2 - Platform Team - Scrum Board - Jira
SevenShores\Hubspot\Exceptions\BadRequest: Client error: `POST [URL_WITH_CREDENTIALS] Graham . I made the product related changes in the table and for the rest I left them as a note in the Technical section for the team to look at when they start looking at this. I wonder about your points related to GDPR. Currently multiple customers are using the Customer API/zapier to feed this data to AI and BI tools. They are also manually exporting transcripts and other information from the platform and feeding it to AI tools. I don’t get how MCP is so much different that all of these and why it will introduce new data processors (which are already being utilised) and would require any changes to the consent provided by participants.
You said
Jiminny MCP Connector
Epic
Link to Epik in Jira
Document status
DRAFT
Objective
Enable customers to connect Jiminny data to external AI tools (Claude, OpenAI, Gemini) so it can be used as part of their broader knowledge base and workflows.
Position Jiminny as a data layer for AI-driven revenue workflows, not just a standalone product.
👤 Target user
Revenue teams using AI tools (Sales, CS, RevOps)
Companies already experimenting with Claude / OpenAI
Mid-market & Enterprise customers with multiple data sources (CRM, docs, CI tools, Support tools etc)
🤕 Pain point or problem
Jiminny data is locked in the platform
AI tools lack access to high-value conversation context
Customers must manually export/copy transcripts
No easy way to combine calls with CRM + docs + other info - using the Jiminny API is not suitable for non technical sales people
Peer pressure as almost all competitors have this
💥 Impact and benefits
For customers
Better AI outputs using real customer conversations
Ability to build automated workflows across tools
For Jiminny
Increased product stickiness (embedded in workflows)
Competitive parity with Gong / Avoma etc.
💡 Solution ideas
Build an AI Knowledge Connector (MCP-based) that:
Exposes Jiminny data (calls, transcripts, metadata) to AI tools
Provides structured insights (summaries, action items, scoring etc.)
Supports deal-level context
Allows integration into customer-owned AI stacks (Claude + Zapier, etc.)
Success metrics
List the key goals and how you will measure success. Include both qualitative and quantitative metrics (e.g., user adoption, retention rate, revenue targets).
Goal
Metric
Increase stickiness by ensuring Jiminny is embedded in the customer’s workflows
% of customers connecting external AI tools
Number of MCP/API calls per customer - and which ones are being used the most
Decrease the manual copying of transcripts
decrease by X %
User interaction and design
Simple setup flow:
Generate API key / connect MCP
Clear instructions for Claude / Zapier setup
Provide:
Example prompts for Claude
Pre-built workflow templates for Zapier
Clear documentation - with use cases
👉 Focus: usable by non-technical users
Detailed Requirements
List the functional and non-functional requirements. Prioritize them (e.g., High, Medium, Low) and add notes for clarification.
Requirement
Importance
Notes
Allow customers to connect Jiminny to their AI tools (e.g. Claude, OpenAI)
HIGH
Provide MCP endpoint so customers can easily integrate Jiminny into their AI stack
Allow customers to access call data through AI tools
HIGH
Expose Jiminny data:
list calls (filter by date, user, account, deal)
get call
get transcript (speaker-separated)
get call metadata
search calls (keyword + semantic)
Support filtering by:
account / contact/ lead / deal
jiminny user
date range
Allow customers to search and query calls using AI tools
HIGH
Support keyword and semantic search across conversations
Provide structured insights so customers can generate better outputs
HIGH
For each call, expose:
Summary
Action items
Key points
Activity type
Notes
Call Score
CRM information
Allow customers to understand deal status across multiple calls/emails
HIGH
For each deal expose:
calls/meetings/emails
Identified risks
contacts related to the deal with their job title
linked account details
all CRM field information that we have in DI + fields used for CRM filling
example - get_deal_summary
request -
{
"tool": "get_deal_summary",
"arguments": {
"deal_name": "ACME"
}
}
responce:
{
"deal_name": "ACME",
"stage": "Negotiation",
"recent_activity": [
"Demo call on 2026-04-01",
"Pricing discussion on 2026-04-03"
],
"risks": [
"Pricing concerns",
"Security review pending"
], "next_steps": [
"Send follow-up to VP Sales",
"Share security documentation"
]
}
Ensure the AI can easily understand the schema of the data coming from Jiminny
HIGH
Models perform much better when tools have:
clear names
rich descriptions
predictable schemas
Provide clear, actionable error states for customers when MCP connections fail
HIGH
Error messages should guide agents toward solutions with specific suggestions and next steps.
Expired or revoked key — “Error: Authentication failed. The API key used to access Jiminny has been revoked or has expired. Please ask your Jiminny admin to generate a new API key in Settings > Organization > General and reconnect the MCP server.”
Rate limit hit — “Error: Rate limit exceeded. Too many requests have been made to the Jiminny MCP server in a short period. Please wait 60 seconds before retrying.”
Permissions mismatch — if a user tries to access data outside their team visibility settings - “Error: Access denied. The requested call (call_id: [X]) is outside your team's visibility settings in Jiminny. Only calls within your permitted scope are accessible.”
Trying to access private meeting - “Error: Access denied. This meeting has been marked as private by the host and cannot be accessed through the MCP connector. Try requesting a different call or ask the meeting host to change the visibility settings in Jiminny.”
Downgraded/Capture account — if a customer's plan drops below Scale tier or the Customer is on Capture in the first place - “Error: MCP access unavailable. The Jiminny MCP connector is available on the Scale plan and above. Your account does not currently have an active Scale subscription.”
Jiminny-side outage — “Error:Jiminny is temporarily unavailable (status 503). This is not a data or permissions issue — please retry in a few minutes.”
No data found - “Error:No calls found matching your criteria. Try adjusting your filters — for example, widening the date range, removing the account filter, or checking the rep name is spelled correctly in Jiminny.”
Allow customers to securely control who and what data is accessible externally
HIGH
Ensure MCP only exposes data user has access to - based on team visibility settings. This means that if a user is not allow to access calls/deals in Jiminny UI then they shouldn’t be able to access those through the MCP as well.
Private meetings shouldn’t be exposed via MCP
HIGH
When a meetings is set to Private then the information about it shouldn’t be exposed through the MCP.
Ensure Jiminny data can be combined with other sources (e.g. CRM, docs) in AI workflows
HIGH
Ensure data is structured to be easily combined with:
CRM (accounts, deals)
external docs
Use consistent identifiers:
account IDs
deal IDs
MCP is available only for Scale tier and above
HIGH
Customers who are on Capture tier should be able to access any of their data through MCP.
This should also cover the scenario when a customer has been on Scale but then downgrades to Capture - their MCP access should stop working.
Provide visibility into how external AI tools access Jiminny data
HIGH
Audit logs:
what data was accessed by which external system when
identity - who made the request
specific queries/filters used
failed access attempts (especially cross-visibility-boundary attempts)
Admins should be able to access the logs from the org settings.We can start with a csv export before building a specific page for it.
example from Atlassian -
Provide customers with example prompts to get started quickly
HIGH
MCP prompts are explicitly defined as prompt templates that clients can discover and call with arguments.
See examples in table below.
Expose Jiminny as a Connector in Claude
medium
Competitors like Fathom are listed as Connectors in Claude. This will make it easier for customers to find us and to connect Jiminny
Provide customers with example workflows to get started quickly
medium
A workflow is usually multiple steps, maybe multiple tools, still focused on one outcome.
See examples in table below.
Allow customers to use predefined Jiminny skills for common workflows
medium
Anthropic describes Skills as folders that include instructions, scripts, and resources that Claude can load when relevant, and as a way to teach Claude repeatable workflows, preferences, and domain expertise once instead of re-explaining them every time. Skills - a reusable package of behavior that can include prompts, instructions, resources, and sometimes scripts/tools for a broader job.
Claude skills - https://resources.anthropic.com/hubfs/The-Complete-Guide-to-Building-Skill-for-Claude.pdf?hsLang=en&utm_source=chatgpt.com
See examples in table below.
Jiminny UI widget for OpenAI
medium
The reason to have this is to make certain Jiminny use cases much easier than pure chat.
Instead of ChatGPT only replying with text like “Here are the last 5 ACME calls,” it could also show a visual Jiminny card or mini-app inside the chat. That widget could list calls, show a deal summary, let the user filter by rep/date/account, open a transcript section, or save a snippet—while the conversation continues in normal chat alongside it.
For Jiminny, the best widget use cases are the ones where users need to browse or compare rather than ask one-off questions. A strong example is deal review: the user asks ChatGPT, “What is the status of the ACME deal?” ChatGPT calls your Jiminny MCP tools, and the widget shows a compact deal view with recent calls, risks, next steps, stakeholders, and links to transcripts/snippets. The chat can still summarize the answer in words, but the widget gives a clearer, scannable interface.
Another good Jiminny widget use case is call search and exploration. A text answer can say “I found 12 calls mentioning pricing objections,” but a widget could show a sortable list with date, rep, account, score, and objection count, then let the user click into one call to see the exact excerpt or jump to a transcript section.
Allow customers to run long-running analyses asynchronously and retrieve progress/results
low
Some requests/questions require analysis of Hugh volumes of data. For those, it may be better to:
start the job
let it run in the background
return a status like “in progress”
let the client come back for the result later
For example - User asks in Claude:
“Analyse all calls from this quarter and tell me the top 5 objections by segment.”
That might require:
searching lots of calls
pulling many summaries/transcripts
aggregating results
Instead of making Claude wait 45+ seconds, Jiminny could:
create an analysis job
return: job_id = 123, status = running
We need this in order to support:
large-scale analysis
multi-call aggregation across lots of data
playlist generation across many calls
heavy recap/report generation
Creating a snippet through the MCP
low
Create a shareable snippet from a call recording by specifying a time range. Useful for highlighting key moments — objection handling, pricing discussions, competitive mentions — and sharing them with your team.
example request:
{
"tool": "create_snippet",
"arguments": {
"call_id": "call_123",
"start_time": "00:18:24",
"end_time": "00:19:10",
"title": "Pricing objection"
}
}
example response:
{
"snippet_id": "snip_987",
"title": "Pricing objection",
"share_url": "https://app.jiminny.com/snippets/snip_987"
}
Ability to add recordings or snippets to a playlist
low
Allow customers to create libraries of calls automatically. They can use those for onboarding or other purposes
Allow AI tools to read reusable Jiminny resources
low
fathom
Resources are useful for data that should be read consistently rather than recomputed every time. In Jiminny terms, that could be:
current deal snapshot
account summary
weekly rep recap
approved talk tracks / objection handling guidance
curated playlists or snippet libraries
This is useful because an AI can consume these directly as context, instead of repeatedly stitching together many tool calls.
Ability to write coaching notes in Jiminny through MCP
low
What we want to do for prompts/worflows and skills
Capability
Type
User value / job to be done
Example Jiminny use case
Inputs
Steps performed
Output
Draft follow-up email
Prompt
Help reps quickly create tailored follow-ups after calls
Use the latest customer call to draft an email with recap and next steps
Call ID
optional tone
optional recipient type
Retrieve call summary and action items from Jiminny.
Pull key points, commitments, and next steps.
Apply the chosen tone and structure.
Draft the email in a consistent format.
Customer-ready follow-up email draft
Summarise call
Prompt
Help users quickly extract the most important points from a conversation
Generate a concise summary of one call for internal or external use
Call ID
optional summary style
optional audience
Retrieve transcript, metadata, and structured insights.
Identify key topics, decisions, risks, and next steps.
Format output for the chosen audience.
Short or structured call summary with actions and risks
Generate deal recap
Prompt
Help reps and managers get a fast overview of a deal
Summarise the current state of a deal based on recent calls and linked CRM context
Deal ID or account name
optional date range
Retrieve calls and meetings linked to the deal.
Pull deal metadata and CRM-linked context.
Identify recent changes, blockers, risks, and next steps.
Summarise into a concise recap.
Deal recap with status, blockers, risks, and recommended next steps
Prepare weekly recap
Prompt
Help managers or reps review what changed over a time period
Weekly recap of calls, themes, and actions for one rep, team, or account
Rep ID
team ID or account ID
time period
Retrieve relevant calls and summaries for the selected time period.
Aggregate themes, action items, and changes.
Highlight notable risks, opportunities, and follow-ups.
Weekly recap with top themes, risks, opportunities, and actions
Prepare deal review
Workflow
Help reps and managers review deal status using multiple sources of context
Review a deal before pipeline review or forecast meeting
Deal ID
optional date range
Retrieve all recent calls, emails, and meetings tied to the deal.
Pull structured call summaries, score, action items, and key points.
Pull linked CRM context such as stage, contacts, and account details.
Aggregate open risks, unresolved objections, stakeholder gaps, and next steps.
Format into a review-ready structure.
Deal review document with current status, risks, stakeholders, blockers, and next steps
Weekly team recap
Workflow
Help managers monitor activity and risk across a group of reps or accounts
End-of-week team summary for sales leadership
Team ID
date range
Retrieve calls and structured insights across the team.
Group by rep, account, or deal.
Identify recurring themes, major risks, strong calls, and missed follow-ups.
Highlight calls or deals that need attention.
Team-level recap with patterns, key risks, notable wins, and action areas
Objection analysis across calls
Workflow
Help teams identify patterns across multiple conversations
Analyse pricing or competitor objections across recent calls
Account ID
deal ID
rep ID
keyword/topic
date range
Search calls matching the topic or keyword.
Retrieve summaries, transcripts, and snippets where relevant.
Identify recurring objections and how they were handled.
Assess whether objections were resolved or remain open.
Summarise patterns and examples.
Objection analysis with themes, frequency, examples, and suggested follow-up actions
Build onboarding playlist
Workflow
Help enablement teams curate useful learning content faster
Build a playlist of strong discovery, demo, or pricing calls for new hires
Topic
call type
rep/team filter
optional time period
Search for calls matching the selected criteria.
Rank or filter calls based on score, topics, or key moments.
Identify useful snippets or full recordings.
Add selected calls/snippets into a playlist structure.
Generate short descriptions for each item.
Curated onboarding playlist with selected calls/snippets and descriptions
Deal Inspection Skill
Skill
Give users a consistent, opinionated way to assess a deal
Claude reviews a deal using a repeatable Jiminny methodology
Deal ID or account name
optional review scope
Determine whether the request is suitable for a deal inspection.
Retrieve relevant calls, summaries, CRM context, stakeholders, and risks.
Apply a standard Jiminny review framework to assess deal health.
Look for missing next steps, unresolved objections, stakeholder gaps, and warning signs.
Present findings in a consistent structure with recommended actions.
Structured deal inspection with health assessment, red flags, and recommendations
Manager Coaching Skill
Skill
Help managers review calls consistently and identify coaching moments
Analyse a rep’s call and surface strengths, gaps, and examples for coaching
Call ID
optional rep ID
optional coaching focus
Retrieve transcript, score, summary, and key moments from the call.
Evaluate the conversation against a coaching framework.
Identify what went well and where the rep could improve.
Suggest moments to clip as snippets.
Recommend coaching actions or playlist additions.
Coaching review with strengths, gaps, snippet suggestions, and recommended coaching actions
CSM / QBR Prep Skill
Skill
Help CS or AM teams prepare structured customer reviews from conversations
Generate an account review or QBR-style summary from recent customer interactions
Account ID, optional time period
Retrieve all recent calls, emails, and account-linked context.
Aggregate themes, requests, blockers, sentiment shifts, and opportunities.
Apply a repeatable account review structure.
Summarise outcomes, open issues, and suggested next steps.
Structured QBR/account review summary with themes, risks, opportunities, and actions
Snippet Builder Skill
Skill
Help users consistently capture and label useful moments from calls
Identify useful moments in a call and convert them into reusable snippets
Call ID, optional focus area such as pricing, objection, competitor, discovery
Retrieve transcript, recording timeline, and call insights.
Detect moments matching the requested focus area.
Propose snippet start/end times and titles.
Tag snippets by type or theme.
Optionally save them or add them to a playlist.
One or more proposed or saved snippets with title, timing, and tags
💡 Technical details
Auth model needs specifying. Are API keys scoped per user, per team, or per Jiminny instance? If a key is generated by an admin, does it inherit their visibility level, or provide org-wide? Are permissions evaluated at query time or frozen at key creation? Needs to be query-time, otherwise permission changes won't propagate.
Key lifecycle management is missing. No mention of rotation, expiry, or revocation. A departed employee's active key is a data leak. Need: revocation, optional expiry, alerts on stale keys, and consider whether keys should be tied to service accounts rather than personal users.
Rate limiting should be HIGH. A compromised key or misconfigured automation could bulk-export an entire customer's call history. Need per-key rate limits and anomaly detection on unusual access patterns.
Open Questions
Track unresolved issues or decisions that need to be made. Update as answers become available.
Question
Answer
Date Answered
Competitor research
Competitor
MCP Availability
Core Capabilities
Advanced Capabilities
Positioning
Key Strength
Key Weakness
Gong
✅ Mature MCP
List/search calls
Get transcripts
get Call metadata
Deal intelligence
Scorecards, analytics
CRM context
Enterprise data layer
Deep data + ecosystem integrations
Limited opinionated AI workflows
Avoma
✅ Mature MCP
list_meetings
get_meeting
get_transcript
key topics
Deal fields/Deal level analysis
Coaching/Scoring
CRM context
pushing insights into Notion / Confluence
AI-ready meeting intelligence
Strongest “outputs” layer
Mostly pull-based interactions
Fathom
✅ MCP
list/search meetings
get transcript
get summary/action items
Team/org context
Webhooks (event-based triggers)
get_weekly_recap
aggregated action items across meetings
creating webhooks directly from the MCP server
Lightweight meeting data access
Includes summaries + actions
Limited analytics depth
Grain
✅ Basic MCP
get meetings
download transcripts
Notes
Deals
Scorecards
Data access utility
Simple + accessible
Low sophistication, sometimes browser-based
Outreach
⚠️ MCP (workflow-focused)...
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Architecture overview - Model Context Protocol — W Architecture overview - Model Context Protocol — Work...
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Platform Sprint 2 Q2 - Platform Team - Scrum Board Platform Sprint 2 Q2 - Platform Team - Scrum Board - Jira
SevenShores\Hubspot\Exceptions\BadRequest: Client error: `POST [URL_WITH_CREDENTIALS] Graham . I made the product related changes in the table and for the rest I left them as a note in the Technical section for the team to look at when they start looking at this. I wonder about your points related to GDPR. Currently multiple customers are using the Customer API/zapier to feed this data to AI and BI tools. They are also manually exporting transcripts and other information from the platform and feeding it to AI tools. I don’t get how MCP is so much different that all of these and why it will introduce new data processors (which are already being utilised) and would require any changes to the consent provided by participants.
You said
Jiminny MCP Connector
Epic
Link to Epik in Jira
Document status
DRAFT
Objective
Enable customers to connect Jiminny data to external AI tools (Claude, OpenAI, Gemini) so it can be used as part of their broader knowledge base and workflows.
Position Jiminny as a data layer for AI-driven revenue workflows, not just a standalone product.
👤 Target user
Revenue teams using AI tools (Sales, CS, RevOps)
Companies already experimenting with Claude / OpenAI
Mid-market & Enterprise customers with multiple data sources (CRM, docs, CI tools, Support tools etc)
🤕 Pain point or problem
Jiminny data is locked in the platform
AI tools lack access to high-value conversation context
Customers must manually export/copy transcripts
No easy way to combine calls with CRM + docs + other info - using the Jiminny API is not suitable for non technical sales people
Peer pressure as almost all competitors have this
💥 Impact and benefits
For customers
Better AI outputs using real customer conversations
Ability to build automated workflows across tools
For Jiminny
Increased product stickiness (embedded in workflows)
Competitive parity with Gong / Avoma etc.
💡 Solution ideas
Build an AI Knowledge Connector (MCP-based) that:
Exposes Jiminny data (calls, transcripts, metadata) to AI tools
Provides structured insights (summaries, action items, scoring etc.)
Supports deal-level context
Allows integration into customer-owned AI stacks (Claude + Zapier, etc.)
Success metrics
List the key goals and how you will measure success. Include both qualitative and quantitative metrics (e.g., user adoption, retention rate, revenue targets).
Goal
Metric
Increase stickiness by ensuring Jiminny is embedded in the customer’s workflows
% of customers connecting external AI tools
Number of MCP/API calls per customer - and which ones are being used the most
Decrease the manual copying of transcripts
decrease by X %
User interaction and design
Simple setup flow:
Generate API key / connect MCP
Clear instructions for Claude / Zapier setup
Provide:
Example prompts for Claude
Pre-built workflow templates for Zapier
Clear documentation - with use cases
👉 Focus: usable by non-technical users
Detailed Requirements
List the functional and non-functional requirements. Prioritize them (e.g., High, Medium, Low) and add notes for clarification.
Requirement
Importance
Notes
Allow customers to connect Jiminny to their AI tools (e.g. Claude, OpenAI)
HIGH
Provide MCP endpoint so customers can easily integrate Jiminny into their AI stack
Allow customers to access call data through AI tools
HIGH
Expose Jiminny data:
list calls (filter by date, user, account, deal)
get call
get transcript (speaker-separated)
get call metadata
search calls (keyword + semantic)
Support filtering by:
account / contact/ lead / deal
jiminny user
date range
Allow customers to search and query calls using AI tools
HIGH
Support keyword and semantic search across conversations
Provide structured insights so customers can generate better outputs
HIGH
For each call, expose:
Summary
Action items
Key points
Activity type
Notes
Call Score
CRM information
Allow customers to understand deal status across multiple calls/emails
HIGH
For each deal expose:
calls/meetings/emails
Identified risks
contacts related to the deal with their job title
linked account details
all CRM field information that we have in DI + fields used for CRM filling
example - get_deal_summary
request -
{
"tool": "get_deal_summary",
"arguments": {
"deal_name": "ACME"
}
}
responce:
{
"deal_name": "ACME",
"stage": "Negotiation",
"recent_activity": [
"Demo call on 2026-04-01",
"Pricing discussion on 2026-04-03"
],
"risks": [
"Pricing concerns",
"Security review pending"
], "next_steps": [
"Send follow-up to VP Sales",
"Share security documentation"
]
}
Ensure the AI can easily understand the schema of the data coming from Jiminny
HIGH
Models perform much better when tools have:
clear names
rich descriptions
predictable schemas
Provide clear, actionable error states for customers when MCP connections fail
HIGH
Error messages should guide agents toward solutions with specific suggestions and next steps.
Expired or revoked key — “Error: Authentication failed. The API key used to access Jiminny has been revoked or has expired. Please ask your Jiminny admin to generate a new API key in Settings > Organization > General and reconnect the MCP server.”
Rate limit hit — “Error: Rate limit exceeded. Too many requests have been made to the Jiminny MCP server in a short period. Please wait 60 seconds before retrying.”
Permissions mismatch — if a user tries to access data outside their team visibility settings - “Error: Access denied. The requested call (call_id: [X]) is outside your team's visibility settings in Jiminny. Only calls within your permitted scope are accessible.”
Trying to access private meeting - “Error: Access denied. This meeting has been marked as private by the host and cannot be accessed through the MCP connector. Try requesting a different call or ask the meeting host to change the visibility settings in Jiminny.”
Downgraded/Capture account — if a customer's plan drops below Scale tier or the Customer is on Capture in the first place - “Error: MCP access unavailable. The Jiminny MCP connector is available on the Scale plan and above. Your account does not currently have an active Scale subscription.”
Jiminny-side outage — “Error:Jiminny is temporarily unavailable (status 503). This is not a data or permissions issue — please retry in a few minutes.”
No data found - “Error:No calls found matching your criteria. Try adjusting your filters — for example, widening the date range, removing the account filter, or checking the rep name is spelled correctly in Jiminny.”
Allow customers to securely control who and what data is accessible externally
HIGH
Ensure MCP only exposes data user has access to - based on team visibility settings. This means that if a user is not allow to access calls/deals in Jiminny UI then they shouldn’t be able to access those through the MCP as well.
Private meetings shouldn’t be exposed via MCP
HIGH
When a meetings is set to Private then the information about it shouldn’t be exposed through the MCP.
Ensure Jiminny data can be combined with other sources (e.g. CRM, docs) in AI workflows
HIGH
Ensure data is structured to be easily combined with:
CRM (accounts, deals)
external docs
Use consistent identifiers:
account IDs
deal IDs
MCP is available only for Scale tier and above
HIGH
Customers who are on Capture tier should be able to access any of their data through MCP.
This should also cover the scenario when a customer has been on Scale but then downgrades to Capture - their MCP access should stop working.
Provide visibility into how external AI tools access Jiminny data
HIGH
Audit logs:
what data was accessed by which external system when
identity - who made the request
specific queries/filters used
failed access attempts (especially cross-visibility-boundary attempts)
Admins should be able to access the logs from the org settings.We can start with a csv export before building a specific page for it.
example from Atlassian -
Provide customers with example prompts to get started quickly
HIGH
MCP prompts are explicitly defined as prompt templates that clients can discover and call with arguments.
See examples in table below.
Expose Jiminny as a Connector in Claude
medium
Competitors like Fathom are listed as Connectors in Claude. This will make it easier for customers to find us and to connect Jiminny
Provide customers with example workflows to get started quickly
medium
A workflow is usually multiple steps, maybe multiple tools, still focused on one outcome.
See examples in table below.
Allow customers to use predefined Jiminny skills for common workflows
medium
Anthropic describes Skills as folders that include instructions, scripts, and resources that Claude can load when relevant, and as a way to teach Claude repeatable workflows, preferences, and domain expertise once instead of re-explaining them every time. Skills - a reusable package of behavior that can include prompts, instructions, resources, and sometimes scripts/tools for a broader job.
Claude skills - https://resources.anthropic.com/hubfs/The-Complete-Guide-to-Building-Skill-for-Claude.pdf?hsLang=en&utm_source=chatgpt.com
See examples in table below.
Jiminny UI widget for OpenAI
medium
The reason to have this is to make certain Jiminny use cases much easier than pure chat.
Instead of ChatGPT only replying with text like “Here are the last 5 ACME calls,” it could also show a visual Jiminny card or mini-app inside the chat. That widget could list calls, show a deal summary, let the user filter by rep/date/account, open a transcript section, or save a snippet—while the conversation continues in normal chat alongside it.
For Jiminny, the best widget use cases are the ones where users need to browse or compare rather than ask one-off questions. A strong example is deal review: the user asks ChatGPT, “What is the status of the ACME deal?” ChatGPT calls your Jiminny MCP tools, and the widget shows a compact deal view with recent calls, risks, next steps, stakeholders, and links to transcripts/snippets. The chat can still summarize the answer in words, but the widget gives a clearer, scannable interface.
Another good Jiminny widget use case is call search and exploration. A text answer can say “I found 12 calls mentioning pricing objections,” but a widget could show a sortable list with date, rep, account, score, and objection count, then let the user click into one call to see the exact excerpt or jump to a transcript section.
Allow customers to run long-running analyses asynchronously and retrieve progress/results
low
Some requests/questions require analysis of Hugh volumes of data. For those, it may be better to:
start the job
let it run in the background
return a status like “in progress”
let the client come back for the result later
For example - User asks in Claude:
“Analyse all calls from this quarter and tell me the top 5 objections by segment.”
That might require:
searching lots of calls
pulling many summaries/transcripts
aggregating results
Instead of making Claude wait 45+ seconds, Jiminny could:
create an analysis job
return: job_id = 123, status = running
We need this in order to support:
large-scale analysis
multi-call aggregation across lots of data
playlist generation across many calls
heavy recap/report generation
Creating a snippet through the MCP
low
Create a shareable snippet from a call recording by specifying a time range. Useful for highlighting key moments — objection handling, pricing discussions, competitive mentions — and sharing them with your team.
example request:
{
"tool": "create_snippet",
"arguments": {
"call_id": "call_123",
"start_time": "00:18:24",
"end_time": "00:19:10",
"title": "Pricing objection"
}
}
example response:
{
"snippet_id": "snip_987",
"title": "Pricing objection",
"share_url": "https://app.jiminny.com/snippets/snip_987"
}
Ability to add recordings or snippets to a playlist
low
Allow customers to create libraries of calls automatically. They can use those for onboarding or other purposes
Allow AI tools to read reusable Jiminny resources
low
fathom
Resources are useful for data that should be read consistently rather than recomputed every time. In Jiminny terms, that could be:
current deal snapshot
account summary
weekly rep recap
approved talk tracks / objection handling guidance
curated playlists or snippet libraries
This is useful because an AI can consume these directly as context, instead of repeatedly stitching together many tool calls.
Ability to write coaching notes in Jiminny through MCP
low
What we want to do for prompts/worflows and skills
Capability
Type
User value / job to be done
Example Jiminny use case
Inputs
Steps performed
Output
Draft follow-up email
Prompt
Help reps quickly create tailored follow-ups after calls
Use the latest customer call to draft an email with recap and next steps
Call ID
optional tone
optional recipient type
Retrieve call summary and action items from Jiminny.
Pull key points, commitments, and next steps.
Apply the chosen tone and structure.
Draft the email in a consistent format.
Customer-ready follow-up email draft
Summarise call
Prompt
Help users quickly extract the most important points from a conversation
Generate a concise summary of one call for internal or external use
Call ID
optional summary style
optional audience
Retrieve transcript, metadata, and structured insights.
Identify key topics, decisions, risks, and next steps.
Format output for the chosen audience.
Short or structured call summary with actions and risks
Generate deal recap
Prompt
Help reps and managers get a fast overview of a deal
Summarise the current state of a deal based on recent calls and linked CRM context
Deal ID or account name
optional date range
Retrieve calls and meetings linked to the deal.
Pull deal metadata and CRM-linked context.
Identify recent changes, blockers, risks, and next steps.
Summarise into a concise recap.
Deal recap with status, blockers, risks, and recommended next steps
Prepare weekly recap
Prompt
Help managers or reps review what changed over a time period
Weekly recap of calls, themes, and actions for one rep, team, or account
Rep ID
team ID or account ID
time period
Retrieve relevant calls and summaries for the selected time period.
Aggregate themes, action items, and changes.
Highlight notable risks, opportunities, and follow-ups.
Weekly recap with top themes, risks, opportunities, and actions
Prepare deal review
Workflow
Help reps and managers review deal status using multiple sources of context
Review a deal before pipeline review or forecast meeting
Deal ID
optional date range
Retrieve all recent calls, emails, and meetings tied to the deal.
Pull structured call summaries, score, action items, and key points.
Pull linked CRM context such as stage, contacts, and account details.
Aggregate open risks, unresolved objections, stakeholder gaps, and next steps.
Format into a review-ready structure.
Deal review document with current status, risks, stakeholders, blockers, and next steps
Weekly team recap
Workflow
Help managers monitor activity and risk across a group of reps or accounts
End-of-week team summary for sales leadership
Team ID
date range
Retrieve calls and structured insights across the team.
Group by rep, account, or deal.
Identify recurring themes, major risks, strong calls, and missed follow-ups.
Highlight calls or deals that need attention.
Team-level recap with patterns, key risks, notable wins, and action areas
Objection analysis across calls
Workflow
Help teams identify patterns across multiple conversations
Analyse pricing or competitor objections across recent calls
Account ID
deal ID
rep ID
keyword/topic
date range
Search calls matching the topic or keyword.
Retrieve summaries, transcripts, and snippets where relevant.
Identify recurring objections and how they were handled.
Assess whether objections were resolved or remain open.
Summarise patterns and examples.
Objection analysis with themes, frequency, examples, and suggested follow-up actions
Build onboarding playlist
Workflow
Help enablement teams curate useful learning content faster
Build a playlist of strong discovery, demo, or pricing calls for new hires
Topic
call type
rep/team filter
optional time period
Search for calls matching the selected criteria.
Rank or filter calls based on score, topics, or key moments.
Identify useful snippets or full recordings.
Add selected calls/snippets into a playlist structure.
Generate short descriptions for each item.
Curated onboarding playlist with selected calls/snippets and descriptions
Deal Inspection Skill
Skill
Give users a consistent, opinionated way to assess a deal
Claude reviews a deal using a repeatable Jiminny methodology
Deal ID or account name
optional review scope
Determine whether the request is suitable for a deal inspection.
Retrieve relevant calls, summaries, CRM context, stakeholders, and risks.
Apply a standard Jiminny review framework to assess deal health.
Look for missing next steps, unresolved objections, stakeholder gaps, and warning signs.
Present findings in a consistent structure with recommended actions.
Structured deal inspection with health assessment, red flags, and recommendations
Manager Coaching Skill
Skill
Help managers review calls consistently and identify coaching moments
Analyse a rep’s call and surface strengths, gaps, and examples for coaching
Call ID
optional rep ID
optional coaching focus
Retrieve transcript, score, summary, and key moments from the call.
Evaluate the conversation against a coaching framework.
Identify what went well and where the rep could improve.
Suggest moments to clip as snippets.
Recommend coaching actions or playlist additions.
Coaching review with strengths, gaps, snippet suggestions, and recommended coaching actions
CSM / QBR Prep Skill
Skill
Help CS or AM teams prepare structured customer reviews from conversations
Generate an account review or QBR-style summary from recent customer interactions
Account ID, optional time period
Retrieve all recent calls, emails, and account-linked context.
Aggregate themes, requests, blockers, sentiment shifts, and opportunities.
Apply a repeatable account review structure.
Summarise outcomes, open issues, and suggested next steps.
Structured QBR/account review summary with themes, risks, opportunities, and actions
Snippet Builder Skill
Skill
Help users consistently capture and label useful moments from calls
Identify useful moments in a call and convert them into reusable snippets
Call ID, optional focus area such as pricing, objection, competitor, discovery
Retrieve transcript, recording timeline, and call insights.
Detect moments matching the requested focus area.
Propose snippet start/end times and titles.
Tag snippets by type or theme.
Optionally save them or add them to a playlist.
One or more proposed or saved snippets with title, timing, and tags
💡 Technical details
Auth model needs specifying. Are API keys scoped per user, per team, or per Jiminny instance? If a key is generated by an admin, does it inherit their visibility level, or provide org-wide? Are permissions evaluated at query time or frozen at key creation? Needs to be query-time, otherwise permission changes won't propagate.
Key lifecycle management is missing. No mention of rotation, expiry, or revocation. A departed employee's active key is a data leak. Need: revocation, optional expiry, alerts on stale keys, and consider whether keys should be tied to service accounts rather than personal users.
Rate limiting should be HIGH. A compromised key or misconfigured automation could bulk-export an entire customer's call history. Need per-key rate limits and anomaly detection on unusual access patterns.
Open Questions
Track unresolved issues or decisions that need to be made. Update as answers become available.
Question
Answer
Date Answered
Competitor research
Competitor
MCP Availability
Core Capabilities
Advanced Capabilities
Positioning
Key Strength
Key Weakness
Gong
✅ Mature MCP
List/search calls
Get transcripts
get Call metadata
Deal intelligence
Scorecards, analytics
CRM context
Enterprise data layer
Deep data + ecosystem integrations
Limited opinionated AI workflows
Avoma
✅ Mature MCP
list_meetings
get_meeting
get_transcript
key topics
Deal fields/Deal level analysis
Coaching/Scoring
CRM context
pushing insights into Notion / Confluence
AI-ready meeting intelligence
Strongest “outputs” layer
Mostly pull-based interactions
Fathom
✅ MCP
list/search meetings
get transcript
get summary/action items
Team/org context
Webhooks (event-based triggers)
get_weekly_recap
aggregated action items across meetings
creating webhooks directly from the MCP server
Lightweight meeting data access
Includes summaries + actions
Limited analytics depth
Grain
✅ Basic MCP
get meetings
download transcripts
Notes
Deals
Scorecards
Data access utility
Simple + accessible
Low sophistication, sometimes browser-based
Outreach
⚠️ MCP (workflow-focused)
Search sequences
Emails
Meetings (Kaia)
account / prospect / opportunity lookups
Workflow automation
Multi-system orchestration
Revenue workflow engine
End-to-end GTM workflows
Less depth in conversation data
Attention
⚠️ Emerging MCP
Meeting data
Transcripts
CRM-linked context
AI insights
Sales assistant workflows
create snippets
AI sales assistant + CRM
Strong CRM linkage
Less focus on external knowledge layer
Planhat -
Related content
Ask Jiminny Anything on Call level
Galya Dimitrova
Hubspot app
Galya Dimitrova
Product Vision & Strategy
Galya Dimitrova
Automated CRM Filling
Simona Georgieva (Deactivated)
Competitive analysis
Galya Dimitrova
AI agent ideas
Steliyan Georgiev
Comments
James Graham
9 Apr
A few areas around Security & Compliance that need more depth before this moves beyond draft:
Auth model needs specifying. Are API keys scoped per user, per team, or per Jiminny instance? If a key is generated by an admin, does it inherit their visibility level, or provide org-wide? Are permissions evaluated at query time or frozen at key creation? Needs to be query-time, otherwise permission changes won't propagate.
Team visibility enforcement should be its own HIGH requirement. The current note under access control ("ensure MCP only exposes data user has access to") is doing too much work as a single line. Every MCP tool response (especially search_calls and deal-level aggregations) must be filtered through the same visibility engine as the UI. Semantic search is the riskiest here; it could surface results across team boundaries if not properly scoped.
No data minimisation or scoping controls. We're exposing transcripts, CRM fields, contact details with job titles, deal context - significant PII and commercial data leaving the platform. Can customers configure which data types are exposed? Can transcripts be PII-stripped before they leave Jiminny? Given we position GDPR consent as a differentiator, we should be thinking about this.
GDPR downstream processing is unaddressed. Piping transcripts to OpenAI/Gemini introduces new data processors. Customers need to acknowledge responsibility for downstream processing during setup. We should also consider whether call participants' recording consent covers onward sharing to third-party AI - it almost certainly doesn't by default. This is one for me to pick up.
Key lifecycle management is missing. No mention of rotation, expiry, or revocation. A departed employee's active key is a data leak. Need: revocation, optional expiry, alerts on stale keys, and consider whether keys should be tied to service accounts rather than personal users.
Rate limiting should be HIGH. A compromised key or misconfigured automation could bulk-export an entire customer's call history. Need per-key rate limits and anomaly detection on unusual ac...
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Position Jiminny as a data layer for AI-driven revenue workflows, not just a standalone product. 👤 Target user Revenue teams using AI tools (Sales, CS, RevOps) Companies already experimenting with Claude / OpenAI Mid-market & Enterprise customers with multiple data sources (CRM, docs, CI tools, Support tools etc) 🤕 Pain point or problem Jiminny data is locked in the platform AI tools lack access to high-value conversation context Customers must manually export/copy transcripts No easy way to combine calls with CRM + docs + other info - using the Jiminny API is not suitable for non technical sales people Peer pressure as almost all competitors have this 💥 Impact and benefits For customers Better AI outputs using real customer conversations Ability to build automated workflows across tools For Jiminny Increased product stickiness (embedded in workflows) Competitive parity with Gong / Avoma etc. 💡 Solution ideas Build an AI Knowledge Connector (MCP-based) that: Exposes Jiminny data (calls, transcripts, metadata) to AI tools Provides structured insights (summaries, action items, scoring etc.) Supports deal-level context Allows integration into customer-owned AI stacks (Claude + Zapier, etc.) Success metrics List the key goals and how you will measure success. Include both qualitative and quantitative metrics (e.g., user adoption, retention rate, revenue targets). Goal Metric Increase stickiness by ensuring Jiminny is embedded in the customer’s workflows % of customers connecting external AI tools Number of MCP/API calls per customer - and which ones are being used the most Decrease the manual copying of transcripts decrease by X % User interaction and design Simple setup flow: Generate API key / connect MCP Clear instructions for Claude / Zapier setup Provide: Example prompts for Claude Pre-built workflow templates for Zapier Clear documentation - with use cases 👉 Focus: usable by non-technical users Detailed Requirements List the functional and non-functional requirements. Prioritize them (e.g., High, Medium, Low) and add notes for clarification. Requirement Importance Notes Allow customers to connect Jiminny to their AI tools (e.g. Claude, OpenAI) HIGH Provide MCP endpoint so customers can easily integrate Jiminny into their AI stack Allow customers to access call data through AI tools HIGH Expose Jiminny data: list calls (filter by date, user, account, deal) get call get transcript (speaker-separated) get call metadata search calls (keyword + semantic) Support filtering by: account / contact/ lead / deal jiminny user date range Allow customers to search and query calls using AI tools HIGH Support keyword and semantic search across conversations Provide structured insights so customers can generate better outputs HIGH For each call, expose: Summary Action items Key points Activity type Notes Call Score CRM information Allow customers to understand deal status across multiple calls/emails HIGH For each deal expose: calls/meetings/emails Identified risks contacts related to the deal with their job title linked account details all CRM field information that we have in DI + fields used for CRM filling example - get_deal_summary request - { \"tool\": \"get_deal_summary\", \"arguments\": { \"deal_name\": \"ACME\" } } responce: { \"deal_name\": \"ACME\", \"stage\": \"Negotiation\", \"recent_activity\": [ \"Demo call on 2026-04-01\", \"Pricing discussion on 2026-04-03\" ], \"risks\": [ \"Pricing concerns\", \"Security review pending\" ], \"next_steps\": [ \"Send follow-up to VP Sales\", \"Share security documentation\" ] } Ensure the AI can easily understand the schema of the data coming from Jiminny HIGH Models perform much better when tools have: clear names rich descriptions predictable schemas Provide clear, actionable error states for customers when MCP connections fail HIGH Error messages should guide agents toward solutions with specific suggestions and next steps. Expired or revoked key — “Error: Authentication failed. The API key used to access Jiminny has been revoked or has expired. Please ask your Jiminny admin to generate a new API key in Settings > Organization > General and reconnect the MCP server.” Rate limit hit — “Error: Rate limit exceeded. Too many requests have been made to the Jiminny MCP server in a short period. Please wait 60 seconds before retrying.” Permissions mismatch — if a user tries to access data outside their team visibility settings - “Error: Access denied. The requested call (call_id: [X]) is outside your team's visibility settings in Jiminny. Only calls within your permitted scope are accessible.” Trying to access private meeting - “Error: Access denied. This meeting has been marked as private by the host and cannot be accessed through the MCP connector. Try requesting a different call or ask the meeting host to change the visibility settings in Jiminny.” Downgraded/Capture account — if a customer's plan drops below Scale tier or the Customer is on Capture in the first place - “Error: MCP access unavailable. The Jiminny MCP connector is available on the Scale plan and above. Your account does not currently have an active Scale subscription.” Jiminny-side outage — “Error:Jiminny is temporarily unavailable (status 503). This is not a data or permissions issue — please retry in a few minutes.” No data found - “Error:No calls found matching your criteria. Try adjusting your filters — for example, widening the date range, removing the account filter, or checking the rep name is spelled correctly in Jiminny.” Allow customers to securely control who and what data is accessible externally HIGH Ensure MCP only exposes data user has access to - based on team visibility settings. This means that if a user is not allow to access calls/deals in Jiminny UI then they shouldn’t be able to access those through the MCP as well. Private meetings shouldn’t be exposed via MCP HIGH When a meetings is set to Private then the information about it shouldn’t be exposed through the MCP. Ensure Jiminny data can be combined with other sources (e.g. CRM, docs) in AI workflows HIGH Ensure data is structured to be easily combined with: CRM (accounts, deals) external docs Use consistent identifiers: account IDs deal IDs MCP is available only for Scale tier and above HIGH Customers who are on Capture tier should be able to access any of their data through MCP. This should also cover the scenario when a customer has been on Scale but then downgrades to Capture - their MCP access should stop working. Provide visibility into how external AI tools access Jiminny data HIGH Audit logs: what data was accessed by which external system when identity - who made the request specific queries/filters used failed access attempts (especially cross-visibility-boundary attempts) Admins should be able to access the logs from the org settings.We can start with a csv export before building a specific page for it. example from Atlassian - Provide customers with example prompts to get started quickly HIGH MCP prompts are explicitly defined as prompt templates that clients can discover and call with arguments. See examples in table below. Expose Jiminny as a Connector in Claude medium Competitors like Fathom are listed as Connectors in Claude. This will make it easier for customers to find us and to connect Jiminny Provide customers with example workflows to get started quickly medium A workflow is usually multiple steps, maybe multiple tools, still focused on one outcome. See examples in table below. Allow customers to use predefined Jiminny skills for common workflows medium Anthropic describes Skills as folders that include instructions, scripts, and resources that Claude can load when relevant, and as a way to teach Claude repeatable workflows, preferences, and domain expertise once instead of re-explaining them every time. Skills - a reusable package of behavior that can include prompts, instructions, resources, and sometimes scripts/tools for a broader job. Claude skills - https://resources.anthropic.com/hubfs/The-Complete-Guide-to-Building-Skill-for-Claude.pdf?hsLang=en&utm_source=chatgpt.com See examples in table below. Jiminny UI widget for OpenAI medium The reason to have this is to make certain Jiminny use cases much easier than pure chat. Instead of ChatGPT only replying with text like “Here are the last 5 ACME calls,” it could also show a visual Jiminny card or mini-app inside the chat. That widget could list calls, show a deal summary, let the user filter by rep/date/account, open a transcript section, or save a snippet—while the conversation continues in normal chat alongside it. For Jiminny, the best widget use cases are the ones where users need to browse or compare rather than ask one-off questions. A strong example is deal review: the user asks ChatGPT, “What is the status of the ACME deal?” ChatGPT calls your Jiminny MCP tools, and the widget shows a compact deal view with recent calls, risks, next steps, stakeholders, and links to transcripts/snippets. The chat can still summarize the answer in words, but the widget gives a clearer, scannable interface. Another good Jiminny widget use case is call search and exploration. A text answer can say “I found 12 calls mentioning pricing objections,” but a widget could show a sortable list with date, rep, account, score, and objection count, then let the user click into one call to see the exact excerpt or jump to a transcript section. Allow customers to run long-running analyses asynchronously and retrieve progress/results low Some requests/questions require analysis of Hugh volumes of data. For those, it may be better to: start the job let it run in the background return a status like “in progress” let the client come back for the result later For example - User asks in Claude: “Analyse all calls from this quarter and tell me the top 5 objections by segment.” That might require: searching lots of calls pulling many summaries/transcripts aggregating results Instead of making Claude wait 45+ seconds, Jiminny could: create an analysis job return: job_id = 123, status = running We need this in order to support: large-scale analysis multi-call aggregation across lots of data playlist generation across many calls heavy recap/report generation Creating a snippet through the MCP low Create a shareable snippet from a call recording by specifying a time range. Useful for highlighting key moments — objection handling, pricing discussions, competitive mentions — and sharing them with your team. example request: { \"tool\": \"create_snippet\", \"arguments\": { \"call_id\": \"call_123\", \"start_time\": \"00:18:24\", \"end_time\": \"00:19:10\", \"title\": \"Pricing objection\" } } example response: { \"snippet_id\": \"snip_987\", \"title\": \"Pricing objection\", \"share_url\": \"https://app.jiminny.com/snippets/snip_987\" } Ability to add recordings or snippets to a playlist low Allow customers to create libraries of calls automatically. They can use those for onboarding or other purposes Allow AI tools to read reusable Jiminny resources low fathom Resources are useful for data that should be read consistently rather than recomputed every time. In Jiminny terms, that could be: current deal snapshot account summary weekly rep recap approved talk tracks / objection handling guidance curated playlists or snippet libraries This is useful because an AI can consume these directly as context, instead of repeatedly stitching together many tool calls. Ability to write coaching notes in Jiminny through MCP low What we want to do for prompts/worflows and skills Capability Type User value / job to be done Example Jiminny use case Inputs Steps performed Output Draft follow-up email Prompt Help reps quickly create tailored follow-ups after calls Use the latest customer call to draft an email with recap and next steps Call ID optional tone optional recipient type Retrieve call summary and action items from Jiminny. Pull key points, commitments, and next steps. Apply the chosen tone and structure. Draft the email in a consistent format. Customer-ready follow-up email draft Summarise call Prompt Help users quickly extract the most important points from a conversation Generate a concise summary of one call for internal or external use Call ID optional summary style optional audience Retrieve transcript, metadata, and structured insights. Identify key topics, decisions, risks, and next steps. Format output for the chosen audience. Short or structured call summary with actions and risks Generate deal recap Prompt Help reps and managers get a fast overview of a deal Summarise the current state of a deal based on recent calls and linked CRM context Deal ID or account name optional date range Retrieve calls and meetings linked to the deal. Pull deal metadata and CRM-linked context. Identify recent changes, blockers, risks, and next steps. Summarise into a concise recap. Deal recap with status, blockers, risks, and recommended next steps Prepare weekly recap Prompt Help managers or reps review what changed over a time period Weekly recap of calls, themes, and actions for one rep, team, or account Rep ID team ID or account ID time period Retrieve relevant calls and summaries for the selected time period. Aggregate themes, action items, and changes. Highlight notable risks, opportunities, and follow-ups. Weekly recap with top themes, risks, opportunities, and actions Prepare deal review Workflow Help reps and managers review deal status using multiple sources of context Review a deal before pipeline review or forecast meeting Deal ID optional date range Retrieve all recent calls, emails, and meetings tied to the deal. Pull structured call summaries, score, action items, and key points. Pull linked CRM context such as stage, contacts, and account details. Aggregate open risks, unresolved objections, stakeholder gaps, and next steps. Format into a review-ready structure. Deal review document with current status, risks, stakeholders, blockers, and next steps Weekly team recap Workflow Help managers monitor activity and risk across a group of reps or accounts End-of-week team summary for sales leadership Team ID date range Retrieve calls and structured insights across the team. Group by rep, account, or deal. Identify recurring themes, major risks, strong calls, and missed follow-ups. Highlight calls or deals that need attention. Team-level recap with patterns, key risks, notable wins, and action areas Objection analysis across calls Workflow Help teams identify patterns across multiple conversations Analyse pricing or competitor objections across recent calls Account ID deal ID rep ID keyword/topic date range Search calls matching the topic or keyword. Retrieve summaries, transcripts, and snippets where relevant. Identify recurring objections and how they were handled. Assess whether objections were resolved or remain open. Summarise patterns and examples. Objection analysis with themes, frequency, examples, and suggested follow-up actions Build onboarding playlist Workflow Help enablement teams curate useful learning content faster Build a playlist of strong discovery, demo, or pricing calls for new hires Topic call type rep/team filter optional time period Search for calls matching the selected criteria. Rank or filter calls based on score, topics, or key moments. Identify useful snippets or full recordings. Add selected calls/snippets into a playlist structure. Generate short descriptions for each item. Curated onboarding playlist with selected calls/snippets and descriptions Deal Inspection Skill Skill Give users a consistent, opinionated way to assess a deal Claude reviews a deal using a repeatable Jiminny methodology Deal ID or account name optional review scope Determine whether the request is suitable for a deal inspection. Retrieve relevant calls, summaries, CRM context, stakeholders, and risks. Apply a standard Jiminny review framework to assess deal health. Look for missing next steps, unresolved objections, stakeholder gaps, and warning signs. Present findings in a consistent structure with recommended actions. Structured deal inspection with health assessment, red flags, and recommendations Manager Coaching Skill Skill Help managers review calls consistently and identify coaching moments Analyse a rep’s call and surface strengths, gaps, and examples for coaching Call ID optional rep ID optional coaching focus Retrieve transcript, score, summary, and key moments from the call. Evaluate the conversation against a coaching framework. Identify what went well and where the rep could improve. Suggest moments to clip as snippets. Recommend coaching actions or playlist additions. Coaching review with strengths, gaps, snippet suggestions, and recommended coaching actions CSM / QBR Prep Skill Skill Help CS or AM teams prepare structured customer reviews from conversations Generate an account review or QBR-style summary from recent customer interactions Account ID, optional time period Retrieve all recent calls, emails, and account-linked context. Aggregate themes, requests, blockers, sentiment shifts, and opportunities. Apply a repeatable account review structure. Summarise outcomes, open issues, and suggested next steps. Structured QBR/account review summary with themes, risks, opportunities, and actions Snippet Builder Skill Skill Help users consistently capture and label useful moments from calls Identify useful moments in a call and convert them into reusable snippets Call ID, optional focus area such as pricing, objection, competitor, discovery Retrieve transcript, recording timeline, and call insights. Detect moments matching the requested focus area. Propose snippet start/end times and titles. Tag snippets by type or theme. Optionally save them or add them to a playlist. One or more proposed or saved snippets with title, timing, and tags 💡 Technical details Auth model needs specifying. Are API keys scoped per user, per team, or per Jiminny instance? If a key is generated by an admin, does it inherit their visibility level, or provide org-wide? Are permissions evaluated at query time or frozen at key creation? Needs to be query-time, otherwise permission changes won't propagate. Key lifecycle management is missing. No mention of rotation, expiry, or revocation. A departed employee's active key is a data leak. Need: revocation, optional expiry, alerts on stale keys, and consider whether keys should be tied to service accounts rather than personal users. Rate limiting should be HIGH. A compromised key or misconfigured automation could bulk-export an entire customer's call history. Need per-key rate limits and anomaly detection on unusual access patterns. Open Questions Track unresolved issues or decisions that need to be made. Update as answers become available. Question Answer Date Answered Competitor research Competitor MCP Availability Core Capabilities Advanced Capabilities Positioning Key Strength Key Weakness Gong ✅ Mature MCP List/search calls Get transcripts get Call metadata Deal intelligence Scorecards, analytics CRM context Enterprise data layer Deep data + ecosystem integrations Limited opinionated AI workflows Avoma ✅ Mature MCP list_meetings get_meeting get_transcript key topics Deal fields/Deal level analysis Coaching/Scoring CRM context pushing insights into Notion / Confluence AI-ready meeting intelligence Strongest “outputs” layer Mostly pull-based interactions Fathom ✅ MCP list/search meetings get transcript get summary/action items Team/org context Webhooks (event-based triggers) get_weekly_recap aggregated action items across meetings creating webhooks directly from the MCP server Lightweight meeting data access Includes summaries + actions Limited analytics depth Grain ✅ Basic MCP get meetings download transcripts Notes Deals Scorecards Data access utility Simple + accessible Low sophistication, sometimes browser-based Outreach ⚠️ MCP (workflow-focused) Search sequences Emails Meetings (Kaia) account / prospect / opportunity lookups Workflow automation Multi-system orchestration Revenue workflow engine End-to-end GTM workflows Less depth in conversation data Attention ⚠️ Emerging MCP Meeting data Transcripts CRM-linked context AI insights Sales assistant workflows create snippets AI sales assistant + CRM Strong CRM linkage Less focus on external knowledge layer Planhat - Related content Ask Jiminny Anything on Call level Galya Dimitrova Hubspot app Galya Dimitrova Product Vision & Strategy Galya Dimitrova Automated CRM Filling Simona Georgieva (Deactivated) Competitive analysis Galya Dimitrova AI agent ideas Steliyan Georgiev Comments James Graham 9 Apr A few areas around Security & Compliance that need more depth before this moves beyond draft: Auth model needs specifying. Are API keys scoped per user, per team, or per Jiminny instance? If a key is generated by an admin, does it inherit their visibility level, or provide org-wide? Are permissions evaluated at query time or frozen at key creation? Needs to be query-time, otherwise permission changes won't propagate. Team visibility enforcement should be its own HIGH requirement. The current note under access control (\"ensure MCP only exposes data user has access to\") is doing too much work as a single line. Every MCP tool response (especially search_calls and deal-level aggregations) must be filtered through the same visibility engine as the UI. Semantic search is the riskiest here; it could surface results across team boundaries if not properly scoped. No data minimisation or scoping controls. We're exposing transcripts, CRM fields, contact details with job titles, deal context - significant PII and commercial data leaving the platform. Can customers configure which data types are exposed? Can transcripts be PII-stripped before they leave Jiminny? Given we position GDPR consent as a differentiator, we should be thinking about this. GDPR downstream processing is unaddressed. Piping transcripts to OpenAI/Gemini introduces new data processors. Customers need to acknowledge responsibility for downstream processing during setup. We should also consider whether call participants' recording consent covers onward sharing to third-party AI - it almost certainly doesn't by default. This is one for me to pick up. Key lifecycle management is missing. No mention of rotation, expiry, or revocation. A departed employee's active key is a data leak. Need: revocation, optional expiry, alerts on stale keys, and consider whether keys should be tied to service accounts rather than personal users. Rate limiting should be HIGH. A compromised key or misconfigured automation could bulk-export an entire customer's call history. Need per-key rate limits and anomaly detection on unusual access patterns. Audit logs should go deeper. Current spec (what data, which system, when) is a start. Add: identity behind the key, specific queries/filters used, and failed access attempts (especially cross-visibility-boundary attempts). Enterprise compliance teams will expect this. Downgrade handling. Doc says Scale tier and above, but doesn't say what happens on downgrade. Keys should auto-deactivate. Happy to help draft a dedicated Security & Compliance section if useful. Galya Dimitrova 15 Apr Thanks for the input @James Graham . I made the product related changes in the table and for the rest I left them as a note in the Technical section for the team to look at when they start looking at this. I wonder about your points related to GDPR. Currently multiple customers are using the Customer API/zapier to feed this data to AI and BI tools. They are also manually exporting transcripts and other information from the platform and feeding it to AI tools. 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This means that if a user is not allow to access calls/deals in Jiminny UI then they shouldn’t be able to access those through the MCP as well.","depth":23,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"Private meetings shouldn’t be exposed via MCP","depth":23,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"HIGH","depth":23,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"When a meetings is set to Private then the information about it shouldn’t be exposed through the MCP.","depth":23,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"Ensure Jiminny data can be combined with other sources (e.g. CRM, docs) in AI workflows","depth":23,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"HIGH","depth":23,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"Ensure data is structured to be easily combined with:","depth":23,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"CRM (accounts, deals)","depth":23,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"external docs","depth":23,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"Use consistent identifiers:","depth":23,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"account IDs","depth":23,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"deal IDs","depth":23,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"MCP is available only for Scale tier and above","depth":23,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"HIGH","depth":23,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"Customers who are on Capture tier should be able to access any of their data through MCP.","depth":23,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"This should also cover the scenario when a customer has been on Scale but then downgrades to Capture - their MCP access should stop working.","depth":23,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"Provide visibility into how external AI tools access Jiminny data","depth":23,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"HIGH","depth":23,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"Audit logs:","depth":23,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"what data was accessed by which external system when","depth":23,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"identity - who made the request","depth":23,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"specific queries/filters used","depth":23,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"failed access attempts (especially cross-visibility-boundary attempts)","depth":23,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"Admins should be able to access the logs from the org settings.We can start with a csv export before building a specific page for it.","depth":23,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"example from Atlassian -","depth":23,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"Provide customers with example prompts to get started quickly","depth":23,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"HIGH","depth":23,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"MCP prompts are explicitly defined as prompt templates that clients can discover and call with arguments.","depth":23,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"See examples in table below.","depth":23,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"Expose Jiminny as a Connector in Claude","depth":23,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"medium","depth":23,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"Competitors like Fathom are listed as Connectors in Claude. This will make it easier for customers to find us and to connect Jiminny","depth":23,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"Provide customers with example workflows to get started quickly","depth":23,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"medium","depth":23,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"A workflow is usually multiple steps, maybe multiple tools, still focused on one outcome.","depth":23,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"See examples in table below.","depth":23,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"Allow customers to use predefined Jiminny skills for common workflows","depth":23,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"medium","depth":23,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"Anthropic describes Skills as folders that include instructions, scripts, and resources that Claude can load when relevant, and as a way to teach Claude repeatable workflows, preferences, and domain expertise once instead of re-explaining them every time. Skills - a reusable package of behavior that can include prompts, instructions, resources, and sometimes scripts/tools for a broader job.","depth":23,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"Claude skills - https://resources.anthropic.com/hubfs/The-Complete-Guide-to-Building-Skill-for-Claude.pdf?hsLang=en&utm_source=chatgpt.com","depth":23,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"See examples in table below.","depth":23,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"Jiminny UI widget for OpenAI","depth":23,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"medium","depth":23,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"The reason to have this is to make certain Jiminny use cases much easier than pure chat.","depth":23,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"Instead of ChatGPT only replying with text like “Here are the last 5 ACME calls,” it could also show a visual Jiminny card or mini-app inside the chat. That widget could list calls, show a deal summary, let the user filter by rep/date/account, open a transcript section, or save a snippet—while the conversation continues in normal chat alongside it.","depth":23,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"For Jiminny, the best widget use cases are the ones where users need to browse or compare rather than ask one-off questions. A strong example is deal review: the user asks ChatGPT, “What is the status of the ACME deal?” ChatGPT calls your Jiminny MCP tools, and the widget shows a compact deal view with recent calls, risks, next steps, stakeholders, and links to transcripts/snippets. The chat can still summarize the answer in words, but the widget gives a clearer, scannable interface.","depth":23,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"Another good Jiminny widget use case is call search and exploration. A text answer can say “I found 12 calls mentioning pricing objections,” but a widget could show a sortable list with date, rep, account, score, and objection count, then let the user click into one call to see the exact excerpt or jump to a transcript section.","depth":23,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"Allow customers to run long-running analyses asynchronously and retrieve progress/results","depth":23,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"low","depth":23,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"Some requests/questions require analysis of Hugh volumes of data. For those, it may be better to:","depth":23,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"start the job","depth":23,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"let it run in the background","depth":23,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"return a status like “in progress”","depth":23,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"let the client come back for the result later","depth":23,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"For example - User asks in Claude:","depth":23,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"“Analyse all calls from this quarter and tell me the top 5 objections by segment.”","depth":23,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"That might require:","depth":23,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"searching lots of calls","depth":23,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"pulling many summaries/transcripts","depth":23,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"aggregating results","depth":23,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"Instead of making Claude wait 45+ seconds, Jiminny could:","depth":23,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"create an analysis job","depth":23,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"return: job_id = 123, status = running","depth":23,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"We need this in order to support:","depth":23,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"large-scale analysis","depth":23,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"multi-call aggregation across lots of data","depth":23,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"playlist generation across many calls","depth":23,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"heavy recap/report generation","depth":23,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"Creating a snippet through the MCP","depth":23,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"low","depth":23,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"Create a shareable snippet from a call recording by specifying a time range. Useful for highlighting key moments — objection handling, pricing discussions, competitive mentions — and sharing them with your team.","depth":23,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"example request:","depth":23,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"{","depth":23,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"\"tool\": \"create_snippet\",","depth":23,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"\"arguments\": {","depth":23,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"\"call_id\": \"call_123\",","depth":23,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"\"start_time\": \"00:18:24\",","depth":23,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"\"end_time\": \"00:19:10\",","depth":23,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"\"title\": \"Pricing objection\"","depth":23,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"}","depth":23,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"}","depth":23,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"example response:","depth":23,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"{","depth":23,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"\"snippet_id\": \"snip_987\",","depth":23,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"\"title\": \"Pricing objection\",","depth":23,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"\"share_url\": \"https://app.jiminny.com/snippets/snip_987\"","depth":23,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"}","depth":23,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"Ability to add recordings or snippets to a playlist","depth":23,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"low","depth":23,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"Allow customers to create libraries of calls automatically. They can use those for onboarding or other purposes","depth":23,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"Allow AI tools to read reusable Jiminny resources","depth":23,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"low","depth":23,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"fathom","depth":23,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"Resources are useful for data that should be read consistently rather than recomputed every time. In Jiminny terms, that could be:","depth":23,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"current deal snapshot","depth":23,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"account summary","depth":23,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"weekly rep recap","depth":23,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"approved talk tracks / objection handling guidance","depth":23,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"curated playlists or snippet libraries","depth":23,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"This is useful because an AI can consume these directly as context, instead of repeatedly stitching together many tool calls.","depth":23,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"Ability to write coaching notes in Jiminny through MCP","depth":23,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"low","depth":23,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"What we want to do for prompts/worflows and skills","depth":23,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"Capability","depth":23,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"Type","depth":23,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"User value / job to be done","depth":23,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"Example Jiminny use 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Are API keys scoped per user, per team, or per Jiminny instance? If a key is generated by an admin, does it inherit their visibility level, or provide org-wide? Are permissions evaluated at query time or frozen at key creation? Needs to be query-time, otherwise permission changes won't propagate.","depth":23,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"Team visibility enforcement should be its own HIGH requirement. The current note under access control (\"ensure MCP only exposes data user has access to\") is doing too much work as a single line. Every MCP tool response (especially search_calls and deal-level aggregations) must be filtered through the same visibility engine as the UI. Semantic search is the riskiest here; it could surface results across team boundaries if not properly scoped.","depth":23,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"No data minimisation or scoping controls. We're exposing transcripts, CRM fields, contact details with job titles, deal context - significant PII and commercial data leaving the platform. Can customers configure which data types are exposed? Can transcripts be PII-stripped before they leave Jiminny? Given we position GDPR consent as a differentiator, we should be thinking about this.","depth":23,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"GDPR downstream processing is unaddressed. Piping transcripts to OpenAI/Gemini introduces new data processors. Customers need to acknowledge responsibility for downstream processing during setup. We should also consider whether call participants' recording consent covers onward sharing to third-party AI - it almost certainly doesn't by default. This is one for me to pick up.","depth":23,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"Key lifecycle management is missing. No mention of rotation, expiry, or revocation. A departed employee's active key is a data leak. Need: revocation, optional expiry, alerts on stale keys, and consider whether keys should be tied to service accounts rather than personal users.","depth":23,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"Rate limiting should be HIGH. A compromised key or misconfigured automation could bulk-export an entire customer's call history. Need per-key rate limits and anomaly detection on unusual access patterns.","depth":23,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"Audit logs should go deeper. Current spec (what data, which system, when) is a start. Add: identity behind the key, specific queries/filters used, and failed access attempts (especially cross-visibility-boundary attempts). Enterprise compliance teams will expect this.","depth":23,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"Downgrade handling. Doc says Scale tier and above, but doesn't say what happens on downgrade. Keys should auto-deactivate.","depth":23,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"Happy to help draft a dedicated Security & Compliance section if useful.","depth":23,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"Galya Dimitrova","depth":23,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"15 Apr","depth":23,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"Thanks for the input @James Graham . I made the product related changes in the table and for the rest I left them as a note in the Technical section for the team to look at when they start looking at this.","depth":23,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"I wonder about your points related to GDPR. Currently multiple customers are using the Customer API/zapier to feed this data to AI and BI tools. They are also manually exporting transcripts and other information from the platform and feeding it to AI tools. I don’t get how MCP is so much different that all of these and why it will introduce new data processors (which are already being utilised) and would require any changes to the consent provided by participants.","depth":23,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXButton","text":"Expand","depth":21,"role_description":"button","subrole":"AXUnknown","is_enabled":true,"is_focused":false,"is_selected":false}]...
|
4479374102923647883
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-2099241112984464807
|
idle
|
accessibility
|
NULL
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Platform Sprint 2 Q2 - Platform Team - Scrum Board Platform Sprint 2 Q2 - Platform Team - Scrum Board - Jira
SevenShores\Hubspot\Exceptions\BadRequest: Client error: `POST [URL_WITH_CREDENTIALS] Graham . I made the product related changes in the table and for the rest I left them as a note in the Technical section for the team to look at when they start looking at this. I wonder about your points related to GDPR. Currently multiple customers are using the Customer API/zapier to feed this data to AI and BI tools. They are also manually exporting transcripts and other information from the platform and feeding it to AI tools. I don’t get how MCP is so much different that all of these and why it will introduce new data processors (which are already being utilised) and would require any changes to the consent provided by participants.
You said
Jiminny MCP Connector
Epic
Link to Epik in Jira
Document status
DRAFT
Objective
Enable customers to connect Jiminny data to external AI tools (Claude, OpenAI, Gemini) so it can be used as part of their broader knowledge base and workflows.
Position Jiminny as a data layer for AI-driven revenue workflows, not just a standalone product.
👤 Target user
Revenue teams using AI tools (Sales, CS, RevOps)
Companies already experimenting with Claude / OpenAI
Mid-market & Enterprise customers with multiple data sources (CRM, docs, CI tools, Support tools etc)
🤕 Pain point or problem
Jiminny data is locked in the platform
AI tools lack access to high-value conversation context
Customers must manually export/copy transcripts
No easy way to combine calls with CRM + docs + other info - using the Jiminny API is not suitable for non technical sales people
Peer pressure as almost all competitors have this
💥 Impact and benefits
For customers
Better AI outputs using real customer conversations
Ability to build automated workflows across tools
For Jiminny
Increased product stickiness (embedded in workflows)
Competitive parity with Gong / Avoma etc.
💡 Solution ideas
Build an AI Knowledge Connector (MCP-based) that:
Exposes Jiminny data (calls, transcripts, metadata) to AI tools
Provides structured insights (summaries, action items, scoring etc.)
Supports deal-level context
Allows integration into customer-owned AI stacks (Claude + Zapier, etc.)
Success metrics
List the key goals and how you will measure success. Include both qualitative and quantitative metrics (e.g., user adoption, retention rate, revenue targets).
Goal
Metric
Increase stickiness by ensuring Jiminny is embedded in the customer’s workflows
% of customers connecting external AI tools
Number of MCP/API calls per customer - and which ones are being used the most
Decrease the manual copying of transcripts
decrease by X %
User interaction and design
Simple setup flow:
Generate API key / connect MCP
Clear instructions for Claude / Zapier setup
Provide:
Example prompts for Claude
Pre-built workflow templates for Zapier
Clear documentation - with use cases
👉 Focus: usable by non-technical users
Detailed Requirements
List the functional and non-functional requirements. Prioritize them (e.g., High, Medium, Low) and add notes for clarification.
Requirement
Importance
Notes
Allow customers to connect Jiminny to their AI tools (e.g. Claude, OpenAI)
HIGH
Provide MCP endpoint so customers can easily integrate Jiminny into their AI stack
Allow customers to access call data through AI tools
HIGH
Expose Jiminny data:
list calls (filter by date, user, account, deal)
get call
get transcript (speaker-separated)
get call metadata
search calls (keyword + semantic)
Support filtering by:
account / contact/ lead / deal
jiminny user
date range
Allow customers to search and query calls using AI tools
HIGH
Support keyword and semantic search across conversations
Provide structured insights so customers can generate better outputs
HIGH
For each call, expose:
Summary
Action items
Key points
Activity type
Notes
Call Score
CRM information
Allow customers to understand deal status across multiple calls/emails
HIGH
For each deal expose:
calls/meetings/emails
Identified risks
contacts related to the deal with their job title
linked account details
all CRM field information that we have in DI + fields used for CRM filling
example - get_deal_summary
request -
{
"tool": "get_deal_summary",
"arguments": {
"deal_name": "ACME"
}
}
responce:
{
"deal_name": "ACME",
"stage": "Negotiation",
"recent_activity": [
"Demo call on 2026-04-01",
"Pricing discussion on 2026-04-03"
],
"risks": [
"Pricing concerns",
"Security review pending"
], "next_steps": [
"Send follow-up to VP Sales",
"Share security documentation"
]
}
Ensure the AI can easily understand the schema of the data coming from Jiminny
HIGH
Models perform much better when tools have:
clear names
rich descriptions
predictable schemas
Provide clear, actionable error states for customers when MCP connections fail
HIGH
Error messages should guide agents toward solutions with specific suggestions and next steps.
Expired or revoked key — “Error: Authentication failed. The API key used to access Jiminny has been revoked or has expired. Please ask your Jiminny admin to generate a new API key in Settings > Organization > General and reconnect the MCP server.”
Rate limit hit — “Error: Rate limit exceeded. Too many requests have been made to the Jiminny MCP server in a short period. Please wait 60 seconds before retrying.”
Permissions mismatch — if a user tries to access data outside their team visibility settings - “Error: Access denied. The requested call (call_id: [X]) is outside your team's visibility settings in Jiminny. Only calls within your permitted scope are accessible.”
Trying to access private meeting - “Error: Access denied. This meeting has been marked as private by the host and cannot be accessed through the MCP connector. Try requesting a different call or ask the meeting host to change the visibility settings in Jiminny.”
Downgraded/Capture account — if a customer's plan drops below Scale tier or the Customer is on Capture in the first place - “Error: MCP access unavailable. The Jiminny MCP connector is available on the Scale plan and above. Your account does not currently have an active Scale subscription.”
Jiminny-side outage — “Error:Jiminny is temporarily unavailable (status 503). This is not a data or permissions issue — please retry in a few minutes.”
No data found - “Error:No calls found matching your criteria. Try adjusting your filters — for example, widening the date range, removing the account filter, or checking the rep name is spelled correctly in Jiminny.”
Allow customers to securely control who and what data is accessible externally
HIGH
Ensure MCP only exposes data user has access to - based on team visibility settings. This means that if a user is not allow to access calls/deals in Jiminny UI then they shouldn’t be able to access those through the MCP as well.
Private meetings shouldn’t be exposed via MCP
HIGH
When a meetings is set to Private then the information about it shouldn’t be exposed through the MCP.
Ensure Jiminny data can be combined with other sources (e.g. CRM, docs) in AI workflows
HIGH
Ensure data is structured to be easily combined with:
CRM (accounts, deals)
external docs
Use consistent identifiers:
account IDs
deal IDs
MCP is available only for Scale tier and above
HIGH
Customers who are on Capture tier should be able to access any of their data through MCP.
This should also cover the scenario when a customer has been on Scale but then downgrades to Capture - their MCP access should stop working.
Provide visibility into how external AI tools access Jiminny data
HIGH
Audit logs:
what data was accessed by which external system when
identity - who made the request
specific queries/filters used
failed access attempts (especially cross-visibility-boundary attempts)
Admins should be able to access the logs from the org settings.We can start with a csv export before building a specific page for it.
example from Atlassian -
Provide customers with example prompts to get started quickly
HIGH
MCP prompts are explicitly defined as prompt templates that clients can discover and call with arguments.
See examples in table below.
Expose Jiminny as a Connector in Claude
medium
Competitors like Fathom are listed as Connectors in Claude. This will make it easier for customers to find us and to connect Jiminny
Provide customers with example workflows to get started quickly
medium
A workflow is usually multiple steps, maybe multiple tools, still focused on one outcome.
See examples in table below.
Allow customers to use predefined Jiminny skills for common workflows
medium
Anthropic describes Skills as folders that include instructions, scripts, and resources that Claude can load when relevant, and as a way to teach Claude repeatable workflows, preferences, and domain expertise once instead of re-explaining them every time. Skills - a reusable package of behavior that can include prompts, instructions, resources, and sometimes scripts/tools for a broader job.
Claude skills - https://resources.anthropic.com/hubfs/The-Complete-Guide-to-Building-Skill-for-Claude.pdf?hsLang=en&utm_source=chatgpt.com
See examples in table below.
Jiminny UI widget for OpenAI
medium
The reason to have this is to make certain Jiminny use cases much easier than pure chat.
Instead of ChatGPT only replying with text like “Here are the last 5 ACME calls,” it could also show a visual Jiminny card or mini-app inside the chat. That widget could list calls, show a deal summary, let the user filter by rep/date/account, open a transcript section, or save a snippet—while the conversation continues in normal chat alongside it.
For Jiminny, the best widget use cases are the ones where users need to browse or compare rather than ask one-off questions. A strong example is deal review: the user asks ChatGPT, “What is the status of the ACME deal?” ChatGPT calls your Jiminny MCP tools, and the widget shows a compact deal view with recent calls, risks, next steps, stakeholders, and links to transcripts/snippets. The chat can still summarize the answer in words, but the widget gives a clearer, scannable interface.
Another good Jiminny widget use case is call search and exploration. A text answer can say “I found 12 calls mentioning pricing objections,” but a widget could show a sortable list with date, rep, account, score, and objection count, then let the user click into one call to see the exact excerpt or jump to a transcript section.
Allow customers to run long-running analyses asynchronously and retrieve progress/results
low
Some requests/questions require analysis of Hugh volumes of data. For those, it may be better to:
start the job
let it run in the background
return a status like “in progress”
let the client come back for the result later
For example - User asks in Claude:
“Analyse all calls from this quarter and tell me the top 5 objections by segment.”
That might require:
searching lots of calls
pulling many summaries/transcripts
aggregating results
Instead of making Claude wait 45+ seconds, Jiminny could:
create an analysis job
return: job_id = 123, status = running
We need this in order to support:
large-scale analysis
multi-call aggregation across lots of data
playlist generation across many calls
heavy recap/report generation
Creating a snippet through the MCP
low
Create a shareable snippet from a call recording by specifying a time range. Useful for highlighting key moments — objection handling, pricing discussions, competitive mentions — and sharing them with your team.
example request:
{
"tool": "create_snippet",
"arguments": {
"call_id": "call_123",
"start_time": "00:18:24",
"end_time": "00:19:10",
"title": "Pricing objection"
}
}
example response:
{
"snippet_id": "snip_987",
"title": "Pricing objection",
"share_url": "https://app.jiminny.com/snippets/snip_987"
}
Ability to add recordings or snippets to a playlist
low
Allow customers to create libraries of calls automatically. They can use those for onboarding or other purposes
Allow AI tools to read reusable Jiminny resources
low
fathom
Resources are useful for data that should be read consistently rather than recomputed every time. In Jiminny terms, that could be:
current deal snapshot
account summary
weekly rep recap
approved talk tracks / objection handling guidance
curated playlists or snippet libraries
This is useful because an AI can consume these directly as context, instead of repeatedly stitching together many tool calls.
Ability to write coaching notes in Jiminny through MCP
low
What we want to do for prompts/worflows and skills
Capability
Type
User value / job to be done
Example Jiminny use case
Inputs
Steps performed
Output
Draft follow-up email
Prompt
Help reps quickly create tailored follow-ups after calls
Use the latest customer call to draft an email with recap and next steps
Call ID
optional tone
optional recipient type
Retrieve call summary and action items from Jiminny.
Pull key points, commitments, and next steps.
Apply the chosen tone and structure.
Draft the email in a consistent format.
Customer-ready follow-up email draft
Summarise call
Prompt
Help users quickly extract the most important points from a conversation
Generate a concise summary of one call for internal or external use
Call ID
optional summary style
optional audience
Retrieve transcript, metadata, and structured insights.
Identify key topics, decisions, risks, and next steps.
Format output for the chosen audience.
Short or structured call summary with actions and risks
Generate deal recap
Prompt
Help reps and managers get a fast overview of a deal
Summarise the current state of a deal based on recent calls and linked CRM context
Deal ID or account name
optional date range
Retrieve calls and meetings linked to the deal.
Pull deal metadata and CRM-linked context.
Identify recent changes, blockers, risks, and next steps.
Summarise into a concise recap.
Deal recap with status, blockers, risks, and recommended next steps
Prepare weekly recap
Prompt
Help managers or reps review what changed over a time period
Weekly recap of calls, themes, and actions for one rep, team, or account
Rep ID
team ID or account ID
time period
Retrieve relevant calls and summaries for the selected time period.
Aggregate themes, action items, and changes.
Highlight notable risks, opportunities, and follow-ups.
Weekly recap with top themes, risks, opportunities, and actions
Prepare deal review
Workflow
Help reps and managers review deal status using multiple sources of context
Review a deal before pipeline review or forecast meeting
Deal ID
optional date range
Retrieve all recent calls, emails, and meetings tied to the deal.
Pull structured call summaries, score, action items, and key points.
Pull linked CRM context such as stage, contacts, and account details.
Aggregate open risks, unresolved objections, stakeholder gaps, and next steps.
Format into a review-ready structure.
Deal review document with current status, risks, stakeholders, blockers, and next steps
Weekly team recap
Workflow
Help managers monitor activity and risk across a group of reps or accounts
End-of-week team summary for sales leadership
Team ID
date range
Retrieve calls and structured insights across the team.
Group by rep, account, or deal.
Identify recurring themes, major risks, strong calls, and missed follow-ups.
Highlight calls or deals that need attention.
Team-level recap with patterns, key risks, notable wins, and action areas
Objection analysis across calls
Workflow
Help teams identify patterns across multiple conversations
Analyse pricing or competitor objections across recent calls
Account ID
deal ID
rep ID
keyword/topic
date range
Search calls matching the topic or keyword.
Retrieve summaries, transcripts, and snippets where relevant.
Identify recurring objections and how they were handled.
Assess whether objections were resolved or remain open.
Summarise patterns and examples.
Objection analysis with themes, frequency, examples, and suggested follow-up actions
Build onboarding playlist
Workflow
Help enablement teams curate useful learning content faster
Build a playlist of strong discovery, demo, or pricing calls for new hires
Topic
call type
rep/team filter
optional time period
Search for calls matching the selected criteria.
Rank or filter calls based on score, topics, or key moments.
Identify useful snippets or full recordings.
Add selected calls/snippets into a playlist structure.
Generate short descriptions for each item.
Curated onboarding playlist with selected calls/snippets and descriptions
Deal Inspection Skill
Skill
Give users a consistent, opinionated way to assess a deal
Claude reviews a deal using a repeatable Jiminny methodology
Deal ID or account name
optional review scope
Determine whether the request is suitable for a deal inspection.
Retrieve relevant calls, summaries, CRM context, stakeholders, and risks.
Apply a standard Jiminny review framework to assess deal health.
Look for missing next steps, unresolved objections, stakeholder gaps, and warning signs.
Present findings in a consistent structure with recommended actions.
Structured deal inspection with health assessment, red flags, and recommendations
Manager Coaching Skill
Skill
Help managers review calls consistently and identify coaching moments
Analyse a rep’s call and surface strengths, gaps, and examples for coaching
Call ID
optional rep ID
optional coaching focus
Retrieve transcript, score, summary, and key moments from the call.
Evaluate the conversation against a coaching framework.
Identify what went well and where the rep could improve.
Suggest moments to clip as snippets.
Recommend coaching actions or playlist additions.
Coaching review with strengths, gaps, snippet suggestions, and recommended coaching actions
CSM / QBR Prep Skill
Skill
Help CS or AM teams prepare structured customer reviews from conversations
Generate an account review or QBR-style summary from recent customer interactions
Account ID, optional time period
Retrieve all recent calls, emails, and account-linked context.
Aggregate themes, requests, blockers, sentiment shifts, and opportunities.
Apply a repeatable account review structure.
Summarise outcomes, open issues, and suggested next steps.
Structured QBR/account review summary with themes, risks, opportunities, and actions
Snippet Builder Skill
Skill
Help users consistently capture and label useful moments from calls
Identify useful moments in a call and convert them into reusable snippets
Call ID, optional focus area such as pricing, objection, competitor, discovery
Retrieve transcript, recording timeline, and call insights.
Detect moments matching the requested focus area.
Propose snippet start/end times and titles.
Tag snippets by type or theme.
Optionally save them or add them to a playlist.
One or more proposed or saved snippets with title, timing, and tags
💡 Technical details
Auth model needs specifying. Are API keys scoped per user, per team, or per Jiminny instance? If a key is generated by an admin, does it inherit their visibility level, or provide org-wide? Are permissions evaluated at query time or frozen at key creation? Needs to be query-time, otherwise permission changes won't propagate.
Key lifecycle management is missing. No mention of rotation, expiry, or revocation. A departed employee's active key is a data leak. Need: revocation, optional expiry, alerts on stale keys, and consider whether keys should be tied to service accounts rather than personal users.
Rate limiting should be HIGH. A compromised key or misconfigured automation could bulk-export an entire customer's call history. Need per-key rate limits and anomaly detection on unusual access patterns.
Open Questions
Track unresolved issues or decisions that need to be made. Update as answers become available.
Question
Answer
Date Answered
Competitor research
Competitor
MCP Availability
Core Capabilities
Advanced Capabilities
Positioning
Key Strength
Key Weakness
Gong
✅ Mature MCP
List/search calls
Get transcripts
get Call metadata
Deal intelligence
Scorecards, analytics
CRM context
Enterprise data layer
Deep data + ecosystem integrations
Limited opinionated AI workflows
Avoma
✅ Mature MCP
list_meetings
get_meeting
get_transcript
key topics
Deal fields/Deal level analysis
Coaching/Scoring
CRM context
pushing insights into Notion / Confluence
AI-ready meeting intelligence
Strongest “outputs” layer
Mostly pull-based interactions
Fathom
✅ MCP
list/search meetings
get transcript
get summary/action items
Team/org context
Webhooks (event-based triggers)
get_weekly_recap
aggregated action items across meetings
creating webhooks directly from the MCP server
Lightweight meeting data access
Includes summaries + actions
Limited analytics depth
Grain
✅ Basic MCP
get meetings
download transcripts
Notes
Deals
Scorecards
Data access utility
Simple + accessible
Low sophistication, sometimes browser-based
Outreach
⚠️ MCP (workflow-focused)
Search sequences
Emails
Meetings (Kaia)
account / prospect / opportunity lookups
Workflow automation
Multi-system orchestration
Revenue workflow engine
End-to-end GTM workflows
Less depth in conversation data
Attention
⚠️ Emerging MCP
Meeting data
Transcripts
CRM-linked context
AI insights
Sales assistant workflows
create snippets
AI sales assistant + CRM
Strong CRM linkage
Less focus on external knowledge layer
Planhat -
Related content
Ask Jiminny Anything on Call level
Galya Dimitrova
Hubspot app
Galya Dimitrova
Product Vision & Strategy
Galya Dimitrova
Automated CRM Filling
Simona Georgieva (Deactivated)
Competitive analysis
Galya Dimitrova
AI agent ideas
Steliyan Georgiev
Comments
James Graham
9 Apr
A few areas around Security & Compliance that need more depth before this moves beyond draft:
Auth model needs specifying. Are API keys scoped per user, per team, or per Jiminny instance? If a key is generated by an admin, does it inherit their visibility level, or provide org-wide? Are permissions evaluated at query time or frozen at key creation? Needs to be query-time, otherwise permission changes won't propagate.
Team visibility enforcement should be its own HIGH requirement. The current note under access control ("ensure MCP only exposes data user has access to") is doing too much work as a single line. Every MCP tool response (especially search_calls and deal-level aggregations) must be filtered through the same visibility engine as the UI. Semantic search is the riskiest here; it could surface results across team boundaries if not properly scoped.
No data minimisation or scoping controls. We're exposing transcripts, CRM fields, contact details with job titles, deal context - significant PII and commercial data leaving the platform. Can customers configure which data types are exposed? Can transcripts be PII-stripped before they leave Jiminny? Given we position GDPR consent as a differentiator, we should be thinking about this.
GDPR downstream processing is unaddressed. Piping transcripts to OpenAI/Gemini introduces new data processors. Customers need to acknowledge responsibility for downstream processing during setup. We should also consider whether call participants' recording consent covers onward sharing to third-party AI - it almost certainly doesn't by default. This is one for me to pick up.
Key lifecycle management is missing. No mention of rotation, expiry, or revocation. A departed employee's active key is a data leak. Need: revocation, optional expiry, alerts on stale keys, and consider whether keys should be tied to service accounts rather than personal users.
Rate limiting should be HIGH. A compromised key or misconfigured automation could bulk-export an entire customer's call history. Need per-key rate limits and anomaly detection on unusual ac...
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Architecture overview - Model Context Protocol — W Architecture overview - Model Context Protocol — Work...
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modelcontextprotocol.io/docs/learn/architecture
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Platform Sprint 2 Q2 - Platform Team - Scrum Board Platform Sprint 2 Q2 - Platform Team - Scrum Board - Jira
SevenShores\Hubspot\Exceptions\BadRequest: Client error: `POST [URL_WITH_CREDENTIALS] Graham . I made the product related changes in the table and for the rest I left them as a note in the Technical section for the team to look at when they start looking at this. I wonder about your points related to GDPR. Currently multiple customers are using the Customer API/zapier to feed this data to AI and BI tools. They are also manually exporting transcripts and other information from the platform and feeding it to AI tools. I don’t get how MCP is so much different that all of these and why it will introduce new data processors (which are already being utilised) and would require any changes to the consent provided by participants.
You said
Jiminny MCP Connector
Epic
Link to Epik in Jira
Document status
DRAFT
Objective
Enable customers to connect Jiminny data to external AI tools (Claude, OpenAI, Gemini) so it can be used as part of their broader knowledge base and workflows.
Position Jiminny as a data layer for AI-driven revenue workflows, not just a standalone product.
👤 Target user
Revenue teams using AI tools (Sales, CS, RevOps)
Companies already experimenting with Claude / OpenAI
Mid-market & Enterprise customers with multiple data sources (CRM, docs, CI tools, Support tools etc)
🤕 Pain point or problem
Jiminny data is locked in the platform
AI tools lack access to high-value conversation context
Customers must manually export/copy transcripts
No easy way to combine calls with CRM + docs + other info - using the Jiminny API is not suitable for non technical sales people
Peer pressure as almost all competitors have this
💥 Impact and benefits
For customers
Better AI outputs using real customer conversations
Ability to build automated workflows across tools
For Jiminny
Increased product stickiness (embedded in workflows)
Competitive parity with Gong / Avoma etc.
💡 Solution ideas
Build an AI Knowledge Connector (MCP-based) that:
Exposes Jiminny data (calls, transcripts, metadata) to AI tools
Provides structured insights (summaries, action items, scoring etc.)
Supports deal-level context
Allows integration into customer-owned AI stacks (Claude + Zapier, etc.)
Success metrics
List the key goals and how you will measure success. Include both qualitative and quantitative metrics (e.g., user adoption, retention rate, revenue targets).
Goal
Metric
Increase stickiness by ensuring Jiminny is embedded in the customer’s workflows
% of customers connecting external AI tools
Number of MCP/API calls per customer - and which ones are being used the most
Decrease the manual copying of transcripts
decrease by X %
User interaction and design
Simple setup flow:
Generate API key / connect MCP
Clear instructions for Claude / Zapier setup
Provide:
Example prompts for Claude
Pre-built workflow templates for Zapier
Clear documentation - with use cases
👉 Focus: usable by non-technical users
Detailed Requirements
List the functional and non-functional requirements. Prioritize them (e.g., High, Medium, Low) and add notes for clarification.
Requirement
Importance
Notes
Allow customers to connect Jiminny to their AI tools (e.g. Claude, OpenAI)
HIGH
Provide MCP endpoint so customers can easily integrate Jiminny into their AI stack
Allow customers to access call data through AI tools
HIGH
Expose Jiminny data:
list calls (filter by date, user, account, deal)
get call
get transcript (speaker-separated)
get call metadata
search calls (keyword + semantic)
Support filtering by:
account / contact/ lead / deal
jiminny user
date range
Allow customers to search and query calls using AI tools
HIGH
Support keyword and semantic search across conversations
Provide structured insights so customers can generate better outputs
HIGH
For each call, expose:
Summary
Action items
Key points
Activity type
Notes
Call Score
CRM information
Allow customers to understand deal status across multiple calls/emails
HIGH
For each deal expose:
calls/meetings/emails
Identified risks
contacts related to the deal with their job title
linked account details
all CRM field information that we have in DI + fields used for CRM filling
example - get_deal_summary
request -
{
"tool": "get_deal_summary",
"arguments": {
"deal_name": "ACME"
}
}
responce:
{
"deal_name": "ACME",
"stage": "Negotiation",
"recent_activity": [
"Demo call on 2026-04-01",
"Pricing discussion on 2026-04-03"
],
"risks": [
"Pricing concerns",
"Security review pending"
], "next_steps": [
"Send follow-up to VP Sales",
"Share security documentation"
]
}
Ensure the AI can easily understand the schema of the data coming from Jiminny
HIGH
Models perform much better when tools have:
clear names
rich descriptions
predictable schemas
Provide clear, actionable error states for customers when MCP connections fail
HIGH
Error messages should guide agents toward solutions with specific suggestions and next steps.
Expired or revoked key — “Error: Authentication failed. The API key used to access Jiminny has been revoked or has expired. Please ask your Jiminny admin to generate a new API key in Settings > Organization > General and reconnect the MCP server.”
Rate limit hit — “Error: Rate limit exceeded. Too many requests have been made to the Jiminny MCP server in a short period. Please wait 60 seconds before retrying.”
Permissions mismatch — if a user tries to access data outside their team visibility settings - “Error: Access denied. The requested call (call_id: [X]) is outside your team's visibility settings in Jiminny. Only calls within your permitted scope are accessible.”
Trying to access private meeting - “Error: Access denied. This meeting has been marked as private by the host and cannot be accessed through the MCP connector. Try requesting a different call or ask the meeting host to change the visibility settings in Jiminny.”
Downgraded/Capture account — if a customer's plan drops below Scale tier or the Customer is on Capture in the first place - “Error: MCP access unavailable. The Jiminny MCP connector is available on the Scale plan and above. Your account does not currently have an active Scale subscription.”
Jiminny-side outage — “Error:Jiminny is temporarily unavailable (status 503). This is not a data or permissions issue — please retry in a few minutes.”
No data found - “Error:No calls found matching your criteria. Try adjusting your filters — for example, widening the date range, removing the account filter, or checking the rep name is spelled correctly in Jiminny.”
Allow customers to securely control who and what data is accessible externally
HIGH
Ensure MCP only exposes data user has access to - based on team visibility settings. This means that if a user is not allow to access calls/deals in Jiminny UI then they shouldn’t be able to access those through the MCP as well.
Private meetings shouldn’t be exposed via MCP
HIGH
When a meetings is set to Private then the information about it shouldn’t be exposed through the MCP.
Ensure Jiminny data can be combined with other sources (e.g. CRM, docs) in AI workflows
HIGH
Ensure data is structured to be easily combined with:
CRM (accounts, deals)
external docs
Use consistent identifiers:
account IDs
deal IDs
MCP is available only for Scale tier and above
HIGH
Customers who are on Capture tier should be able to access any of their data through MCP.
This should also cover the scenario when a customer has been on Scale but then downgrades to Capture - their MCP access should stop working.
Provide visibility into how external AI tools access Jiminny data
HIGH
Audit logs:
what data was accessed by which external system when
identity - who made the request
specific queries/filters used
failed access attempts (especially cross-visibility-boundary attempts)
Admins should be able to access the logs from the org settings.We can start with a csv export before building a specific page for it.
example from Atlassian -
Provide customers with example prompts to get started quickly
HIGH
MCP prompts are explicitly defined as prompt templates that clients can discover and call with arguments.
See examples in table below.
Expose Jiminny as a Connector in Claude
medium
Competitors like Fathom are listed as Connectors in Claude. This will make it easier for customers to find us and to connect Jiminny
Provide customers with example workflows to get started quickly
medium
A workflow is usually multiple steps, maybe multiple tools, still focused on one outcome.
See examples in table below.
Allow customers to use predefined Jiminny skills for common workflows
medium
Anthropic describes Skills as folders that include instructions, scripts, and resources that Claude can load when relevant, and as a way to teach Claude repeatable workflows, preferences, and domain expertise once instead of re-explaining them every time. Skills - a reusable package of behavior that can include prompts, instructions, resources, and sometimes scripts/tools for a broader job.
Claude skills - https://resources.anthropic.com/hubfs/The-Complete-Guide-to-Building-Skill-for-Claude.pdf?hsLang=en&utm_source=chatgpt.com
See examples in table below.
Jiminny UI widget for OpenAI
medium
The reason to have this is to make certain Jiminny use cases much easier than pure chat.
Instead of ChatGPT only replying with text like “Here are the last 5 ACME calls,” it could also show a visual Jiminny card or mini-app inside the chat. That widget could list calls, show a deal summary, let the user filter by rep/date/account, open a transcript section, or save a snippet—while the conversation continues in normal chat alongside it.
For Jiminny, the best widget use cases are the ones where users need to browse or compare rather than ask one-off questions. A strong example is deal review: the user asks ChatGPT, “What is the status of the ACME deal?” ChatGPT calls your Jiminny MCP tools, and the widget shows a compact deal view with recent calls, risks, next steps, stakeholders, and links to transcripts/snippets. The chat can still summarize the answer in words, but the widget gives a clearer, scannable interface.
Another good Jiminny widget use case is call search and exploration. A text answer can say “I found 12 calls mentioning pricing objections,” but a widget could show a sortable list with date, rep, account, score, and objection count, then let the user click into one call to see the exact excerpt or jump to a transcript section.
Allow customers to run long-running analyses asynchronously and retrieve progress/results
low
Some requests/questions require analysis of Hugh volumes of data. For those, it may be better to:
start the job
let it run in the background
return a status like “in progress”
let the client come back for the result later
For example - User asks in Claude:
“Analyse all calls from this quarter and tell me the top 5 objections by segment.”
That might require:
searching lots of calls
pulling many summaries/transcripts
aggregating results
Instead of making Claude wait 45+ seconds, Jiminny could:
create an analysis job
return: job_id = 123, status = running
We need this in order to support:
large-scale analysis
multi-call aggregation across lots of data
playlist generation across many calls
heavy recap/report generation
Creating a snippet through the MCP
low
Create a shareable snippet from a call recording by specifying a time range. Useful for highlighting key moments — objection handling, pricing discussions, competitive mentions — and sharing them with your team.
example request:
{
"tool": "create_snippet",
"arguments": {
"call_id": "call_123",
"start_time": "00:18:24",
"end_time": "00:19:10",
"title": "Pricing objection"
}
}
example response:
{
"snippet_id": "snip_987",
"title": "Pricing objection",
"share_url": "https://app.jiminny.com/snippets/snip_987"
}
Ability to add recordings or snippets to a playlist
low
Allow customers to create libraries of calls automatically. They can use those for onboarding or other purposes
Allow AI tools to read reusable Jiminny resources
low
fathom
Resources are useful for data that should be read consistently rather than recomputed every time. In Jiminny terms, that could be:
current deal snapshot
account summary
weekly rep recap
approved talk tracks / objection handling guidance
curated playlists or snippet libraries
This is useful because an AI can consume these directly as context, instead of repeatedly stitching together many tool calls.
Ability to write coaching notes in Jiminny through MCP
low
What we want to do for prompts/worflows and skills
Capability
Type
User value / job to be done
Example Jiminny use case
Inputs
Steps performed
Output
Draft follow-up email
Prompt
Help reps quickly create tailored follow-ups after calls
Use the latest customer call to draft an email with recap and next steps
Call ID
optional tone
optional recipient type
Retrieve call summary and action items from Jiminny.
Pull key points, commitments, and next steps.
Apply the chosen tone and structure.
Draft the email in a consistent format.
Customer-ready follow-up email draft
Summarise call
Prompt
Help users quickly extract the most important points from a conversation
Generate a concise summary of one call for internal or external use
Call ID
optional summary style
optional audience
Retrieve transcript, metadata, and structured insights.
Identify key topics, decisions, risks, and next steps.
Format output for the chosen audience.
Short or structured call summary with actions and risks
Generate deal recap
Prompt
Help reps and managers get a fast overview of a deal
Summarise the current state of a deal based on recent calls and linked CRM context
Deal ID or account name
optional date range
Retrieve calls and meetings linked to the deal.
Pull deal metadata and CRM-linked context.
Identify recent changes, blockers, risks, and next steps.
Summarise into a concise recap.
Deal recap with status, blockers, risks, and recommended next steps
Prepare weekly recap
Prompt
Help managers or reps review what changed over a time period
Weekly recap of calls, themes, and actions for one rep, team, or account
Rep ID
team ID or account ID
time period
Retrieve relevant calls and summaries for the selected time period.
Aggregate themes, action items, and changes.
Highlight notable risks, opportunities, and follow-ups.
Weekly recap with top themes, risks, opportunities, and actions
Prepare deal review
Workflow
Help reps and managers review deal status using multiple sources of context
Review a deal before pipeline review or forecast meeting
Deal ID
optional date range
Retrieve all recent calls, emails, and meetings tied to the deal.
Pull structured call summaries, score, action items, and key points.
Pull linked CRM context such as stage, contacts, and account details.
Aggregate open risks, unresolved objections, stakeholder gaps, and next steps.
Format into a review-ready structure.
Deal review document with current status, risks, stakeholders, blockers, and next steps
Weekly team recap
Workflow
Help managers monitor activity and risk across a group of reps or accounts
End-of-week team summary for sales leadership
Team ID
date range
Retrieve calls and structured insights across the team.
Group by rep, account, or deal.
Identify recurring themes, major risks, strong calls, and missed follow-ups.
Highlight calls or deals that need attention.
Team-level recap with patterns, key risks, notable wins, and action areas
Objection analysis across calls
Workflow
Help teams identify patterns across multiple conversations
Analyse pricing or competitor objections across recent calls
Account ID
deal ID
rep ID
keyword/topic
date range
Search calls matching the topic or keyword.
Retrieve summaries, transcripts, and snippets where relevant.
Identify recurring objections and how they were handled.
Assess whether objections were resolved or remain open.
Summarise patterns and examples.
Objection analysis with themes, frequency, examples, and suggested follow-up actions
Build onboarding playlist
Workflow
Help enablement teams curate useful learning content faster
Build a playlist of strong discovery, demo, or pricing calls for new hires
Topic
call type
rep/team filter
optional time period
Search for calls matching the selected criteria.
Rank or filter calls based on score, topics, or key moments.
Identify useful snippets or full recordings.
Add selected calls/snippets into a playlist structure.
Generate short descriptions for each item.
Curated onboarding playlist with selected calls/snippets and descriptions
Deal Inspection Skill
Skill
Give users a consistent, opinionated way to assess a deal
Claude reviews a deal using a repeatable Jiminny methodology
Deal ID or account name
optional review scope
Determine whether the request is suitable for a deal inspection.
Retrieve relevant calls, summaries, CRM context, stakeholders, and risks.
Apply a standard Jiminny review framework to assess deal health.
Look for missing next steps, unresolved objections, stakeholder gaps, and warning signs.
Present findings in a consistent structure with recommended actions.
Structured deal inspection with health assessment, red flags, and recommendations
Manager Coaching Skill
Skill
Help managers review calls consistently and identify coaching moments
Analyse a rep’s call and surface strengths, gaps, and examples for coaching
Call ID
optional rep ID
optional coaching focus
Retrieve transcript, score, summary, and key moments from the call.
Evaluate the conversation against a coaching framework.
Identify what went well and where the rep could improve.
Suggest moments to clip as snippets.
Recommend coaching actions or playlist additions.
Coaching review with strengths, gaps, snippet suggestions, and recommended coaching actions
CSM / QBR Prep Skill
Skill
Help CS or AM teams prepare structured customer reviews from conversations
Generate an account review or QBR-style summary from recent customer interactions
Account ID, optional time period
Retrieve all recent calls, emails, and account-linked context.
Aggregate themes, requests, blockers, sentiment shifts, and opportunities.
Apply a repeatable account review structure.
Summarise outcomes, open issues, and suggested next steps.
Structured QBR/account review summary with themes, risks, opportunities, and actions
Snippet Builder Skill
Skill
Help users consistently capture and label useful moments from calls
Identify useful moments in a call and convert them into reusable snippets
Call ID, optional focus area such as pricing, objection, competitor, discovery
Retrieve transcript, recording timeline, and call insights.
Detect moments matching the requested focus area.
Propose snippet start/end times and titles.
Tag snippets by type or theme.
Optionally save them or add them to a playlist.
One or more proposed or saved snippets with title, timing, and tags
💡 Technical details
Auth model needs specifying. Are API keys scoped per user, per team, or per Jiminny instance? If a key is generated by an admin, does it inherit their visibility level, or provide org-wide? Are permissions evaluated at query time or frozen at key creation? Needs to be query-time, otherwise permission changes won't propagate.
Key lifecycle management is missing. No mention of rotation, expiry, or revocation. A departed employee's active key is a data leak. Need: revocation, optional expiry, alerts on stale keys, and consider whether keys should be tied to service accounts rather than personal users.
Rate limiting should be HIGH. A compromised key or misconfigured automation could bulk-export an entire customer's call history. Need per-key rate limits and anomaly detection on unusual access patterns.
Open Questions
Track unresolved issues or decisions that need to be made. Update as answers become available.
Question
Answer
Date Answered
Competitor research
Competitor
MCP Availability
Core Capabilities
Advanced Capabilities
Positioning
Key Strength
Key Weakness
Gong
✅ Mature MCP
List/search calls
Get transcripts
get Call metadata
Deal intelligence
Scorecards, analytics
CRM context
Enterprise data layer
Deep data + ecosystem integrations
Limited opinionated AI workflows
Avoma
✅ Mature MCP
list_meetings
get_meeting
get_transcript
key topics
Deal fields/Deal level analysis
Coaching/Scoring
CRM context
pushing insights into Notion / Confluence
AI-ready meeting intelligence
Strongest “outputs” layer
Mostly pull-based interactions
Fathom
✅ MCP
list/search meetings
get transcript
get summary/action items
Team/org context
Webhooks (event-based triggers)
get_weekly_recap
aggregated action items across meetings
creating webhooks directly from the MCP server
Lightweight meeting data access
Includes summaries + actions
Limited analytics depth
Grain
✅ Basic MCP
get meetings
download transcripts
Notes
Deals
Scorecards
Data access utility
Simple + accessible
Low sophistication, sometimes browser-based
Outreach
⚠️ MCP (workflow-focused)
Search sequences
Emails
Meetings (Kaia)
account / prospect / opportunity lookups
Workflow automation
Multi-system orchestration
Revenue workflow engine
End-to-end GTM workflows
Less depth in conversation data
Attention
⚠️ Emerging MCP
Meeting data
Transcripts
CRM-linked context
AI insights
Sales assistant workflows
create snippets
AI sales assistant + CRM
Strong CRM linkage
Less focus on external knowledge layer
Planhat -
Related content
Ask Jiminny Anything on Call level
Galya Dimitrova
Hubspot app
Galya Dimitrova
Product Vision & Strategy
Galya Dimitrova
Automated CRM Filling
Simona Georgieva (Deactivated)
Competitive analysis
Galya Dimitrova
AI agent ideas
Steliyan Georgiev
Comments
James Graham
9 Apr
A few areas around Security & Compliance that need more depth before this moves beyond draft:
Auth model needs specifying. Are API keys scoped per user, per team, or per Jiminny instance? If a key is generated by an admin, does it inherit their visibility level, or provide org-wide? Are permissions evaluated at query time or frozen at key creation? Needs to be query-time, otherwise permission changes won't propagate.
Team visibility enforcement should be its own HIGH requirement. The current note under access control ("ensure MCP only exposes data user has access to") is doing too much work as a single line. Every MCP tool response (especially search_calls and deal-level aggregations) must be filtered through the same visibility engine as the UI. Semantic search is the riskiest here; it could surface results across team boundaries if not properly scoped.
No data minimisation or scoping controls. We're exposing transcripts, CRM fields, contact details with job titles, deal context - significant PII and commercial data leaving the platform. Can customers configure which data types are exposed? Can transcripts be PII-stripped before they leave Jiminny? Given we position GDPR consent as a differentiator, we should be thinking about this.
GDPR downstream processing is unaddressed. Piping transcripts to OpenAI/Gemini introduces new data processors. Customers need to acknowledge responsibility for downstream processing during setup. We should also consider whether call participants' recording consent covers onward sharing to third-party AI - it almost certainly doesn't by default. This is one for me to pick up.
Key lifecycle management is missing. No mention of rotation, expiry, or revocation. A departed employee's active key is a data leak. Need: revocation, optional expiry, alerts on stale keys, and consider whether keys should be tied to service accounts rather than personal users.
Rate limiting should be HIGH. A compromised key or misconfigured automation could bulk-export an entire customer's call history. Need per-key rate limits and anomaly detection on unusual ac...
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Objective Enable customers to connect Jiminny data to external AI tools (Claude, OpenAI, Gemini) so it can be used as part of their broader knowledge base and workflows. Position Jiminny as a data layer for AI-driven revenue workflows, not just a standalone product. 👤 Target user Revenue teams using AI tools (Sales, CS, RevOps) Companies already experimenting with Claude / OpenAI Mid-market & Enterprise customers with multiple data sources (CRM, docs, CI tools, Support tools etc) 🤕 Pain point or problem Jiminny data is locked in the platform AI tools lack access to high-value conversation context Customers must manually export/copy transcripts No easy way to combine calls with CRM + docs + other info - using the Jiminny API is not suitable for non technical sales people Peer pressure as almost all competitors have this 💥 Impact and benefits For customers Better AI outputs using real customer conversations Ability to build automated workflows across tools For Jiminny Increased product stickiness (embedded in workflows) Competitive parity with Gong / Avoma etc. 💡 Solution ideas Build an AI Knowledge Connector (MCP-based) that: Exposes Jiminny data (calls, transcripts, metadata) to AI tools Provides structured insights (summaries, action items, scoring etc.) Supports deal-level context Allows integration into customer-owned AI stacks (Claude + Zapier, etc.) Success metrics List the key goals and how you will measure success. Include both qualitative and quantitative metrics (e.g., user adoption, retention rate, revenue targets). Goal Metric Increase stickiness by ensuring Jiminny is embedded in the customer’s workflows % of customers connecting external AI tools Number of MCP/API calls per customer - and which ones are being used the most Decrease the manual copying of transcripts decrease by X % User interaction and design Simple setup flow: Generate API key / connect MCP Clear instructions for Claude / Zapier setup Provide: Example prompts for Claude Pre-built workflow templates for Zapier Clear documentation - with use cases 👉 Focus: usable by non-technical users Detailed Requirements List the functional and non-functional requirements. Prioritize them (e.g., High, Medium, Low) and add notes for clarification. Requirement Importance Notes Allow customers to connect Jiminny to their AI tools (e.g. Claude, OpenAI) HIGH Provide MCP endpoint so customers can easily integrate Jiminny into their AI stack Allow customers to access call data through AI tools HIGH Expose Jiminny data: list calls (filter by date, user, account, deal) get call get transcript (speaker-separated) get call metadata search calls (keyword + semantic) Support filtering by: account / contact/ lead / deal jiminny user date range Allow customers to search and query calls using AI tools HIGH Support keyword and semantic search across conversations Provide structured insights so customers can generate better outputs HIGH For each call, expose: Summary Action items Key points Activity type Notes Call Score CRM information Allow customers to understand deal status across multiple calls/emails HIGH For each deal expose: calls/meetings/emails Identified risks contacts related to the deal with their job title linked account details all CRM field information that we have in DI + fields used for CRM filling example - get_deal_summary request - { \"tool\": \"get_deal_summary\", \"arguments\": { \"deal_name\": \"ACME\" } } responce: { \"deal_name\": \"ACME\", \"stage\": \"Negotiation\", \"recent_activity\": [ \"Demo call on 2026-04-01\", \"Pricing discussion on 2026-04-03\" ], \"risks\": [ \"Pricing concerns\", \"Security review pending\" ], \"next_steps\": [ \"Send follow-up to VP Sales\", \"Share security documentation\" ] } Ensure the AI can easily understand the schema of the data coming from Jiminny HIGH Models perform much better when tools have: clear names rich descriptions predictable schemas Provide clear, actionable error states for customers when MCP connections fail HIGH Error messages should guide agents toward solutions with specific suggestions and next steps. Expired or revoked key — “Error: Authentication failed. The API key used to access Jiminny has been revoked or has expired. Please ask your Jiminny admin to generate a new API key in Settings > Organization > General and reconnect the MCP server.” Rate limit hit — “Error: Rate limit exceeded. Too many requests have been made to the Jiminny MCP server in a short period. Please wait 60 seconds before retrying.” Permissions mismatch — if a user tries to access data outside their team visibility settings - “Error: Access denied. The requested call (call_id: [X]) is outside your team's visibility settings in Jiminny. Only calls within your permitted scope are accessible.” Trying to access private meeting - “Error: Access denied. This meeting has been marked as private by the host and cannot be accessed through the MCP connector. Try requesting a different call or ask the meeting host to change the visibility settings in Jiminny.” Downgraded/Capture account — if a customer's plan drops below Scale tier or the Customer is on Capture in the first place - “Error: MCP access unavailable. The Jiminny MCP connector is available on the Scale plan and above. Your account does not currently have an active Scale subscription.” Jiminny-side outage — “Error:Jiminny is temporarily unavailable (status 503). This is not a data or permissions issue — please retry in a few minutes.” No data found - “Error:No calls found matching your criteria. Try adjusting your filters — for example, widening the date range, removing the account filter, or checking the rep name is spelled correctly in Jiminny.” Allow customers to securely control who and what data is accessible externally HIGH Ensure MCP only exposes data user has access to - based on team visibility settings. This means that if a user is not allow to access calls/deals in Jiminny UI then they shouldn’t be able to access those through the MCP as well. Private meetings shouldn’t be exposed via MCP HIGH When a meetings is set to Private then the information about it shouldn’t be exposed through the MCP. Ensure Jiminny data can be combined with other sources (e.g. CRM, docs) in AI workflows HIGH Ensure data is structured to be easily combined with: CRM (accounts, deals) external docs Use consistent identifiers: account IDs deal IDs MCP is available only for Scale tier and above HIGH Customers who are on Capture tier should be able to access any of their data through MCP. This should also cover the scenario when a customer has been on Scale but then downgrades to Capture - their MCP access should stop working. Provide visibility into how external AI tools access Jiminny data HIGH Audit logs: what data was accessed by which external system when identity - who made the request specific queries/filters used failed access attempts (especially cross-visibility-boundary attempts) Admins should be able to access the logs from the org settings.We can start with a csv export before building a specific page for it. example from Atlassian - Provide customers with example prompts to get started quickly HIGH MCP prompts are explicitly defined as prompt templates that clients can discover and call with arguments. See examples in table below. Expose Jiminny as a Connector in Claude medium Competitors like Fathom are listed as Connectors in Claude. This will make it easier for customers to find us and to connect Jiminny Provide customers with example workflows to get started quickly medium A workflow is usually multiple steps, maybe multiple tools, still focused on one outcome. See examples in table below. Allow customers to use predefined Jiminny skills for common workflows medium Anthropic describes Skills as folders that include instructions, scripts, and resources that Claude can load when relevant, and as a way to teach Claude repeatable workflows, preferences, and domain expertise once instead of re-explaining them every time. Skills - a reusable package of behavior that can include prompts, instructions, resources, and sometimes scripts/tools for a broader job. Claude skills - https://resources.anthropic.com/hubfs/The-Complete-Guide-to-Building-Skill-for-Claude.pdf?hsLang=en&utm_source=chatgpt.com See examples in table below. Jiminny UI widget for OpenAI medium The reason to have this is to make certain Jiminny use cases much easier than pure chat. Instead of ChatGPT only replying with text like “Here are the last 5 ACME calls,” it could also show a visual Jiminny card or mini-app inside the chat. That widget could list calls, show a deal summary, let the user filter by rep/date/account, open a transcript section, or save a snippet—while the conversation continues in normal chat alongside it. For Jiminny, the best widget use cases are the ones where users need to browse or compare rather than ask one-off questions. A strong example is deal review: the user asks ChatGPT, “What is the status of the ACME deal?” ChatGPT calls your Jiminny MCP tools, and the widget shows a compact deal view with recent calls, risks, next steps, stakeholders, and links to transcripts/snippets. The chat can still summarize the answer in words, but the widget gives a clearer, scannable interface. Another good Jiminny widget use case is call search and exploration. A text answer can say “I found 12 calls mentioning pricing objections,” but a widget could show a sortable list with date, rep, account, score, and objection count, then let the user click into one call to see the exact excerpt or jump to a transcript section. Allow customers to run long-running analyses asynchronously and retrieve progress/results low Some requests/questions require analysis of Hugh volumes of data. For those, it may be better to: start the job let it run in the background return a status like “in progress” let the client come back for the result later For example - User asks in Claude: “Analyse all calls from this quarter and tell me the top 5 objections by segment.” That might require: searching lots of calls pulling many summaries/transcripts aggregating results Instead of making Claude wait 45+ seconds, Jiminny could: create an analysis job return: job_id = 123, status = running We need this in order to support: large-scale analysis multi-call aggregation across lots of data playlist generation across many calls heavy recap/report generation Creating a snippet through the MCP low Create a shareable snippet from a call recording by specifying a time range. Useful for highlighting key moments — objection handling, pricing discussions, competitive mentions — and sharing them with your team. example request: { \"tool\": \"create_snippet\", \"arguments\": { \"call_id\": \"call_123\", \"start_time\": \"00:18:24\", \"end_time\": \"00:19:10\", \"title\": \"Pricing objection\" } } example response: { \"snippet_id\": \"snip_987\", \"title\": \"Pricing objection\", \"share_url\": \"https://app.jiminny.com/snippets/snip_987\" } Ability to add recordings or snippets to a playlist low Allow customers to create libraries of calls automatically. They can use those for onboarding or other purposes Allow AI tools to read reusable Jiminny resources low fathom Resources are useful for data that should be read consistently rather than recomputed every time. In Jiminny terms, that could be: current deal snapshot account summary weekly rep recap approved talk tracks / objection handling guidance curated playlists or snippet libraries This is useful because an AI can consume these directly as context, instead of repeatedly stitching together many tool calls. Ability to write coaching notes in Jiminny through MCP low What we want to do for prompts/worflows and skills Capability Type User value / job to be done Example Jiminny use case Inputs Steps performed Output Draft follow-up email Prompt Help reps quickly create tailored follow-ups after calls Use the latest customer call to draft an email with recap and next steps Call ID optional tone optional recipient type Retrieve call summary and action items from Jiminny. Pull key points, commitments, and next steps. Apply the chosen tone and structure. Draft the email in a consistent format. Customer-ready follow-up email draft Summarise call Prompt Help users quickly extract the most important points from a conversation Generate a concise summary of one call for internal or external use Call ID optional summary style optional audience Retrieve transcript, metadata, and structured insights. Identify key topics, decisions, risks, and next steps. Format output for the chosen audience. Short or structured call summary with actions and risks Generate deal recap Prompt Help reps and managers get a fast overview of a deal Summarise the current state of a deal based on recent calls and linked CRM context Deal ID or account name optional date range Retrieve calls and meetings linked to the deal. Pull deal metadata and CRM-linked context. Identify recent changes, blockers, risks, and next steps. Summarise into a concise recap. Deal recap with status, blockers, risks, and recommended next steps Prepare weekly recap Prompt Help managers or reps review what changed over a time period Weekly recap of calls, themes, and actions for one rep, team, or account Rep ID team ID or account ID time period Retrieve relevant calls and summaries for the selected time period. Aggregate themes, action items, and changes. Highlight notable risks, opportunities, and follow-ups. Weekly recap with top themes, risks, opportunities, and actions Prepare deal review Workflow Help reps and managers review deal status using multiple sources of context Review a deal before pipeline review or forecast meeting Deal ID optional date range Retrieve all recent calls, emails, and meetings tied to the deal. Pull structured call summaries, score, action items, and key points. Pull linked CRM context such as stage, contacts, and account details. Aggregate open risks, unresolved objections, stakeholder gaps, and next steps. Format into a review-ready structure. Deal review document with current status, risks, stakeholders, blockers, and next steps Weekly team recap Workflow Help managers monitor activity and risk across a group of reps or accounts End-of-week team summary for sales leadership Team ID date range Retrieve calls and structured insights across the team. Group by rep, account, or deal. Identify recurring themes, major risks, strong calls, and missed follow-ups. Highlight calls or deals that need attention. Team-level recap with patterns, key risks, notable wins, and action areas Objection analysis across calls Workflow Help teams identify patterns across multiple conversations Analyse pricing or competitor objections across recent calls Account ID deal ID rep ID keyword/topic date range Search calls matching the topic or keyword. Retrieve summaries, transcripts, and snippets where relevant. Identify recurring objections and how they were handled. Assess whether objections were resolved or remain open. Summarise patterns and examples. Objection analysis with themes, frequency, examples, and suggested follow-up actions Build onboarding playlist Workflow Help enablement teams curate useful learning content faster Build a playlist of strong discovery, demo, or pricing calls for new hires Topic call type rep/team filter optional time period Search for calls matching the selected criteria. Rank or filter calls based on score, topics, or key moments. Identify useful snippets or full recordings. Add selected calls/snippets into a playlist structure. Generate short descriptions for each item. Curated onboarding playlist with selected calls/snippets and descriptions Deal Inspection Skill Skill Give users a consistent, opinionated way to assess a deal Claude reviews a deal using a repeatable Jiminny methodology Deal ID or account name optional review scope Determine whether the request is suitable for a deal inspection. Retrieve relevant calls, summaries, CRM context, stakeholders, and risks. Apply a standard Jiminny review framework to assess deal health. Look for missing next steps, unresolved objections, stakeholder gaps, and warning signs. Present findings in a consistent structure with recommended actions. Structured deal inspection with health assessment, red flags, and recommendations Manager Coaching Skill Skill Help managers review calls consistently and identify coaching moments Analyse a rep’s call and surface strengths, gaps, and examples for coaching Call ID optional rep ID optional coaching focus Retrieve transcript, score, summary, and key moments from the call. Evaluate the conversation against a coaching framework. Identify what went well and where the rep could improve. Suggest moments to clip as snippets. Recommend coaching actions or playlist additions. Coaching review with strengths, gaps, snippet suggestions, and recommended coaching actions CSM / QBR Prep Skill Skill Help CS or AM teams prepare structured customer reviews from conversations Generate an account review or QBR-style summary from recent customer interactions Account ID, optional time period Retrieve all recent calls, emails, and account-linked context. Aggregate themes, requests, blockers, sentiment shifts, and opportunities. Apply a repeatable account review structure. Summarise outcomes, open issues, and suggested next steps. Structured QBR/account review summary with themes, risks, opportunities, and actions Snippet Builder Skill Skill Help users consistently capture and label useful moments from calls Identify useful moments in a call and convert them into reusable snippets Call ID, optional focus area such as pricing, objection, competitor, discovery Retrieve transcript, recording timeline, and call insights. Detect moments matching the requested focus area. Propose snippet start/end times and titles. Tag snippets by type or theme. Optionally save them or add them to a playlist. One or more proposed or saved snippets with title, timing, and tags 💡 Technical details Auth model needs specifying. Are API keys scoped per user, per team, or per Jiminny instance? If a key is generated by an admin, does it inherit their visibility level, or provide org-wide? Are permissions evaluated at query time or frozen at key creation? Needs to be query-time, otherwise permission changes won't propagate. Key lifecycle management is missing. No mention of rotation, expiry, or revocation. A departed employee's active key is a data leak. Need: revocation, optional expiry, alerts on stale keys, and consider whether keys should be tied to service accounts rather than personal users. Rate limiting should be HIGH. A compromised key or misconfigured automation could bulk-export an entire customer's call history. Need per-key rate limits and anomaly detection on unusual access patterns. Open Questions Track unresolved issues or decisions that need to be made. Update as answers become available. Question Answer Date Answered Competitor research Competitor MCP Availability Core Capabilities Advanced Capabilities Positioning Key Strength Key Weakness Gong ✅ Mature MCP List/search calls Get transcripts get Call metadata Deal intelligence Scorecards, analytics CRM context Enterprise data layer Deep data + ecosystem integrations Limited opinionated AI workflows Avoma ✅ Mature MCP list_meetings get_meeting get_transcript key topics Deal fields/Deal level analysis Coaching/Scoring CRM context pushing insights into Notion / Confluence AI-ready meeting intelligence Strongest “outputs” layer Mostly pull-based interactions Fathom ✅ MCP list/search meetings get transcript get summary/action items Team/org context Webhooks (event-based triggers) get_weekly_recap aggregated action items across meetings creating webhooks directly from the MCP server Lightweight meeting data access Includes summaries + actions Limited analytics depth Grain ✅ Basic MCP get meetings download transcripts Notes Deals Scorecards Data access utility Simple + accessible Low sophistication, sometimes browser-based Outreach ⚠️ MCP (workflow-focused) Search sequences Emails Meetings (Kaia) account / prospect / opportunity lookups Workflow automation Multi-system orchestration Revenue workflow engine End-to-end GTM workflows Less depth in conversation data Attention ⚠️ Emerging MCP Meeting data Transcripts CRM-linked context AI insights Sales assistant workflows create snippets AI sales assistant + CRM Strong CRM linkage Less focus on external knowledge layer Planhat - Related content Ask Jiminny Anything on Call level Galya Dimitrova Hubspot app Galya Dimitrova Product Vision & Strategy Galya Dimitrova Automated CRM Filling Simona Georgieva (Deactivated) Competitive analysis Galya Dimitrova AI agent ideas Steliyan Georgiev Comments James Graham 9 Apr A few areas around Security & Compliance that need more depth before this moves beyond draft: Auth model needs specifying. Are API keys scoped per user, per team, or per Jiminny instance? If a key is generated by an admin, does it inherit their visibility level, or provide org-wide? Are permissions evaluated at query time or frozen at key creation? Needs to be query-time, otherwise permission changes won't propagate. Team visibility enforcement should be its own HIGH requirement. The current note under access control (\"ensure MCP only exposes data user has access to\") is doing too much work as a single line. Every MCP tool response (especially search_calls and deal-level aggregations) must be filtered through the same visibility engine as the UI. Semantic search is the riskiest here; it could surface results across team boundaries if not properly scoped. No data minimisation or scoping controls. We're exposing transcripts, CRM fields, contact details with job titles, deal context - significant PII and commercial data leaving the platform. Can customers configure which data types are exposed? Can transcripts be PII-stripped before they leave Jiminny? Given we position GDPR consent as a differentiator, we should be thinking about this. GDPR downstream processing is unaddressed. Piping transcripts to OpenAI/Gemini introduces new data processors. Customers need to acknowledge responsibility for downstream processing during setup. We should also consider whether call participants' recording consent covers onward sharing to third-party AI - it almost certainly doesn't by default. This is one for me to pick up. Key lifecycle management is missing. No mention of rotation, expiry, or revocation. A departed employee's active key is a data leak. Need: revocation, optional expiry, alerts on stale keys, and consider whether keys should be tied to service accounts rather than personal users. Rate limiting should be HIGH. A compromised key or misconfigured automation could bulk-export an entire customer's call history. Need per-key rate limits and anomaly detection on unusual access patterns. Audit logs should go deeper. Current spec (what data, which system, when) is a start. Add: identity behind the key, specific queries/filters used, and failed access attempts (especially cross-visibility-boundary attempts). Enterprise compliance teams will expect this. Downgrade handling. Doc says Scale tier and above, but doesn't say what happens on downgrade. Keys should auto-deactivate. Happy to help draft a dedicated Security & Compliance section if useful. Galya Dimitrova 15 Apr Thanks for the input @James Graham . I made the product related changes in the table and for the rest I left them as a note in the Technical section for the team to look at when they start looking at this. I wonder about your points related to GDPR. Currently multiple customers are using the Customer API/zapier to feed this data to AI and BI tools. They are also manually exporting transcripts and other information from the platform and feeding it to AI tools. I don’t get how MCP is so much different that all of these and why it will introduce new data processors (which are already being utilised) and would require any changes to the consent provided by participants.","depth":21,"bounds":{"left":0.41805187,"top":0.19313647,"width":0.051861703,"height":0.11173184},"help_text":"","role_description":"heading","subrole":"AXUnknown"},{"role":"AXStaticText","text":"You said","depth":23,"bounds":{"left":0.36053857,"top":0.19553073,"width":0.019946808,"height":0.016360734},"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"Jiminny MCP Connector","depth":23,"bounds":{"left":0.41805187,"top":0.1963288,"width":0.03125,"height":0.038707104},"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"Epic","depth":23,"bounds":{"left":0.41805187,"top":0.30806065,"width":0.010305851,"height":0.016360734},"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"Link to Epik in Jira","depth":23,"bounds":{"left":0.41805187,"top":0.33040702,"width":0.043218084,"height":0.016360734},"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"Document status","depth":23,"bounds":{"left":0.41805187,"top":0.3527534,"width":0.04105718,"height":0.016360734},"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"DRAFT","depth":23,"bounds":{"left":0.41805187,"top":0.37509975,"width":0.016289894,"height":0.016360734},"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"Objective","depth":23,"bounds":{"left":0.41805187,"top":0.39744613,"width":0.024268618,"height":0.016360734},"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"Enable customers to connect Jiminny data to external AI tools (Claude, OpenAI, Gemini) so it can be used as part of their broader knowledge base and workflows.","depth":23,"bounds":{"left":0.41805187,"top":0.4197925,"width":0.051529255,"height":0.17278531},"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"Position Jiminny as a data layer for AI-driven revenue workflows, not just a standalone product.","depth":23,"bounds":{"left":0.41805187,"top":0.59856343,"width":0.049700797,"height":0.10574621},"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"👤 Target user","depth":23,"bounds":{"left":0.41805187,"top":0.75458896,"width":0.033909574,"height":0.016759777},"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"Revenue teams using AI tools (Sales, CS, RevOps)","depth":23,"bounds":{"left":0.41805187,"top":0.7773344,"width":0.051030584,"height":0.061053474},"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"Companies already experimenting with Claude / OpenAI","depth":23,"bounds":{"left":0.41805187,"top":0.8443735,"width":0.04637633,"height":0.061053474},"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"Mid-market & Enterprise customers with multiple data sources (CRM, docs, CI tools, Support tools etc)","depth":23,"bounds":{"left":0.41805187,"top":0.9114126,"width":0.051363032,"height":0.0885874},"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"🤕 Pain point or problem","depth":23,"bounds":{"left":0.41805187,"top":1.0,"width":0.03706782,"height":-0.0897845},"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"Jiminny data is locked in the platform","depth":23,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"AI tools lack access to high-value conversation context","depth":23,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"Customers must manually export/copy transcripts","depth":23,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"No easy way to combine calls with CRM + docs + other info - 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The API key used to access Jiminny has been revoked or has expired. Please ask your Jiminny admin to generate a new API key in Settings > Organization > General and reconnect the MCP server.”","depth":23,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"Rate limit hit — “Error: Rate limit exceeded. Too many requests have been made to the Jiminny MCP server in a short period. Please wait 60 seconds before retrying.”","depth":23,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"Permissions mismatch — if a user tries to access data outside their team visibility settings - “Error: Access denied. The requested call (call_id: [X]) is outside your team's visibility settings in Jiminny. Only calls within your permitted scope are accessible.”","depth":23,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"Trying to access private meeting - “Error: Access denied. 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This is not a data or permissions issue — please retry in a few minutes.”","depth":23,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"No data found - “Error:No calls found matching your criteria. Try adjusting your filters — for example, widening the date range, removing the account filter, or checking the rep name is spelled correctly in Jiminny.”","depth":23,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"Allow customers to securely control who and what data is accessible externally","depth":23,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"HIGH","depth":23,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"Ensure MCP only exposes data user has access to - based on team visibility settings. 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This will make it easier for customers to find us and to connect Jiminny","depth":23,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"Provide customers with example workflows to get started quickly","depth":23,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"medium","depth":23,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"A workflow is usually multiple steps, maybe multiple tools, still focused on one outcome.","depth":23,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"See examples in table below.","depth":23,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"Allow customers to use predefined Jiminny skills for common workflows","depth":23,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"medium","depth":23,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"Anthropic describes Skills as folders that include instructions, scripts, and resources that Claude can load when relevant, and as a way to teach Claude repeatable workflows, preferences, and domain expertise once instead of re-explaining them every time. Skills - a reusable package of behavior that can include prompts, instructions, resources, and sometimes scripts/tools for a broader job.","depth":23,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"Claude skills - https://resources.anthropic.com/hubfs/The-Complete-Guide-to-Building-Skill-for-Claude.pdf?hsLang=en&utm_source=chatgpt.com","depth":23,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"See examples in table below.","depth":23,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"Jiminny UI widget for OpenAI","depth":23,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"medium","depth":23,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"The reason to have this is to make certain Jiminny use cases much easier than pure chat.","depth":23,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"Instead of ChatGPT only replying with text like “Here are the last 5 ACME calls,” it could also show a visual Jiminny card or mini-app inside the chat. That widget could list calls, show a deal summary, let the user filter by rep/date/account, open a transcript section, or save a snippet—while the conversation continues in normal chat alongside it.","depth":23,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"For Jiminny, the best widget use cases are the ones where users need to browse or compare rather than ask one-off questions. A strong example is deal review: the user asks ChatGPT, “What is the status of the ACME deal?” ChatGPT calls your Jiminny MCP tools, and the widget shows a compact deal view with recent calls, risks, next steps, stakeholders, and links to transcripts/snippets. The chat can still summarize the answer in words, but the widget gives a clearer, scannable interface.","depth":23,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"Another good Jiminny widget use case is call search and exploration. A text answer can say “I found 12 calls mentioning pricing objections,” but a widget could show a sortable list with date, rep, account, score, and objection count, then let the user click into one call to see the exact excerpt or jump to a transcript section.","depth":23,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"Allow customers to run long-running analyses asynchronously and retrieve progress/results","depth":23,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"low","depth":23,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"Some requests/questions require analysis of Hugh volumes of data. 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Useful for highlighting key moments — objection handling, pricing discussions, competitive mentions — and sharing them with your team.","depth":23,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"example request:","depth":23,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"{","depth":23,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"\"tool\": \"create_snippet\",","depth":23,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"\"arguments\": {","depth":23,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"\"call_id\": \"call_123\",","depth":23,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"\"start_time\": \"00:18:24\",","depth":23,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"\"end_time\": \"00:19:10\",","depth":23,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"\"title\": \"Pricing objection\"","depth":23,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"}","depth":23,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"}","depth":23,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"example response:","depth":23,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"{","depth":23,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"\"snippet_id\": \"snip_987\",","depth":23,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"\"title\": \"Pricing objection\",","depth":23,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"\"share_url\": \"https://app.jiminny.com/snippets/snip_987\"","depth":23,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"}","depth":23,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"Ability to add recordings or snippets to a playlist","depth":23,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"low","depth":23,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"Allow customers to create libraries of calls automatically. They can use those for onboarding or other purposes","depth":23,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"Allow AI tools to read reusable Jiminny resources","depth":23,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"low","depth":23,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"fathom","depth":23,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"Resources are useful for data that should be read consistently rather than recomputed every time. In Jiminny terms, that could be:","depth":23,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"current deal snapshot","depth":23,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"account summary","depth":23,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"weekly rep recap","depth":23,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"approved talk tracks / objection handling guidance","depth":23,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"curated playlists or snippet libraries","depth":23,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"This is useful because an AI can consume these directly as context, instead of repeatedly stitching together many tool calls.","depth":23,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"Ability to write coaching notes in Jiminny through MCP","depth":23,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"low","depth":23,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"What we want to do for prompts/worflows and skills","depth":23,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"Capability","depth":23,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"Type","depth":23,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"User value / job to be done","depth":23,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"Example Jiminny use 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Are API keys scoped per user, per team, or per Jiminny instance? If a key is generated by an admin, does it inherit their visibility level, or provide org-wide? Are permissions evaluated at query time or frozen at key creation? Needs to be query-time, otherwise permission changes won't propagate.","depth":23,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"Team visibility enforcement should be its own HIGH requirement. The current note under access control (\"ensure MCP only exposes data user has access to\") is doing too much work as a single line. Every MCP tool response (especially search_calls and deal-level aggregations) must be filtered through the same visibility engine as the UI. Semantic search is the riskiest here; it could surface results across team boundaries if not properly scoped.","depth":23,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"No data minimisation or scoping controls. We're exposing transcripts, CRM fields, contact details with job titles, deal context - significant PII and commercial data leaving the platform. Can customers configure which data types are exposed? Can transcripts be PII-stripped before they leave Jiminny? Given we position GDPR consent as a differentiator, we should be thinking about this.","depth":23,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"GDPR downstream processing is unaddressed. Piping transcripts to OpenAI/Gemini introduces new data processors. Customers need to acknowledge responsibility for downstream processing during setup. We should also consider whether call participants' recording consent covers onward sharing to third-party AI - it almost certainly doesn't by default. This is one for me to pick up.","depth":23,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"Key lifecycle management is missing. No mention of rotation, expiry, or revocation. A departed employee's active key is a data leak. Need: revocation, optional expiry, alerts on stale keys, and consider whether keys should be tied to service accounts rather than personal users.","depth":23,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"Rate limiting should be HIGH. A compromised key or misconfigured automation could bulk-export an entire customer's call history. Need per-key rate limits and anomaly detection on unusual access patterns.","depth":23,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"Audit logs should go deeper. Current spec (what data, which system, when) is a start. Add: identity behind the key, specific queries/filters used, and failed access attempts (especially cross-visibility-boundary attempts). Enterprise compliance teams will expect this.","depth":23,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"Downgrade handling. Doc says Scale tier and above, but doesn't say what happens on downgrade. Keys should auto-deactivate.","depth":23,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"Happy to help draft a dedicated Security & Compliance section if useful.","depth":23,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"Galya Dimitrova","depth":23,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"15 Apr","depth":23,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"Thanks for the input @James Graham . I made the product related changes in the table and for the rest I left them as a note in the Technical section for the team to look at when they start looking at this.","depth":23,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"I wonder about your points related to GDPR. Currently multiple customers are using the Customer API/zapier to feed this data to AI and BI tools. They are also manually exporting transcripts and other information from the platform and feeding it to AI tools. I don’t get how MCP is so much different that all of these and why it will introduce new data processors (which are already being utilised) and would require any changes to the consent provided by participants.","depth":23,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXButton","text":"Expand","depth":21,"bounds":{"left":0.46991357,"top":0.19313647,"width":0.013297873,"height":0.031923383},"role_description":"button","subrole":"AXUnknown","is_enabled":true,"is_focused":false,"is_selected":false},{"role":"AXButton","text":"Listen","depth":22,"bounds":{"left":0.47523272,"top":0.3367917,"width":0.013297873,"height":0.031923383},"help_text":"","role_description":"button","subrole":"AXUnknown","is_enabled":true,"is_focused":false,"is_selected":false},{"role":"AXButton","text":"Show more options","depth":20,"bounds":{"left":0.47523272,"top":0.3312051,"width":0.013297873,"height":0.031923383},"role_description":"button","subrole":"AXUnknown","is_enabled":true,"is_focused":false,"is_selected":false},{"role":"AXStaticText","text":"Show thinking","depth":26,"bounds":{"left":0.3828125,"top":0.33918595,"width":0.030917553,"height":0.014764565},"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXHeading","text":"Gemini said","depth":20,"bounds":{"left":0.3804854,"top":0.38068634,"width":0.0003324468,"height":0.0007980846},"help_text":"","role_description":"heading","subrole":"AXUnknown"},{"role":"AXStaticText","text":"Gemini said","depth":21,"bounds":{"left":0.3804854,"top":0.38268158,"width":0.04105718,"height":0.01915403},"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"Thank you for sharing the draft PRD for the","depth":24,"bounds":{"left":0.3695146,"top":0.39026338,"width":0.10521942,"height":0.016360734},"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"Jiminny MCP Connector","depth":24,"bounds":{"left":0.3695146,"top":0.41101357,"width":0.0625,"height":0.016360734},"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":". It looks like a highly strategic initiative to transition Jiminny from a standalone platform into a foundational data layer for AI-driven revenue workflows.","depth":24,"bounds":{"left":0.3695146,"top":0.41101357,"width":0.11319814,"height":0.07861133},"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"Here is a quick breakdown of the document as it currently stands:","depth":24,"bounds":{"left":0.3695146,"top":0.5067837,"width":0.11635638,"height":0.037110932},"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXHeading","text":"Executive Summary","depth":23,"bounds":{"left":0.3695146,"top":0.56823623,"width":0.11635638,"height":0.01915403},"help_text":"","role_description":"heading","subrole":"AXUnknown"},{"role":"AXStaticText","text":"Executive Summary","depth":24,"bounds":{"left":0.3695146,"top":0.5698324,"width":0.051363032,"height":0.016360734},"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"Core Objective:","depth":26,"bounds":{"left":0.38115028,"top":0.5961692,"width":0.040392287,"height":0.016360734},"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"Build an MCP-based AI Knowledge Connector to expose Jiminny data (transcripts, summaries, deal context) to external AI tools like Claude, OpenAI, and Gemini.","depth":26,"bounds":{"left":0.38115028,"top":0.5961692,"width":0.10472074,"height":0.09936153},"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"Target Value:","depth":26,"bounds":{"left":0.38115028,"top":0.70630485,"width":0.03374335,"height":0.016360734},"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"Increases product stickiness, reduces manual data entry/copy-pasting, and achieves competitive parity with platforms like Gong and Avoma.","depth":26,"bounds":{"left":0.38115028,"top":0.70630485,"width":0.10305851,"height":0.07861133},"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"Key Capabilities:","depth":26,"bounds":{"left":0.38115028,"top":0.79569036,"width":0.043550532,"height":0.016360734},"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"* Call and deal-level data retrieval.","depth":26,"bounds":{"left":0.38115028,"top":0.79569036,"width":0.09458112,"height":0.037110932},"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"Semantic and keyword search.","depth":28,"bounds":{"left":0.39145613,"top":0.8435754,"width":0.073803194,"height":0.016360734},"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"Pre-built prompts, workflows, and skills (e.g., deal inspection, objection analysis).","depth":28,"bounds":{"left":0.39145613,"top":0.8707103,"width":0.08976064,"height":0.057861134},"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"Current Bottlenecks & Discussions:","depth":26,"bounds":{"left":0.38115028,"top":0.9393456,"width":0.09142287,"height":0.016360734},"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"James Graham has flagged several critical security and compliance considerations (auth modeling, data minimization, key lifecycle, rate limiting, and GDPR downstream processing). Galya has integrated some of these into the technical requirements but pushed back on the GDPR point, noting that customers already export this data manually or via standard APIs.","depth":26,"bounds":{"left":0.38115028,"top":0.9393456,"width":0.10472074,"height":0.0606544},"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"Since you shared the document without a specific prompt, how would you like to proceed—would you like help drafting a response to Galya's GDPR question, refining the technical requirements based on James's feedback, or summarizing this into a pitch for stakeholders?","depth":24,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXTextArea","text":"Enter a prompt for Gemini\nencrypted","depth":20,"bounds":{"left":0.37416887,"top":0.8104549,"width":0.10638298,"height":0.01915403},"value":"Enter a prompt for Gemini\nencrypted","help_text":"","role_description":"text entry area","subrole":"AXUnknown","is_enabled":true,"is_focused":false,"is_selected":false},{"role":"AXStaticText","text":"Enter a prompt for Gemini","depth":21,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"encrypted","depth":21,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXButton","text":"Open upload file menu","depth":20,"bounds":{"left":0.37017953,"top":0.8447725,"width":0.013297873,"height":0.031923383},"role_description":"button","subrole":"AXUnknown","is_enabled":true,"is_focused":false,"is_selected":false,"is_expanded":false},{"role":"AXButton","text":"Tools","depth":18,"bounds":{"left":0.38613698,"top":0.8447725,"width":0.013297873,"height":0.031923383},"help_text":"","role_description":"button","subrole":"AXUnknown","is_enabled":true,"is_focused":false,"is_selected":false,"is_expanded":false},{"role":"AXButton","text":"Open mode picker","depth":20,"bounds":{"left":0.4431516,"top":0.8439745,"width":0.026097074,"height":0.031923383},"help_text":"","role_description":"button","subrole":"AXUnknown","is_enabled":true,"is_focused":false,"is_selected":false},{"role":"AXStaticText","text":"Pro","depth":23,"bounds":{"left":0.44847074,"top":0.8527534,"width":0.007480053,"height":0.014764565},"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXCheckBox","text":"Microphone","depth":19,"bounds":{"left":0.47124335,"top":0.8439745,"width":0.013297873,"height":0.031923383},"role_description":"toggle button","subrole":"AXToggle","is_enabled":true,"is_focused":false,"is_selected":false},{"role":"AXStaticText","text":"Your Jiminny chats aren’t used to improve our models. Gemini is AI and can make mistakes, including about people.","depth":17,"bounds":{"left":0.3665226,"top":0.896249,"width":0.12167553,"height":0.025139665},"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXLink","text":"Your privacy & Gemini Opens in a new window","depth":17,"bounds":{"left":0.40724733,"top":0.92178774,"width":0.040226065,"height":0.012370312},"help_text":"","role_description":"link","subrole":"AXUnknown","is_enabled":true,"is_focused":false,"is_selected":false}]...
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Platform Sprint 2 Q2 - Platform Team - Scrum Board Platform Sprint 2 Q2 - Platform Team - Scrum Board - Jira
SevenShores\Hubspot\Exceptions\BadRequest: Client error: `POST [URL_WITH_CREDENTIALS] Graham . I made the product related changes in the table and for the rest I left them as a note in the Technical section for the team to look at when they start looking at this. I wonder about your points related to GDPR. Currently multiple customers are using the Customer API/zapier to feed this data to AI and BI tools. They are also manually exporting transcripts and other information from the platform and feeding it to AI tools. I don’t get how MCP is so much different that all of these and why it will introduce new data processors (which are already being utilised) and would require any changes to the consent provided by participants.
You said
Jiminny MCP Connector
Epic
Link to Epik in Jira
Document status
DRAFT
Objective
Enable customers to connect Jiminny data to external AI tools (Claude, OpenAI, Gemini) so it can be used as part of their broader knowledge base and workflows.
Position Jiminny as a data layer for AI-driven revenue workflows, not just a standalone product.
👤 Target user
Revenue teams using AI tools (Sales, CS, RevOps)
Companies already experimenting with Claude / OpenAI
Mid-market & Enterprise customers with multiple data sources (CRM, docs, CI tools, Support tools etc)
🤕 Pain point or problem
Jiminny data is locked in the platform
AI tools lack access to high-value conversation context
Customers must manually export/copy transcripts
No easy way to combine calls with CRM + docs + other info - using the Jiminny API is not suitable for non technical sales people
Peer pressure as almost all competitors have this
💥 Impact and benefits
For customers
Better AI outputs using real customer conversations
Ability to build automated workflows across tools
For Jiminny
Increased product stickiness (embedded in workflows)
Competitive parity with Gong / Avoma etc.
💡 Solution ideas
Build an AI Knowledge Connector (MCP-based) that:
Exposes Jiminny data (calls, transcripts, metadata) to AI tools
Provides structured insights (summaries, action items, scoring etc.)
Supports deal-level context
Allows integration into customer-owned AI stacks (Claude + Zapier, etc.)
Success metrics
List the key goals and how you will measure success. Include both qualitative and quantitative metrics (e.g., user adoption, retention rate, revenue targets).
Goal
Metric
Increase stickiness by ensuring Jiminny is embedded in the customer’s workflows
% of customers connecting external AI tools
Number of MCP/API calls per customer - and which ones are being used the most
Decrease the manual copying of transcripts
decrease by X %
User interaction and design
Simple setup flow:
Generate API key / connect MCP
Clear instructions for Claude / Zapier setup
Provide:
Example prompts for Claude
Pre-built workflow templates for Zapier
Clear documentation - with use cases
👉 Focus: usable by non-technical users
Detailed Requirements
List the functional and non-functional requirements. Prioritize them (e.g., High, Medium, Low) and add notes for clarification.
Requirement
Importance
Notes
Allow customers to connect Jiminny to their AI tools (e.g. Claude, OpenAI)
HIGH
Provide MCP endpoint so customers can easily integrate Jiminny into their AI stack
Allow customers to access call data through AI tools
HIGH
Expose Jiminny data:
list calls (filter by date, user, account, deal)
get call
get transcript (speaker-separated)
get call metadata
search calls (keyword + semantic)
Support filtering by:
account / contact/ lead / deal
jiminny user
date range
Allow customers to search and query calls using AI tools
HIGH
Support keyword and semantic search across conversations
Provide structured insights so customers can generate better outputs
HIGH
For each call, expose:
Summary
Action items
Key points
Activity type
Notes
Call Score
CRM information
Allow customers to understand deal status across multiple calls/emails
HIGH
For each deal expose:
calls/meetings/emails
Identified risks
contacts related to the deal with their job title
linked account details
all CRM field information that we have in DI + fields used for CRM filling
example - get_deal_summary
request -
{
"tool": "get_deal_summary",
"arguments": {
"deal_name": "ACME"
}
}
responce:
{
"deal_name": "ACME",
"stage": "Negotiation",
"recent_activity": [
"Demo call on 2026-04-01",
"Pricing discussion on 2026-04-03"
],
"risks": [
"Pricing concerns",
"Security review pending"
], "next_steps": [
"Send follow-up to VP Sales",
"Share security documentation"
]
}
Ensure the AI can easily understand the schema of the data coming from Jiminny
HIGH
Models perform much better when tools have:
clear names
rich descriptions
predictable schemas
Provide clear, actionable error states for customers when MCP connections fail
HIGH
Error messages should guide agents toward solutions with specific suggestions and next steps.
Expired or revoked key — “Error: Authentication failed. The API key used to access Jiminny has been revoked or has expired. Please ask your Jiminny admin to generate a new API key in Settings > Organization > General and reconnect the MCP server.”
Rate limit hit — “Error: Rate limit exceeded. Too many requests have been made to the Jiminny MCP server in a short period. Please wait 60 seconds before retrying.”
Permissions mismatch — if a user tries to access data outside their team visibility settings - “Error: Access denied. The requested call (call_id: [X]) is outside your team's visibility settings in Jiminny. Only calls within your permitted scope are accessible.”
Trying to access private meeting - “Error: Access denied. This meeting has been marked as private by the host and cannot be accessed through the MCP connector. Try requesting a different call or ask the meeting host to change the visibility settings in Jiminny.”
Downgraded/Capture account — if a customer's plan drops below Scale tier or the Customer is on Capture in the first place - “Error: MCP access unavailable. The Jiminny MCP connector is available on the Scale plan and above. Your account does not currently have an active Scale subscription.”
Jiminny-side outage — “Error:Jiminny is temporarily unavailable (status 503). This is not a data or permissions issue — please retry in a few minutes.”
No data found - “Error:No calls found matching your criteria. Try adjusting your filters — for example, widening the date range, removing the account filter, or checking the rep name is spelled correctly in Jiminny.”
Allow customers to securely control who and what data is accessible externally
HIGH
Ensure MCP only exposes data user has access to - based on team visibility settings. This means that if a user is not allow to access calls/deals in Jiminny UI then they shouldn’t be able to access those through the MCP as well.
Private meetings shouldn’t be exposed via MCP
HIGH
When a meetings is set to Private then the information about it shouldn’t be exposed through the MCP.
Ensure Jiminny data can be combined with other sources (e.g. CRM, docs) in AI workflows
HIGH
Ensure data is structured to be easily combined with:
CRM (accounts, deals)
external docs
Use consistent identifiers:
account IDs
deal IDs
MCP is available only for Scale tier and above
HIGH
Customers who are on Capture tier should be able to access any of their data through MCP.
This should also cover the scenario when a customer has been on Scale but then downgrades to Capture - their MCP access should stop working.
Provide visibility into how external AI tools access Jiminny data
HIGH
Audit logs:
what data was accessed by which external system when
identity - who made the request
specific queries/filters used
failed access attempts (especially cross-visibility-boundary attempts)
Admins should be able to access the logs from the org settings.We can start with a csv export before building a specific page for it.
example from Atlassian -
Provide customers with example prompts to get started quickly
HIGH
MCP prompts are explicitly defined as prompt templates that clients can discover and call with arguments.
See examples in table below.
Expose Jiminny as a Connector in Claude
medium
Competitors like Fathom are listed as Connectors in Claude. This will make it easier for customers to find us and to connect Jiminny
Provide customers with example workflows to get started quickly
medium
A workflow is usually multiple steps, maybe multiple tools, still focused on one outcome.
See examples in table below.
Allow customers to use predefined Jiminny skills for common workflows
medium
Anthropic describes Skills as folders that include instructions, scripts, and resources that Claude can load when relevant, and as a way to teach Claude repeatable workflows, preferences, and domain expertise once instead of re-explaining them every time. Skills - a reusable package of behavior that can include prompts, instructions, resources, and sometimes scripts/tools for a broader job.
Claude skills - https://resources.anthropic.com/hubfs/The-Complete-Guide-to-Building-Skill-for-Claude.pdf?hsLang=en&utm_source=chatgpt.com
See examples in table below.
Jiminny UI widget for OpenAI
medium
The reason to have this is to make certain Jiminny use cases much easier than pure chat.
Instead of ChatGPT only replying with text like “Here are the last 5 ACME calls,” it could also show a visual Jiminny card or mini-app inside the chat. That widget could list calls, show a deal summary, let the user filter by rep/date/account, open a transcript section, or save a snippet—while the conversation continues in normal chat alongside it.
For Jiminny, the best widget use cases are the ones where users need to browse or compare rather than ask one-off questions. A strong example is deal review: the user asks ChatGPT, “What is the status of the ACME deal?” ChatGPT calls your Jiminny MCP tools, and the widget shows a compact deal view with recent calls, risks, next steps, stakeholders, and links to transcripts/snippets. The chat can still summarize the answer in words, but the widget gives a clearer, scannable interface.
Another good Jiminny widget use case is call search and exploration. A text answer can say “I found 12 calls mentioning pricing objections,” but a widget could show a sortable list with date, rep, account, score, and objection count, then let the user click into one call to see the exact excerpt or jump to a transcript section.
Allow customers to run long-running analyses asynchronously and retrieve progress/results
low
Some requests/questions require analysis of Hugh volumes of data. For those, it may be better to:
start the job
let it run in the background
return a status like “in progress”
let the client come back for the result later
For example - User asks in Claude:
“Analyse all calls from this quarter and tell me the top 5 objections by segment.”
That might require:
searching lots of calls
pulling many summaries/transcripts
aggregating results
Instead of making Claude wait 45+ seconds, Jiminny could:
create an analysis job
return: job_id = 123, status = running
We need this in order to support:
large-scale analysis
multi-call aggregation across lots of data
playlist generation across many calls
heavy recap/report generation
Creating a snippet through the MCP
low
Create a shareable snippet from a call recording by specifying a time range. Useful for highlighting key moments — objection handling, pricing discussions, competitive mentions — and sharing them with your team.
example request:
{
"tool": "create_snippet",
"arguments": {
"call_id": "call_123",
"start_time": "00:18:24",
"end_time": "00:19:10",
"title": "Pricing objection"
}
}
example response:
{
"snippet_id": "snip_987",
"title": "Pricing objection",
"share_url": "https://app.jiminny.com/snippets/snip_987"
}
Ability to add recordings or snippets to a playlist
low
Allow customers to create libraries of calls automatically. They can use those for onboarding or other purposes
Allow AI tools to read reusable Jiminny resources
low
fathom
Resources are useful for data that should be read consistently rather than recomputed every time. In Jiminny terms, that could be:
current deal snapshot
account summary
weekly rep recap
approved talk tracks / objection handling guidance
curated playlists or snippet libraries
This is useful because an AI can consume these directly as context, instead of repeatedly stitching together many tool calls.
Ability to write coaching notes in Jiminny through MCP
low
What we want to do for prompts/worflows and skills
Capability
Type
User value / job to be done
Example Jiminny use case
Inputs
Steps performed
Output
Draft follow-up email
Prompt
Help reps quickly create tailored follow-ups after calls
Use the latest customer call to draft an email with recap and next steps
Call ID
optional tone
optional recipient type
Retrieve call summary and action items from Jiminny.
Pull key points, commitments, and next steps.
Apply the chosen tone and structure.
Draft the email in a consistent format.
Customer-ready follow-up email draft
Summarise call
Prompt
Help users quickly extract the most important points from a conversation
Generate a concise summary of one call for internal or external use
Call ID
optional summary style
optional audience
Retrieve transcript, metadata, and structured insights.
Identify key topics, decisions, risks, and next steps.
Format output for the chosen audience.
Short or structured call summary with actions and risks
Generate deal recap
Prompt
Help reps and managers get a fast overview of a deal
Summarise the current state of a deal based on recent calls and linked CRM context
Deal ID or account name
optional date range
Retrieve calls and meetings linked to the deal.
Pull deal metadata and CRM-linked context.
Identify recent changes, blockers, risks, and next steps.
Summarise into a concise recap.
Deal recap with status, blockers, risks, and recommended next steps
Prepare weekly recap
Prompt
Help managers or reps review what changed over a time period
Weekly recap of calls, themes, and actions for one rep, team, or account
Rep ID
team ID or account ID
time period
Retrieve relevant calls and summaries for the selected time period.
Aggregate themes, action items, and changes.
Highlight notable risks, opportunities, and follow-ups.
Weekly recap with top themes, risks, opportunities, and actions
Prepare deal review
Workflow
Help reps and managers review deal status using multiple sources of context
Review a deal before pipeline review or forecast meeting
Deal ID
optional date range
Retrieve all recent calls, emails, and meetings tied to the deal.
Pull structured call summaries, score, action items, and key points.
Pull linked CRM context such as stage, contacts, and account details.
Aggregate open risks, unresolved objections, stakeholder gaps, and next steps.
Format into a review-ready structure.
Deal review document with current status, risks, stakeholders, blockers, and next steps
Weekly team recap
Workflow
Help managers monitor activity and risk across a group of reps or accounts
End-of-week team summary for sales leadership
Team ID
date range
Retrieve calls and structured insights across the team.
Group by rep, account, or deal.
Identify recurring themes, major risks, strong calls, and missed follow-ups.
Highlight calls or deals that need attention.
Team-level recap with patterns, key risks, notable wins, and action areas
Objection analysis across calls
Workflow
Help teams identify patterns across multiple conversations
Analyse pricing or competitor objections across recent calls
Account ID
deal ID
rep ID
keyword/topic
date range
Search calls matching the topic or keyword.
Retrieve summaries, transcripts, and snippets where relevant.
Identify recurring objections and how they were handled.
Assess whether objections were resolved or remain open.
Summarise patterns and examples.
Objection analysis with themes, frequency, examples, and suggested follow-up actions
Build onboarding playlist
Workflow
Help enablement teams curate useful learning content faster
Build a playlist of strong discovery, demo, or pricing calls for new hires
Topic
call type
rep/team filter
optional time period
Search for calls matching the selected criteria.
Rank or filter calls based on score, topics, or key moments.
Identify useful snippets or full recordings.
Add selected calls/snippets into a playlist structure.
Generate short descriptions for each item.
Curated onboarding playlist with selected calls/snippets and descriptions
Deal Inspection Skill
Skill
Give users a consistent, opinionated way to assess a deal
Claude reviews a deal using a repeatable Jiminny methodology
Deal ID or account name
optional review scope
Determine whether the request is suitable for a deal inspection.
Retrieve relevant calls, summaries, CRM context, stakeholders, and risks.
Apply a standard Jiminny review framework to assess deal health.
Look for missing next steps, unresolved objections, stakeholder gaps, and warning signs.
Present findings in a consistent structure with recommended actions.
Structured deal inspection with health assessment, red flags, and recommendations
Manager Coaching Skill
Skill
Help managers review calls consistently and identify coaching moments
Analyse a rep’s call and surface strengths, gaps, and examples for coaching
Call ID
optional rep ID
optional coaching focus
Retrieve transcript, score, summary, and key moments from the call.
Evaluate the conversation against a coaching framework.
Identify what went well and where the rep could improve.
Suggest moments to clip as snippets.
Recommend coaching actions or playlist additions.
Coaching review with strengths, gaps, snippet suggestions, and recommended coaching actions
CSM / QBR Prep Skill
Skill
Help CS or AM teams prepare structured customer reviews from conversations
Generate an account review or QBR-style summary from recent customer interactions
Account ID, optional time period
Retrieve all recent calls, emails, and account-linked context.
Aggregate themes, requests, blockers, sentiment shifts, and opportunities.
Apply a repeatable account review structure.
Summarise outcomes, open issues, and suggested next steps.
Structured QBR/account review summary with themes, risks, opportunities, and actions
Snippet Builder Skill
Skill
Help users consistently capture and label useful moments from calls
Identify useful moments in a call and convert them into reusable snippets
Call ID, optional focus area such as pricing, objection, competitor, discovery
Retrieve transcript, recording timeline, and call insights.
Detect moments matching the requested focus area.
Propose snippet start/end times and titles.
Tag snippets by type or theme.
Optionally save them or add them to a playlist.
One or more proposed or saved snippets with title, timing, and tags
💡 Technical details
Auth model needs specifying. Are API keys scoped per user, per team, or per Jiminny instance? If a key is generated by an admin, does it inherit their visibility level, or provide org-wide? Are permissions evaluated at query time or frozen at key creation? Needs to be query-time, otherwise permission changes won't propagate.
Key lifecycle management is missing. No mention of rotation, expiry, or revocation. A departed employee's active key is a data leak. Need: revocation, optional expiry, alerts on stale keys, and consider whether keys should be tied to service accounts rather than personal users.
Rate limiting should be HIGH. A compromised key or misconfigured automation could bulk-export an entire customer's call history. Need per-key rate limits and anomaly detection on unusual access patterns.
Open Questions
Track unresolved issues or decisions that need to be made. Update as answers become available.
Question
Answer
Date Answered
Competitor research
Competitor
MCP Availability
Core Capabilities
Advanced Capabilities
Positioning
Key Strength
Key Weakness
Gong
✅ Mature MCP
List/search calls
Get transcripts
get Call metadata
Deal intelligence
Scorecards, analytics
CRM context
Enterprise data layer
Deep data + ecosystem integrations
Limited opinionated AI workflows
Avoma
✅ Mature MCP
list_meetings
get_meeting
get_transcript
key topics
Deal fields/Deal level analysis
Coaching/Scoring
CRM context
pushing insights into Notion / Confluence
AI-ready meeting intelligence
Strongest “outputs” layer
Mostly pull-based interactions
Fathom
✅ MCP
list/search meetings
get transcript
get summary/action items
Team/org context
Webhooks (event-based triggers)
get_weekly_recap
aggregated action items across meetings
creating webhooks directly from the MCP server
Lightweight meeting data access
Includes summaries + actions
Limited analytics depth
Grain
✅ Basic MCP
get meetings
download transcripts
Notes
Deals
Scorecards
Data access utility
Simple + accessible
Low sophistication, sometimes browser-based
Outreach
⚠️ MCP (workflow-focused)
Search sequences
Emails
Meetings (Kaia)
account / prospect / opportunity lookups
Workflow automation
Multi-system orchestration
Revenue workflow engine
End-to-end GTM workflows
Less depth in conversation data
Attention
⚠️ Emerging MCP
Meeting data
Transcripts
CRM-linked context
AI insights
Sales assistant workflows
create snippets
AI sales assistant + CRM
Strong CRM linkage
Less focus on external knowledge layer
Planhat -
Related content
Ask Jiminny Anything on Call level
Galya Dimitrova
Hubspot app
Galya Dimitrova
Product Vision & Strategy
Galya Dimitrova
Automated CRM Filling
Simona Georgieva (Deactivated)
Competitive analysis
Galya Dimitrova
AI agent ideas
Steliyan Georgiev
Comments
James Graham
9 Apr
A few areas around Security & Compliance that need more depth before this moves beyond draft:
Auth model needs specifying. Are API keys scoped per user, per team, or per Jiminny instance? If a key is generated by an admin, does it inherit their visibility level, or provide org-wide? Are permissions evaluated at query time or frozen at key creation? Needs to be query-time, otherwise permission changes won't propagate.
Team visibility enforcement should be its own HIGH requirement. The current note under access control ("ensure MCP only exposes data user has access to") is doing too much work as a single line. Every MCP tool response (especially search_calls and deal-level aggregations) must be filtered through the same visibility engine as the UI. Semantic search is the riskiest here; it could surface results across team boundaries if not properly scoped.
No data minimisation or scoping controls. We're exposing transcripts, CRM fields, contact details with job titles, deal context - significant PII and commercial data leaving the platform. Can customers configure which data types are exposed? Can transcripts be PII-stripped before they leave Jiminny? Given we position GDPR consent as a differentiator, we should be thinking about this.
GDPR downstream processing is unaddressed. Piping transcripts to OpenAI/Gemini introduces new data processors. Customers need to acknowledge responsibility for downstream processing during setup. We should also consider whether call participants' recording consent covers onward sharing to third-party AI - it almost certainly doesn't by default. This is one for me to pick up.
Key lifecycle management is missing. No mention of rotation, expiry, or revocation. A departed employee's active key is a data leak. Need: revocation, optional expiry, alerts on stale keys, and consider whether keys should be tied to service accounts rather than personal users.
Rate limiting should be HIGH. A compromised key or misconfigured automation could bulk-export an entire customer's call history. Need per-key rate limits and anomaly detection on unusual ac...
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Platform Sprint 2 Q2 - Platform Team - Scrum Board Platform Sprint 2 Q2 - Platform Team - Scrum Board - Jira
SevenShores\Hubspot\Exceptions\BadRequest: Client error: `POST [URL_WITH_CREDENTIALS] Graham . I made the product related changes in the table and for the rest I left them as a note in the Technical section for the team to look at when they start looking at this. I wonder about your points related to GDPR. Currently multiple customers are using the Customer API/zapier to feed this data to AI and BI tools. They are also manually exporting transcripts and other information from the platform and feeding it to AI tools. I don’t get how MCP is so much different that all of these and why it will introduce new data processors (which are already being utilised) and would require any changes to the consent provided by participants.
You said
Jiminny MCP Connector
Epic
Link to Epik in Jira
Document status
DRAFT
Objective
Enable customers to connect Jiminny data to external AI tools (Claude, OpenAI, Gemini) so it can be used as part of their broader knowledge base and workflows.
Position Jiminny as a data layer for AI-driven revenue workflows, not just a standalone product.
👤 Target user
Revenue teams using AI tools (Sales, CS, RevOps)
Companies already experimenting with Claude / OpenAI
Mid-market & Enterprise customers with multiple data sources (CRM, docs, CI tools, Support tools etc)
🤕 Pain point or problem
Jiminny data is locked in the platform
AI tools lack access to high-value conversation context
Customers must manually export/copy transcripts
No easy way to combine calls with CRM + docs + other info - using the Jiminny API is not suitable for non technical sales people
Peer pressure as almost all competitors have this
💥 Impact and benefits
For customers
Better AI outputs using real customer conversations
Ability to build automated workflows across tools
For Jiminny
Increased product stickiness (embedded in workflows)
Competitive parity with Gong / Avoma etc.
💡 Solution ideas
Build an AI Knowledge Connector (MCP-based) that:
Exposes Jiminny data (calls, transcripts, metadata) to AI tools
Provides structured insights (summaries, action items, scoring etc.)
Supports deal-level context
Allows integration into customer-owned AI stacks (Claude + Zapier, etc.)
Success metrics
List the key goals and how you will measure success. Include both qualitative and quantitative metrics (e.g., user adoption, retention rate, revenue targets).
Goal
Metric
Increase stickiness by ensuring Jiminny is embedded in the customer’s workflows
% of customers connecting external AI tools
Number of MCP/API calls per customer - and which ones are being used the most
Decrease the manual copying of transcripts
decrease by X %
User interaction and design
Simple setup flow:
Generate API key / connect MCP
Clear instructions for Claude / Zapier setup
Provide:
Example prompts for Claude
Pre-built workflow templates for Zapier
Clear documentation - with use cases
👉 Focus: usable by non-technical users
Detailed Requirements
List the functional and non-functional requirements. Prioritize them (e.g., High, Medium, Low) and add notes for clarification.
Requirement
Importance
Notes
Allow customers to connect Jiminny to their AI tools (e.g. Claude, OpenAI)
HIGH
Provide MCP endpoint so customers can easily integrate Jiminny into their AI stack
Allow customers to access call data through AI tools
HIGH
Expose Jiminny data:
list calls (filter by date, user, account, deal)
get call
get transcript (speaker-separated)
get call metadata
search calls (keyword + semantic)
Support filtering by:
account / contact/ lead / deal
jiminny user
date range
Allow customers to search and query calls using AI tools
HIGH
Support keyword and semantic search across conversations
Provide structured insights so customers can generate better outputs
HIGH
For each call, expose:
Summary
Action items
Key points
Activity type
Notes
Call Score
CRM information
Allow customers to understand deal status across multiple calls/emails
HIGH
For each deal expose:
calls/meetings/emails
Identified risks
contacts related to the deal with their job title
linked account details
all CRM field information that we have in DI + fields used for CRM filling
example - get_deal_summary
request -
{
"tool": "get_deal_summary",
"arguments": {
"deal_name": "ACME"
}
}
responce:
{
"deal_name": "ACME",
"stage": "Negotiation",
"recent_activity": [
"Demo call on 2026-04-01",
"Pricing discussion on 2026-04-03"
],
"risks": [
"Pricing concerns",
"Security review pending"
], "next_steps": [
"Send follow-up to VP Sales",
"Share security documentation"
]
}
Ensure the AI can easily understand the schema of the data coming from Jiminny
HIGH
Models perform much better when tools have:
clear names
rich descriptions
predictable schemas
Provide clear, actionable error states for customers when MCP connections fail
HIGH
Error messages should guide agents toward solutions with specific suggestions and next steps.
Expired or revoked key — “Error: Authentication failed. The API key used to access Jiminny has been revoked or has expired. Please ask your Jiminny admin to generate a new API key in Settings > Organization > General and reconnect the MCP server.”
Rate limit hit — “Error: Rate limit exceeded. Too many requests have been made to the Jiminny MCP server in a short period. Please wait 60 seconds before retrying.”
Permissions mismatch — if a user tries to access data outside their team visibility settings - “Error: Access denied. The requested call (call_id: [X]) is outside your team's visibility settings in Jiminny. Only calls within your permitted scope are accessible.”
Trying to access private meeting - “Error: Access denied. This meeting has been marked as private by the host and cannot be accessed through the MCP connector. Try requesting a different call or ask the meeting host to change the visibility settings in Jiminny.”
Downgraded/Capture account — if a customer's plan drops below Scale tier or the Customer is on Capture in the first place - “Error: MCP access unavailable. The Jiminny MCP connector is available on the Scale plan and above. Your account does not currently have an active Scale subscription.”
Jiminny-side outage — “Error:Jiminny is temporarily unavailable (status 503). This is not a data or permissions issue — please retry in a few minutes.”
No data found - “Error:No calls found matching your criteria. Try adjusting your filters — for example, widening the date range, removing the account filter, or checking the rep name is spelled correctly in Jiminny.”
Allow customers to securely control who and what data is accessible externally
HIGH
Ensure MCP only exposes data user has access to - based on team visibility settings. This means that if a user is not allow to access calls/deals in Jiminny UI then they shouldn’t be able to access those through the MCP as well.
Private meetings shouldn’t be exposed via MCP
HIGH
When a meetings is set to Private then the information about it shouldn’t be exposed through the MCP.
Ensure Jiminny data can be combined with other sources (e.g. CRM, docs) in AI workflows
HIGH
Ensure data is structured to be easily combined with:
CRM (accounts, deals)
external docs
Use consistent identifiers:
account IDs
deal IDs
MCP is available only for Scale tier and above
HIGH
Customers who are on Capture tier should be able to access any of their data through MCP.
This should also cover the scenario when a customer has been on Scale but then downgrades to Capture - their MCP access should stop working.
Provide visibility into how external AI tools access Jiminny data
HIGH
Audit logs:
what data was accessed by which external system when
identity - who made the request
specific queries/filters used
failed access attempts (especially cross-visibility-boundary attempts)
Admins should be able to access the logs from the org settings.We can start with a csv export before building a specific page for it.
example from Atlassian -
Provide customers with example prompts to get started quickly
HIGH
MCP prompts are explicitly defined as prompt templates that clients can discover and call with arguments.
See examples in table below.
Expose Jiminny as a Connector in Claude
medium
Competitors like Fathom are listed as Connectors in Claude. This will make it easier for customers to find us and to connect Jiminny
Provide customers with example workflows to get started quickly
medium
A workflow is usually multiple steps, maybe multiple tools, still focused on one outcome.
See examples in table below.
Allow customers to use predefined Jiminny skills for common workflows
medium
Anthropic describes Skills as folders that include instructions, scripts, and resources that Claude can load when relevant, and as a way to teach Claude repeatable workflows, preferences, and domain expertise once instead of re-explaining them every time. Skills - a reusable package of behavior that can include prompts, instructions, resources, and sometimes scripts/tools for a broader job.
Claude skills - https://resources.anthropic.com/hubfs/The-Complete-Guide-to-Building-Skill-for-Claude.pdf?hsLang=en&utm_source=chatgpt.com
See examples in table below.
Jiminny UI widget for OpenAI
medium
The reason to have this is to make certain Jiminny use cases much easier than pure chat.
Instead of ChatGPT only replying with text like “Here are the last 5 ACME calls,” it could also show a visual Jiminny card or mini-app inside the chat. That widget could list calls, show a deal summary, let the user filter by rep/date/account, open a transcript section, or save a snippet—while the conversation continues in normal chat alongside it.
For Jiminny, the best widget use cases are the ones where users need to browse or compare rather than ask one-off questions. A strong example is deal review: the user asks ChatGPT, “What is the status of the ACME deal?” ChatGPT calls your Jiminny MCP tools, and the widget shows a compact deal view with recent calls, risks, next steps, stakeholders, and links to transcripts/snippets. The chat can still summarize the answer in words, but the widget gives a clearer, scannable interface.
Another good Jiminny widget use case is call search and exploration. A text answer can say “I found 12 calls mentioning pricing objections,” but a widget could show a sortable list with date, rep, account, score, and objection count, then let the user click into one call to see the exact excerpt or jump to a transcript section.
Allow customers to run long-running analyses asynchronously and retrieve progress/results
low
Some requests/questions require analysis of Hugh volumes of data. For those, it may be better to:
start the job
let it run in the background
return a status like “in progress”
let the client come back for the result later
For example - User asks in Claude:
“Analyse all calls from this quarter and tell me the top 5 objections by segment.”
That might require:
searching lots of calls
pulling many summaries/transcripts
aggregating results
Instead of making Claude wait 45+ seconds, Jiminny could:
create an analysis job
return: job_id = 123, status = running
We need this in order to support:
large-scale analysis
multi-call aggregation across lots of data
playlist generation across many calls
heavy recap/report generation
Creating a snippet through the MCP
low
Create a shareable snippet from a call recording by specifying a time range. Useful for highlighting key moments — objection handling, pricing discussions, competitive mentions — and sharing them with your team.
example request:
{
"tool": "create_snippet",
"arguments": {
"call_id": "call_123",
"start_time": "00:18:24",
"end_time": "00:19:10",
"title": "Pricing objection"
}
}
example response:
{
"snippet_id": "snip_987",
"title": "Pricing objection",
"share_url": "https://app.jiminny.com/snippets/snip_987"
}
Ability to add recordings or snippets to a playlist
low
Allow customers to create libraries of calls automatically. They can use those for onboarding or other purposes
Allow AI tools to read reusable Jiminny resources
low
fathom
Resources are useful for data that should be read consistently rather than recomputed every time. In Jiminny terms, that could be:
current deal snapshot
account summary
weekly rep recap
approved talk tracks / objection handling guidance
curated playlists or snippet libraries
This is useful because an AI can consume these directly as context, instead of repeatedly stitching together many tool calls.
Ability to write coaching notes in Jiminny through MCP
low
What we want to do for prompts/worflows and skills
Capability
Type
User value / job to be done
Example Jiminny use case
Inputs
Steps performed
Output
Draft follow-up email
Prompt
Help reps quickly create tailored follow-ups after calls
Use the latest customer call to draft an email with recap and next steps
Call ID
optional tone
optional recipient type
Retrieve call summary and action items from Jiminny.
Pull key points, commitments, and next steps.
Apply the chosen tone and structure.
Draft the email in a consistent format.
Customer-ready follow-up email draft
Summarise call
Prompt
Help users quickly extract the most important points from a conversation
Generate a concise summary of one call for internal or external use
Call ID
optional summary style
optional audience
Retrieve transcript, metadata, and structured insights.
Identify key topics, decisions, risks, and next steps.
Format output for the chosen audience.
Short or structured call summary with actions and risks
Generate deal recap
Prompt
Help reps and managers get a fast overview of a deal
Summarise the current state of a deal based on recent calls and linked CRM context
Deal ID or account name
optional date range
Retrieve calls and meetings linked to the deal.
Pull deal metadata and CRM-linked context.
Identify recent changes, blockers, risks, and next steps.
Summarise into a concise recap.
Deal recap with status, blockers, risks, and recommended next steps
Prepare weekly recap
Prompt
Help managers or reps review what changed over a time period
Weekly recap of calls, themes, and actions for one rep, team, or account
Rep ID
team ID or account ID
time period
Retrieve relevant calls and summaries for the selected time period.
Aggregate themes, action items, and changes.
Highlight notable risks, opportunities, and follow-ups.
Weekly recap with top themes, risks, opportunities, and actions
Prepare deal review
Workflow
Help reps and managers review deal status using multiple sources of context
Review a deal before pipeline review or forecast meeting
Deal ID
optional date range
Retrieve all recent calls, emails, and meetings tied to the deal.
Pull structured call summaries, score, action items, and key points.
Pull linked CRM context such as stage, contacts, and account details.
Aggregate open risks, unresolved objections, stakeholder gaps, and next steps.
Format into a review-ready structure.
Deal review document with current status, risks, stakeholders, blockers, and next steps
Weekly team recap
Workflow
Help managers monitor activity and risk across a group of reps or accounts
End-of-week team summary for sales leadership
Team ID
date range
Retrieve calls and structured insights across the team.
Group by rep, account, or deal.
Identify recurring themes, major risks, strong calls, and missed follow-ups.
Highlight calls or deals that need attention.
Team-level recap with patterns, key risks, notable wins, and action areas
Objection analysis across calls
Workflow
Help teams identify patterns across multiple conversations
Analyse pricing or competitor objections across recent calls
Account ID
deal ID
rep ID
keyword/topic
date range
Search calls matching the topic or keyword.
Retrieve summaries, transcripts, and snippets where relevant.
Identify recurring objections and how they were handled.
Assess whether objections were resolved or remain open.
Summarise patterns and examples.
Objection analysis with themes, frequency, examples, and suggested follow-up actions
Build onboarding playlist
Workflow
Help enablement teams curate useful learning content faster
Build a playlist of strong discovery, demo, or pricing calls for new hires
Topic
call type
rep/team filter
optional time period
Search for calls matching the selected criteria.
Rank or filter calls based on score, topics, or key moments.
Identify useful snippets or full recordings.
Add selected calls/snippets into a playlist structure.
Generate short descriptions for each item.
Curated onboarding playlist with selected calls/snippets and descriptions
Deal Inspection Skill
Skill
Give users a consistent, opinionated way to assess a deal
Claude reviews a deal using a repeatable Jiminny methodology
Deal ID or account name
optional review scope
Determine whether the request is suitable for a deal inspection.
Retrieve relevant calls, summaries, CRM context, stakeholders, and risks.
Apply a standard Jiminny review framework to assess deal health.
Look for missing next steps, unresolved objections, stakeholder gaps, and warning signs.
Present findings in a consistent structure with recommended actions.
Structured deal inspection with health assessment, red flags, and recommendations
Manager Coaching Skill
Skill
Help managers review calls consistently and identify coaching moments
Analyse a rep’s call and surface strengths, gaps, and examples for coaching
Call ID
optional rep ID
optional coaching focus
Retrieve transcript, score, summary, and key moments from the call.
Evaluate the conversation against a coaching framework.
Identify what went well and where the rep could improve.
Suggest moments to clip as snippets.
Recommend coaching actions or playlist additions.
Coaching review with strengths, gaps, snippet suggestions, and recommended coaching actions
CSM / QBR Prep Skill
Skill
Help CS or AM teams prepare structured customer reviews from conversations
Generate an account review or QBR-style summary from recent customer interactions
Account ID, optional time period
Retrieve all recent calls, emails, and account-linked context.
Aggregate themes, requests, blockers, sentiment shifts, and opportunities.
Apply a repeatable account review structure.
Summarise outcomes, open issues, and suggested next steps.
Structured QBR/account review summary with themes, risks, opportunities, and actions
Snippet Builder Skill
Skill
Help users consistently capture and label useful moments from calls
Identify useful moments in a call and convert them into reusable snippets
Call ID, optional focus area such as pricing, objection, competitor, discovery
Retrieve transcript, recording timeline, and call insights.
Detect moments matching the requested focus area.
Propose snippet start/end times and titles.
Tag snippets by type or theme.
Optionally save them or add them to a playlist.
One or more proposed or saved snippets with title, timing, and tags
💡 Technical details
Auth model needs specifying. Are API keys scoped per user, per team, or per Jiminny instance? If a key is generated by an admin, does it inherit their visibility level, or provide org-wide? Are permissions evaluated at query time or frozen at key creation? Needs to be query-time, otherwise permission changes won't propagate.
Key lifecycle management is missing. No mention of rotation, expiry, or revocation. A departed employee's active key is a data leak. Need: revocation, optional expiry, alerts on stale keys, and consider whether keys should be tied to service accounts rather than personal users.
Rate limiting should be HIGH. A compromised key or misconfigured automation could bulk-export an entire customer's call history. Need per-key rate limits and anomaly detection on unusual access patterns.
Open Questions
Track unresolved issues or decisions that need to be made. Update as answers become available.
Question
Answer
Date Answered
Competitor research
Competitor
MCP Availability
Core Capabilities
Advanced Capabilities
Positioning
Key Strength
Key Weakness
Gong
✅ Mature MCP
List/search calls
Get transcripts
get Call metadata
Deal intelligence
Scorecards, analytics
CRM context
Enterprise data layer
Deep data + ecosystem integrations
Limited opinionated AI workflows
Avoma
✅ Mature MCP
list_meetings
get_meeting
get_transcript
key topics
Deal fields/Deal level analysis
Coaching/Scoring
CRM context
pushing insights into Notion / Confluence
AI-ready meeting intelligence
Strongest “outputs” layer
Mostly pull-based interactions...
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Position Jiminny as a data layer for AI-driven revenue workflows, not just a standalone product. 👤 Target user Revenue teams using AI tools (Sales, CS, RevOps) Companies already experimenting with Claude / OpenAI Mid-market & Enterprise customers with multiple data sources (CRM, docs, CI tools, Support tools etc) 🤕 Pain point or problem Jiminny data is locked in the platform AI tools lack access to high-value conversation context Customers must manually export/copy transcripts No easy way to combine calls with CRM + docs + other info - using the Jiminny API is not suitable for non technical sales people Peer pressure as almost all competitors have this 💥 Impact and benefits For customers Better AI outputs using real customer conversations Ability to build automated workflows across tools For Jiminny Increased product stickiness (embedded in workflows) Competitive parity with Gong / Avoma etc. 💡 Solution ideas Build an AI Knowledge Connector (MCP-based) that: Exposes Jiminny data (calls, transcripts, metadata) to AI tools Provides structured insights (summaries, action items, scoring etc.) Supports deal-level context Allows integration into customer-owned AI stacks (Claude + Zapier, etc.) Success metrics List the key goals and how you will measure success. Include both qualitative and quantitative metrics (e.g., user adoption, retention rate, revenue targets). Goal Metric Increase stickiness by ensuring Jiminny is embedded in the customer’s workflows % of customers connecting external AI tools Number of MCP/API calls per customer - and which ones are being used the most Decrease the manual copying of transcripts decrease by X % User interaction and design Simple setup flow: Generate API key / connect MCP Clear instructions for Claude / Zapier setup Provide: Example prompts for Claude Pre-built workflow templates for Zapier Clear documentation - with use cases 👉 Focus: usable by non-technical users Detailed Requirements List the functional and non-functional requirements. Prioritize them (e.g., High, Medium, Low) and add notes for clarification. Requirement Importance Notes Allow customers to connect Jiminny to their AI tools (e.g. Claude, OpenAI) HIGH Provide MCP endpoint so customers can easily integrate Jiminny into their AI stack Allow customers to access call data through AI tools HIGH Expose Jiminny data: list calls (filter by date, user, account, deal) get call get transcript (speaker-separated) get call metadata search calls (keyword + semantic) Support filtering by: account / contact/ lead / deal jiminny user date range Allow customers to search and query calls using AI tools HIGH Support keyword and semantic search across conversations Provide structured insights so customers can generate better outputs HIGH For each call, expose: Summary Action items Key points Activity type Notes Call Score CRM information Allow customers to understand deal status across multiple calls/emails HIGH For each deal expose: calls/meetings/emails Identified risks contacts related to the deal with their job title linked account details all CRM field information that we have in DI + fields used for CRM filling example - get_deal_summary request - { \"tool\": \"get_deal_summary\", \"arguments\": { \"deal_name\": \"ACME\" } } responce: { \"deal_name\": \"ACME\", \"stage\": \"Negotiation\", \"recent_activity\": [ \"Demo call on 2026-04-01\", \"Pricing discussion on 2026-04-03\" ], \"risks\": [ \"Pricing concerns\", \"Security review pending\" ], \"next_steps\": [ \"Send follow-up to VP Sales\", \"Share security documentation\" ] } Ensure the AI can easily understand the schema of the data coming from Jiminny HIGH Models perform much better when tools have: clear names rich descriptions predictable schemas Provide clear, actionable error states for customers when MCP connections fail HIGH Error messages should guide agents toward solutions with specific suggestions and next steps. Expired or revoked key — “Error: Authentication failed. The API key used to access Jiminny has been revoked or has expired. Please ask your Jiminny admin to generate a new API key in Settings > Organization > General and reconnect the MCP server.” Rate limit hit — “Error: Rate limit exceeded. Too many requests have been made to the Jiminny MCP server in a short period. Please wait 60 seconds before retrying.” Permissions mismatch — if a user tries to access data outside their team visibility settings - “Error: Access denied. The requested call (call_id: [X]) is outside your team's visibility settings in Jiminny. Only calls within your permitted scope are accessible.” Trying to access private meeting - “Error: Access denied. This meeting has been marked as private by the host and cannot be accessed through the MCP connector. Try requesting a different call or ask the meeting host to change the visibility settings in Jiminny.” Downgraded/Capture account — if a customer's plan drops below Scale tier or the Customer is on Capture in the first place - “Error: MCP access unavailable. The Jiminny MCP connector is available on the Scale plan and above. Your account does not currently have an active Scale subscription.” Jiminny-side outage — “Error:Jiminny is temporarily unavailable (status 503). This is not a data or permissions issue — please retry in a few minutes.” No data found - “Error:No calls found matching your criteria. Try adjusting your filters — for example, widening the date range, removing the account filter, or checking the rep name is spelled correctly in Jiminny.” Allow customers to securely control who and what data is accessible externally HIGH Ensure MCP only exposes data user has access to - based on team visibility settings. This means that if a user is not allow to access calls/deals in Jiminny UI then they shouldn’t be able to access those through the MCP as well. Private meetings shouldn’t be exposed via MCP HIGH When a meetings is set to Private then the information about it shouldn’t be exposed through the MCP. Ensure Jiminny data can be combined with other sources (e.g. CRM, docs) in AI workflows HIGH Ensure data is structured to be easily combined with: CRM (accounts, deals) external docs Use consistent identifiers: account IDs deal IDs MCP is available only for Scale tier and above HIGH Customers who are on Capture tier should be able to access any of their data through MCP. This should also cover the scenario when a customer has been on Scale but then downgrades to Capture - their MCP access should stop working. Provide visibility into how external AI tools access Jiminny data HIGH Audit logs: what data was accessed by which external system when identity - who made the request specific queries/filters used failed access attempts (especially cross-visibility-boundary attempts) Admins should be able to access the logs from the org settings.We can start with a csv export before building a specific page for it. example from Atlassian - Provide customers with example prompts to get started quickly HIGH MCP prompts are explicitly defined as prompt templates that clients can discover and call with arguments. See examples in table below. Expose Jiminny as a Connector in Claude medium Competitors like Fathom are listed as Connectors in Claude. This will make it easier for customers to find us and to connect Jiminny Provide customers with example workflows to get started quickly medium A workflow is usually multiple steps, maybe multiple tools, still focused on one outcome. See examples in table below. Allow customers to use predefined Jiminny skills for common workflows medium Anthropic describes Skills as folders that include instructions, scripts, and resources that Claude can load when relevant, and as a way to teach Claude repeatable workflows, preferences, and domain expertise once instead of re-explaining them every time. Skills - a reusable package of behavior that can include prompts, instructions, resources, and sometimes scripts/tools for a broader job. Claude skills - https://resources.anthropic.com/hubfs/The-Complete-Guide-to-Building-Skill-for-Claude.pdf?hsLang=en&utm_source=chatgpt.com See examples in table below. Jiminny UI widget for OpenAI medium The reason to have this is to make certain Jiminny use cases much easier than pure chat. Instead of ChatGPT only replying with text like “Here are the last 5 ACME calls,” it could also show a visual Jiminny card or mini-app inside the chat. That widget could list calls, show a deal summary, let the user filter by rep/date/account, open a transcript section, or save a snippet—while the conversation continues in normal chat alongside it. For Jiminny, the best widget use cases are the ones where users need to browse or compare rather than ask one-off questions. A strong example is deal review: the user asks ChatGPT, “What is the status of the ACME deal?” ChatGPT calls your Jiminny MCP tools, and the widget shows a compact deal view with recent calls, risks, next steps, stakeholders, and links to transcripts/snippets. The chat can still summarize the answer in words, but the widget gives a clearer, scannable interface. Another good Jiminny widget use case is call search and exploration. A text answer can say “I found 12 calls mentioning pricing objections,” but a widget could show a sortable list with date, rep, account, score, and objection count, then let the user click into one call to see the exact excerpt or jump to a transcript section. Allow customers to run long-running analyses asynchronously and retrieve progress/results low Some requests/questions require analysis of Hugh volumes of data. For those, it may be better to: start the job let it run in the background return a status like “in progress” let the client come back for the result later For example - User asks in Claude: “Analyse all calls from this quarter and tell me the top 5 objections by segment.” That might require: searching lots of calls pulling many summaries/transcripts aggregating results Instead of making Claude wait 45+ seconds, Jiminny could: create an analysis job return: job_id = 123, status = running We need this in order to support: large-scale analysis multi-call aggregation across lots of data playlist generation across many calls heavy recap/report generation Creating a snippet through the MCP low Create a shareable snippet from a call recording by specifying a time range. Useful for highlighting key moments — objection handling, pricing discussions, competitive mentions — and sharing them with your team. example request: { \"tool\": \"create_snippet\", \"arguments\": { \"call_id\": \"call_123\", \"start_time\": \"00:18:24\", \"end_time\": \"00:19:10\", \"title\": \"Pricing objection\" } } example response: { \"snippet_id\": \"snip_987\", \"title\": \"Pricing objection\", \"share_url\": \"https://app.jiminny.com/snippets/snip_987\" } Ability to add recordings or snippets to a playlist low Allow customers to create libraries of calls automatically. They can use those for onboarding or other purposes Allow AI tools to read reusable Jiminny resources low fathom Resources are useful for data that should be read consistently rather than recomputed every time. In Jiminny terms, that could be: current deal snapshot account summary weekly rep recap approved talk tracks / objection handling guidance curated playlists or snippet libraries This is useful because an AI can consume these directly as context, instead of repeatedly stitching together many tool calls. Ability to write coaching notes in Jiminny through MCP low What we want to do for prompts/worflows and skills Capability Type User value / job to be done Example Jiminny use case Inputs Steps performed Output Draft follow-up email Prompt Help reps quickly create tailored follow-ups after calls Use the latest customer call to draft an email with recap and next steps Call ID optional tone optional recipient type Retrieve call summary and action items from Jiminny. Pull key points, commitments, and next steps. Apply the chosen tone and structure. Draft the email in a consistent format. Customer-ready follow-up email draft Summarise call Prompt Help users quickly extract the most important points from a conversation Generate a concise summary of one call for internal or external use Call ID optional summary style optional audience Retrieve transcript, metadata, and structured insights. Identify key topics, decisions, risks, and next steps. Format output for the chosen audience. Short or structured call summary with actions and risks Generate deal recap Prompt Help reps and managers get a fast overview of a deal Summarise the current state of a deal based on recent calls and linked CRM context Deal ID or account name optional date range Retrieve calls and meetings linked to the deal. Pull deal metadata and CRM-linked context. Identify recent changes, blockers, risks, and next steps. Summarise into a concise recap. Deal recap with status, blockers, risks, and recommended next steps Prepare weekly recap Prompt Help managers or reps review what changed over a time period Weekly recap of calls, themes, and actions for one rep, team, or account Rep ID team ID or account ID time period Retrieve relevant calls and summaries for the selected time period. Aggregate themes, action items, and changes. Highlight notable risks, opportunities, and follow-ups. Weekly recap with top themes, risks, opportunities, and actions Prepare deal review Workflow Help reps and managers review deal status using multiple sources of context Review a deal before pipeline review or forecast meeting Deal ID optional date range Retrieve all recent calls, emails, and meetings tied to the deal. Pull structured call summaries, score, action items, and key points. Pull linked CRM context such as stage, contacts, and account details. Aggregate open risks, unresolved objections, stakeholder gaps, and next steps. Format into a review-ready structure. Deal review document with current status, risks, stakeholders, blockers, and next steps Weekly team recap Workflow Help managers monitor activity and risk across a group of reps or accounts End-of-week team summary for sales leadership Team ID date range Retrieve calls and structured insights across the team. Group by rep, account, or deal. Identify recurring themes, major risks, strong calls, and missed follow-ups. Highlight calls or deals that need attention. Team-level recap with patterns, key risks, notable wins, and action areas Objection analysis across calls Workflow Help teams identify patterns across multiple conversations Analyse pricing or competitor objections across recent calls Account ID deal ID rep ID keyword/topic date range Search calls matching the topic or keyword. Retrieve summaries, transcripts, and snippets where relevant. Identify recurring objections and how they were handled. Assess whether objections were resolved or remain open. Summarise patterns and examples. Objection analysis with themes, frequency, examples, and suggested follow-up actions Build onboarding playlist Workflow Help enablement teams curate useful learning content faster Build a playlist of strong discovery, demo, or pricing calls for new hires Topic call type rep/team filter optional time period Search for calls matching the selected criteria. Rank or filter calls based on score, topics, or key moments. Identify useful snippets or full recordings. Add selected calls/snippets into a playlist structure. Generate short descriptions for each item. Curated onboarding playlist with selected calls/snippets and descriptions Deal Inspection Skill Skill Give users a consistent, opinionated way to assess a deal Claude reviews a deal using a repeatable Jiminny methodology Deal ID or account name optional review scope Determine whether the request is suitable for a deal inspection. Retrieve relevant calls, summaries, CRM context, stakeholders, and risks. Apply a standard Jiminny review framework to assess deal health. Look for missing next steps, unresolved objections, stakeholder gaps, and warning signs. Present findings in a consistent structure with recommended actions. Structured deal inspection with health assessment, red flags, and recommendations Manager Coaching Skill Skill Help managers review calls consistently and identify coaching moments Analyse a rep’s call and surface strengths, gaps, and examples for coaching Call ID optional rep ID optional coaching focus Retrieve transcript, score, summary, and key moments from the call. Evaluate the conversation against a coaching framework. Identify what went well and where the rep could improve. Suggest moments to clip as snippets. Recommend coaching actions or playlist additions. Coaching review with strengths, gaps, snippet suggestions, and recommended coaching actions CSM / QBR Prep Skill Skill Help CS or AM teams prepare structured customer reviews from conversations Generate an account review or QBR-style summary from recent customer interactions Account ID, optional time period Retrieve all recent calls, emails, and account-linked context. Aggregate themes, requests, blockers, sentiment shifts, and opportunities. Apply a repeatable account review structure. Summarise outcomes, open issues, and suggested next steps. Structured QBR/account review summary with themes, risks, opportunities, and actions Snippet Builder Skill Skill Help users consistently capture and label useful moments from calls Identify useful moments in a call and convert them into reusable snippets Call ID, optional focus area such as pricing, objection, competitor, discovery Retrieve transcript, recording timeline, and call insights. Detect moments matching the requested focus area. Propose snippet start/end times and titles. Tag snippets by type or theme. Optionally save them or add them to a playlist. One or more proposed or saved snippets with title, timing, and tags 💡 Technical details Auth model needs specifying. Are API keys scoped per user, per team, or per Jiminny instance? If a key is generated by an admin, does it inherit their visibility level, or provide org-wide? Are permissions evaluated at query time or frozen at key creation? Needs to be query-time, otherwise permission changes won't propagate. Key lifecycle management is missing. No mention of rotation, expiry, or revocation. A departed employee's active key is a data leak. Need: revocation, optional expiry, alerts on stale keys, and consider whether keys should be tied to service accounts rather than personal users. Rate limiting should be HIGH. A compromised key or misconfigured automation could bulk-export an entire customer's call history. Need per-key rate limits and anomaly detection on unusual access patterns. Open Questions Track unresolved issues or decisions that need to be made. Update as answers become available. Question Answer Date Answered Competitor research Competitor MCP Availability Core Capabilities Advanced Capabilities Positioning Key Strength Key Weakness Gong ✅ Mature MCP List/search calls Get transcripts get Call metadata Deal intelligence Scorecards, analytics CRM context Enterprise data layer Deep data + ecosystem integrations Limited opinionated AI workflows Avoma ✅ Mature MCP list_meetings get_meeting get_transcript key topics Deal fields/Deal level analysis Coaching/Scoring CRM context pushing insights into Notion / Confluence AI-ready meeting intelligence Strongest “outputs” layer Mostly pull-based interactions Fathom ✅ MCP list/search meetings get transcript get summary/action items Team/org context Webhooks (event-based triggers) get_weekly_recap aggregated action items across meetings creating webhooks directly from the MCP server Lightweight meeting data access Includes summaries + actions Limited analytics depth Grain ✅ Basic MCP get meetings download transcripts Notes Deals Scorecards Data access utility Simple + accessible Low sophistication, sometimes browser-based Outreach ⚠️ MCP (workflow-focused) Search sequences Emails Meetings (Kaia) account / prospect / opportunity lookups Workflow automation Multi-system orchestration Revenue workflow engine End-to-end GTM workflows Less depth in conversation data Attention ⚠️ Emerging MCP Meeting data Transcripts CRM-linked context AI insights Sales assistant workflows create snippets AI sales assistant + CRM Strong CRM linkage Less focus on external knowledge layer Planhat - Related content Ask Jiminny Anything on Call level Galya Dimitrova Hubspot app Galya Dimitrova Product Vision & Strategy Galya Dimitrova Automated CRM Filling Simona Georgieva (Deactivated) Competitive analysis Galya Dimitrova AI agent ideas Steliyan Georgiev Comments James Graham 9 Apr A few areas around Security & Compliance that need more depth before this moves beyond draft: Auth model needs specifying. Are API keys scoped per user, per team, or per Jiminny instance? If a key is generated by an admin, does it inherit their visibility level, or provide org-wide? Are permissions evaluated at query time or frozen at key creation? Needs to be query-time, otherwise permission changes won't propagate. Team visibility enforcement should be its own HIGH requirement. The current note under access control (\"ensure MCP only exposes data user has access to\") is doing too much work as a single line. Every MCP tool response (especially search_calls and deal-level aggregations) must be filtered through the same visibility engine as the UI. Semantic search is the riskiest here; it could surface results across team boundaries if not properly scoped. No data minimisation or scoping controls. We're exposing transcripts, CRM fields, contact details with job titles, deal context - significant PII and commercial data leaving the platform. Can customers configure which data types are exposed? Can transcripts be PII-stripped before they leave Jiminny? Given we position GDPR consent as a differentiator, we should be thinking about this. GDPR downstream processing is unaddressed. Piping transcripts to OpenAI/Gemini introduces new data processors. Customers need to acknowledge responsibility for downstream processing during setup. We should also consider whether call participants' recording consent covers onward sharing to third-party AI - it almost certainly doesn't by default. This is one for me to pick up. Key lifecycle management is missing. No mention of rotation, expiry, or revocation. A departed employee's active key is a data leak. Need: revocation, optional expiry, alerts on stale keys, and consider whether keys should be tied to service accounts rather than personal users. Rate limiting should be HIGH. A compromised key or misconfigured automation could bulk-export an entire customer's call history. Need per-key rate limits and anomaly detection on unusual access patterns. Audit logs should go deeper. Current spec (what data, which system, when) is a start. Add: identity behind the key, specific queries/filters used, and failed access attempts (especially cross-visibility-boundary attempts). Enterprise compliance teams will expect this. Downgrade handling. Doc says Scale tier and above, but doesn't say what happens on downgrade. Keys should auto-deactivate. Happy to help draft a dedicated Security & Compliance section if useful. Galya Dimitrova 15 Apr Thanks for the input @James Graham . I made the product related changes in the table and for the rest I left them as a note in the Technical section for the team to look at when they start looking at this. I wonder about your points related to GDPR. Currently multiple customers are using the Customer API/zapier to feed this data to AI and BI tools. They are also manually exporting transcripts and other information from the platform and feeding it to AI tools. 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each deal expose:","depth":23,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"calls/meetings/emails","depth":23,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"Identified risks","depth":23,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"contacts related to the deal with their job title","depth":23,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"linked account details","depth":23,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"all CRM field information that we have in DI + fields used for CRM filling","depth":23,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"example - get_deal_summary","depth":23,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"request 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The API key used to access Jiminny has been revoked or has expired. Please ask your Jiminny admin to generate a new API key in Settings > Organization > General and reconnect the MCP server.”","depth":23,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"Rate limit hit — “Error: Rate limit exceeded. Too many requests have been made to the Jiminny MCP server in a short period. Please wait 60 seconds before retrying.”","depth":23,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"Permissions mismatch — if a user tries to access data outside their team visibility settings - “Error: Access denied. The requested call (call_id: [X]) is outside your team's visibility settings in Jiminny. Only calls within your permitted scope are accessible.”","depth":23,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"Trying to access private meeting - “Error: Access denied. 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This is not a data or permissions issue — please retry in a few minutes.”","depth":23,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"No data found - “Error:No calls found matching your criteria. Try adjusting your filters — for example, widening the date range, removing the account filter, or checking the rep name is spelled correctly in Jiminny.”","depth":23,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"Allow customers to securely control who and what data is accessible externally","depth":23,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"HIGH","depth":23,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"Ensure MCP only exposes data user has access to - based on team visibility settings. 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This will make it easier for customers to find us and to connect Jiminny","depth":23,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"Provide customers with example workflows to get started quickly","depth":23,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"medium","depth":23,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"A workflow is usually multiple steps, maybe multiple tools, still focused on one outcome.","depth":23,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"See examples in table below.","depth":23,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"Allow customers to use predefined Jiminny skills for common workflows","depth":23,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"medium","depth":23,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"Anthropic describes Skills as folders that include instructions, scripts, and resources that Claude can load when relevant, and as a way to teach Claude repeatable workflows, preferences, and domain expertise once instead of re-explaining them every time. Skills - a reusable package of behavior that can include prompts, instructions, resources, and sometimes scripts/tools for a broader job.","depth":23,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"Claude skills - https://resources.anthropic.com/hubfs/The-Complete-Guide-to-Building-Skill-for-Claude.pdf?hsLang=en&utm_source=chatgpt.com","depth":23,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"See examples in table below.","depth":23,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"Jiminny UI widget for OpenAI","depth":23,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"medium","depth":23,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"The reason to have this is to make certain Jiminny use cases much easier than pure chat.","depth":23,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"Instead of ChatGPT only replying with text like “Here are the last 5 ACME calls,” it could also show a visual Jiminny card or mini-app inside the chat. That widget could list calls, show a deal summary, let the user filter by rep/date/account, open a transcript section, or save a snippet—while the conversation continues in normal chat alongside it.","depth":23,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"For Jiminny, the best widget use cases are the ones where users need to browse or compare rather than ask one-off questions. A strong example is deal review: the user asks ChatGPT, “What is the status of the ACME deal?” ChatGPT calls your Jiminny MCP tools, and the widget shows a compact deal view with recent calls, risks, next steps, stakeholders, and links to transcripts/snippets. The chat can still summarize the answer in words, but the widget gives a clearer, scannable interface.","depth":23,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"Another good Jiminny widget use case is call search and exploration. A text answer can say “I found 12 calls mentioning pricing objections,” but a widget could show a sortable list with date, rep, account, score, and objection count, then let the user click into one call to see the exact excerpt or jump to a transcript section.","depth":23,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"Allow customers to run long-running analyses asynchronously and retrieve progress/results","depth":23,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"low","depth":23,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"Some requests/questions require analysis of Hugh volumes of data. 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Useful for highlighting key moments — objection handling, pricing discussions, competitive mentions — and sharing them with your team.","depth":23,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"example request:","depth":23,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"{","depth":23,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"\"tool\": \"create_snippet\",","depth":23,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"\"arguments\": {","depth":23,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"\"call_id\": \"call_123\",","depth":23,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"\"start_time\": \"00:18:24\",","depth":23,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"\"end_time\": \"00:19:10\",","depth":23,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"\"title\": \"Pricing objection\"","depth":23,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"}","depth":23,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"}","depth":23,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"example response:","depth":23,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"{","depth":23,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"\"snippet_id\": \"snip_987\",","depth":23,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"\"title\": \"Pricing objection\",","depth":23,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"\"share_url\": \"https://app.jiminny.com/snippets/snip_987\"","depth":23,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"}","depth":23,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"Ability to add recordings or snippets to a playlist","depth":23,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"low","depth":23,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"Allow customers to create libraries of calls automatically. They can use those for onboarding or other purposes","depth":23,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"Allow AI tools to read reusable Jiminny resources","depth":23,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"low","depth":23,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"fathom","depth":23,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"Resources are useful for data that should be read consistently rather than recomputed every time. 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calls.","depth":23,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"Ability to write coaching notes in Jiminny through MCP","depth":23,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"low","depth":23,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"What we want to do for prompts/worflows and skills","depth":23,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"Capability","depth":23,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"Type","depth":23,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"User value / job to be done","depth":23,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"Example Jiminny use 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opportunities.","depth":23,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"Apply a repeatable account review structure.","depth":23,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"Summarise outcomes, open issues, and suggested next steps.","depth":23,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"Structured QBR/account review summary with themes, risks, opportunities, and actions","depth":23,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"Snippet Builder Skill","depth":23,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"Skill","depth":23,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"Help users consistently capture and label useful moments from calls","depth":23,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"Identify useful moments in a call and convert them into reusable snippets","depth":23,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"Call ID, optional focus area such as pricing, objection, competitor, discovery","depth":23,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"Retrieve transcript, recording timeline, and call insights.","depth":23,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"Detect moments matching the requested focus area.","depth":23,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"Propose snippet start/end times and titles.","depth":23,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"Tag snippets by type or theme.","depth":23,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"Optionally save them or add them to a playlist.","depth":23,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"One or more proposed or saved snippets with title, timing, and tags","depth":23,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"💡 Technical details","depth":23,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"Auth model needs specifying. Are API keys scoped per user, per team, or per Jiminny instance? If a key is generated by an admin, does it inherit their visibility level, or provide org-wide? Are permissions evaluated at query time or frozen at key creation? Needs to be query-time, otherwise permission changes won't propagate.","depth":23,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"Key lifecycle management is missing. No mention of rotation, expiry, or revocation. A departed employee's active key is a data leak. Need: revocation, optional expiry, alerts on stale keys, and consider whether keys should be tied to service accounts rather than personal users.","depth":23,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"Rate limiting should be HIGH. A compromised key or misconfigured automation could bulk-export an entire customer's call history. Need per-key rate limits and anomaly detection on unusual access patterns.","depth":23,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"Open Questions","depth":23,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"Track unresolved issues or decisions that need to be made. Update as answers become available.","depth":23,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"Question","depth":23,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"Answer","depth":23,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"Date Answered","depth":23,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"Competitor research","depth":23,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"Competitor","depth":23,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"MCP Availability","depth":23,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"Core Capabilities","depth":23,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"Advanced Capabilities","depth":23,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"Positioning","depth":23,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"Key Strength","depth":23,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"Key Weakness","depth":23,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"Gong","depth":23,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"✅ Mature MCP","depth":23,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"List/search calls","depth":23,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"Get transcripts","depth":23,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"get Call metadata","depth":23,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"Deal intelligence","depth":23,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"Scorecards, analytics","depth":23,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"CRM context","depth":23,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"Enterprise data layer","depth":23,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"Deep data + ecosystem integrations","depth":23,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"Limited opinionated AI workflows","depth":23,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"Avoma","depth":23,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"✅ Mature MCP","depth":23,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"list_meetings","depth":23,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"get_meeting","depth":23,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"get_transcript","depth":23,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"key topics","depth":23,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"Deal fields/Deal level analysis","depth":23,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"Coaching/Scoring","depth":23,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"CRM context","depth":23,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"pushing insights into Notion / Confluence","depth":23,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"AI-ready meeting intelligence","depth":23,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"Strongest “outputs” layer","depth":23,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"Mostly pull-based interactions","depth":23,"help_text":"","role_description":"text","subrole":"AXUnknown"}]...
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Platform Sprint 2 Q2 - Platform Team - Scrum Board Platform Sprint 2 Q2 - Platform Team - Scrum Board - Jira
SevenShores\Hubspot\Exceptions\BadRequest: Client error: `POST [URL_WITH_CREDENTIALS] Graham . I made the product related changes in the table and for the rest I left them as a note in the Technical section for the team to look at when they start looking at this. I wonder about your points related to GDPR. Currently multiple customers are using the Customer API/zapier to feed this data to AI and BI tools. They are also manually exporting transcripts and other information from the platform and feeding it to AI tools. I don’t get how MCP is so much different that all of these and why it will introduce new data processors (which are already being utilised) and would require any changes to the consent provided by participants.
You said
Jiminny MCP Connector
Epic
Link to Epik in Jira
Document status
DRAFT
Objective
Enable customers to connect Jiminny data to external AI tools (Claude, OpenAI, Gemini) so it can be used as part of their broader knowledge base and workflows.
Position Jiminny as a data layer for AI-driven revenue workflows, not just a standalone product.
👤 Target user
Revenue teams using AI tools (Sales, CS, RevOps)
Companies already experimenting with Claude / OpenAI
Mid-market & Enterprise customers with multiple data sources (CRM, docs, CI tools, Support tools etc)
🤕 Pain point or problem
Jiminny data is locked in the platform
AI tools lack access to high-value conversation context
Customers must manually export/copy transcripts
No easy way to combine calls with CRM + docs + other info - using the Jiminny API is not suitable for non technical sales people
Peer pressure as almost all competitors have this
💥 Impact and benefits
For customers
Better AI outputs using real customer conversations
Ability to build automated workflows across tools
For Jiminny
Increased product stickiness (embedded in workflows)
Competitive parity with Gong / Avoma etc.
💡 Solution ideas
Build an AI Knowledge Connector (MCP-based) that:
Exposes Jiminny data (calls, transcripts, metadata) to AI tools
Provides structured insights (summaries, action items, scoring etc.)
Supports deal-level context
Allows integration into customer-owned AI stacks (Claude + Zapier, etc.)
Success metrics
List the key goals and how you will measure success. Include both qualitative and quantitative metrics (e.g., user adoption, retention rate, revenue targets).
Goal
Metric
Increase stickiness by ensuring Jiminny is embedded in the customer’s workflows
% of customers connecting external AI tools
Number of MCP/API calls per customer - and which ones are being used the most
Decrease the manual copying of transcripts
decrease by X %
User interaction and design
Simple setup flow:
Generate API key / connect MCP
Clear instructions for Claude / Zapier setup
Provide:
Example prompts for Claude
Pre-built workflow templates for Zapier
Clear documentation - with use cases
👉 Focus: usable by non-technical users
Detailed Requirements
List the functional and non-functional requirements. Prioritize them (e.g., High, Medium, Low) and add notes for clarification.
Requirement
Importance
Notes
Allow customers to connect Jiminny to their AI tools (e.g. Claude, OpenAI)
HIGH
Provide MCP endpoint so customers can easily integrate Jiminny into their AI stack
Allow customers to access call data through AI tools
HIGH
Expose Jiminny data:
list calls (filter by date, user, account, deal)
get call
get transcript (speaker-separated)
get call metadata
search calls (keyword + semantic)
Support filtering by:
account / contact/ lead / deal
jiminny user
date range
Allow customers to search and query calls using AI tools
HIGH
Support keyword and semantic search across conversations
Provide structured insights so customers can generate better outputs
HIGH
For each call, expose:
Summary
Action items
Key points
Activity type
Notes
Call Score
CRM information
Allow customers to understand deal status across multiple calls/emails
HIGH
For each deal expose:
calls/meetings/emails
Identified risks
contacts related to the deal with their job title
linked account details
all CRM field information that we have in DI + fields used for CRM filling
example - get_deal_summary
request -
{
"tool": "get_deal_summary",
"arguments": {
"deal_name": "ACME"
}
}
responce:
{
"deal_name": "ACME",
"stage": "Negotiation",
"recent_activity": [
"Demo call on 2026-04-01",
"Pricing discussion on 2026-04-03"
],
"risks": [
"Pricing concerns",
"Security review pending"
], "next_steps": [
"Send follow-up to VP Sales",
"Share security documentation"
]
}
Ensure the AI can easily understand the schema of the data coming from Jiminny
HIGH
Models perform much better when tools have:
clear names
rich descriptions
predictable schemas
Provide clear, actionable error states for customers when MCP connections fail
HIGH
Error messages should guide agents toward solutions with specific suggestions and next steps.
Expired or revoked key — “Error: Authentication failed. The API key used to access Jiminny has been revoked or has expired. Please ask your Jiminny admin to generate a new API key in Settings > Organization > General and reconnect the MCP server.”
Rate limit hit — “Error: Rate limit exceeded. Too many requests have been made to the Jiminny MCP server in a short period. Please wait 60 seconds before retrying.”
Permissions mismatch — if a user tries to access data outside their team visibility settings - “Error: Access denied. The requested call (call_id: [X]) is outside your team's visibility settings in Jiminny. Only calls within your permitted scope are accessible.”
Trying to access private meeting - “Error: Access denied. This meeting has been marked as private by the host and cannot be accessed through the MCP connector. Try requesting a different call or ask the meeting host to change the visibility settings in Jiminny.”
Downgraded/Capture account — if a customer's plan drops below Scale tier or the Customer is on Capture in the first place - “Error: MCP access unavailable. The Jiminny MCP connector is available on the Scale plan and above. Your account does not currently have an active Scale subscription.”
Jiminny-side outage — “Error:Jiminny is temporarily unavailable (status 503). This is not a data or permissions issue — please retry in a few minutes.”
No data found - “Error:No calls found matching your criteria. Try adjusting your filters — for example, widening the date range, removing the account filter, or checking the rep name is spelled correctly in Jiminny.”
Allow customers to securely control who and what data is accessible externally
HIGH
Ensure MCP only exposes data user has access to - based on team visibility settings. This means that if a user is not allow to access calls/deals in Jiminny UI then they shouldn’t be able to access those through the MCP as well.
Private meetings shouldn’t be exposed via MCP
HIGH
When a meetings is set to Private then the information about it shouldn’t be exposed through the MCP.
Ensure Jiminny data can be combined with other sources (e.g. CRM, docs) in AI workflows
HIGH
Ensure data is structured to be easily combined with:
CRM (accounts, deals)
external docs
Use consistent identifiers:
account IDs
deal IDs
MCP is available only for Scale tier and above
HIGH
Customers who are on Capture tier should be able to access any of their data through MCP.
This should also cover the scenario when a customer has been on Scale but then downgrades to Capture - their MCP access should stop working.
Provide visibility into how external AI tools access Jiminny data
HIGH
Audit logs:
what data was accessed by which external system when
identity - who made the request
specific queries/filters used
failed access attempts (especially cross-visibility-boundary attempts)
Admins should be able to access the logs from the org settings.We can start with a csv export before building a specific page for it.
example from Atlassian -
Provide customers with example prompts to get started quickly
HIGH
MCP prompts are explicitly defined as prompt templates that clients can discover and call with arguments.
See examples in table below.
Expose Jiminny as a Connector in Claude
medium
Competitors like Fathom are listed as Connectors in Claude. This will make it easier for customers to find us and to connect Jiminny
Provide customers with example workflows to get started quickly
medium
A workflow is usually multiple steps, maybe multiple tools, still focused on one outcome.
See examples in table below.
Allow customers to use predefined Jiminny skills for common workflows
medium
Anthropic describes Skills as folders that include instructions, scripts, and resources that Claude can load when relevant, and as a way to teach Claude repeatable workflows, preferences, and domain expertise once instead of re-explaining them every time. Skills - a reusable package of behavior that can include prompts, instructions, resources, and sometimes scripts/tools for a broader job.
Claude skills - https://resources.anthropic.com/hubfs/The-Complete-Guide-to-Building-Skill-for-Claude.pdf?hsLang=en&utm_source=chatgpt.com
See examples in table below.
Jiminny UI widget for OpenAI
medium
The reason to have this is to make certain Jiminny use cases much easier than pure chat.
Instead of ChatGPT only replying with text like “Here are the last 5 ACME calls,” it could also show a visual Jiminny card or mini-app inside the chat. That widget could list calls, show a deal summary, let the user filter by rep/date/account, open a transcript section, or save a snippet—while the conversation continues in normal chat alongside it.
For Jiminny, the best widget use cases are the ones where users need to browse or compare rather than ask one-off questions. A strong example is deal review: the user asks ChatGPT, “What is the status of the ACME deal?” ChatGPT calls your Jiminny MCP tools, and the widget shows a compact deal view with recent calls, risks, next steps, stakeholders, and links to transcripts/snippets. The chat can still summarize the answer in words, but the widget gives a clearer, scannable interface.
Another good Jiminny widget use case is call search and exploration. A text answer can say “I found 12 calls mentioning pricing objections,” but a widget could show a sortable list with date, rep, account, score, and objection count, then let the user click into one call to see the exact excerpt or jump to a transcript section.
Allow customers to run long-running analyses asynchronously and retrieve progress/results
low
Some requests/questions require analysis of Hugh volumes of data. For those, it may be better to:
start the job
let it run in the background
return a status like “in progress”
let the client come back for the result later
For example - User asks in Claude:
“Analyse all calls from this quarter and tell me the top 5 objections by segment.”
That might require:
searching lots of calls
pulling many summaries/transcripts
aggregating results
Instead of making Claude wait 45+ seconds, Jiminny could:
create an analysis job
return: job_id = 123, status = running
We need this in order to support:
large-scale analysis
multi-call aggregation across lots of data
playlist generation across many calls
heavy recap/report generation
Creating a snippet through the MCP
low
Create a shareable snippet from a call recording by specifying a time range. Useful for highlighting key moments — objection handling, pricing discussions, competitive mentions — and sharing them with your team.
example request:
{
"tool": "create_snippet",
"arguments": {
"call_id": "call_123",
"start_time": "00:18:24",
"end_time": "00:19:10",
"title": "Pricing objection"
}
}
example response:
{
"snippet_id": "snip_987",
"title": "Pricing objection",
"share_url": "https://app.jiminny.com/snippets/snip_987"
}
Ability to add recordings or snippets to a playlist
low
Allow customers to create libraries of calls automatically. They can use those for onboarding or other purposes
Allow AI tools to read reusable Jiminny resources
low
fathom
Resources are useful for data that should be read consistently rather than recomputed every time. In Jiminny terms, that could be:
current deal snapshot
account summary
weekly rep recap
approved talk tracks / objection handling guidance
curated playlists or snippet libraries
This is useful because an AI can consume these directly as context, instead of repeatedly stitching together many tool calls.
Ability to write coaching notes in Jiminny through MCP
low
What we want to do for prompts/worflows and skills
Capability
Type
User value / job to be done
Example Jiminny use case
Inputs
Steps performed
Output
Draft follow-up email
Prompt
Help reps quickly create tailored follow-ups after calls
Use the latest customer call to draft an email with recap and next steps
Call ID
optional tone
optional recipient type
Retrieve call summary and action items from Jiminny.
Pull key points, commitments, and next steps.
Apply the chosen tone and structure.
Draft the email in a consistent format.
Customer-ready follow-up email draft
Summarise call
Prompt
Help users quickly extract the most important points from a conversation
Generate a concise summary of one call for internal or external use
Call ID
optional summary style
optional audience
Retrieve transcript, metadata, and structured insights.
Identify key topics, decisions, risks, and next steps.
Format output for the chosen audience.
Short or structured call summary with actions and risks
Generate deal recap
Prompt
Help reps and managers get a fast overview of a deal
Summarise the current state of a deal based on recent calls and linked CRM context
Deal ID or account name
optional date range
Retrieve calls and meetings linked to the deal.
Pull deal metadata and CRM-linked context.
Identify recent changes, blockers, risks, and next steps.
Summarise into a concise recap.
Deal recap with status, blockers, risks, and recommended next steps
Prepare weekly recap
Prompt
Help managers or reps review what changed over a time period
Weekly recap of calls, themes, and actions for one rep, team, or account
Rep ID
team ID or account ID
time period
Retrieve relevant calls and summaries for the selected time period.
Aggregate themes, action items, and changes.
Highlight notable risks, opportunities, and follow-ups.
Weekly recap with top themes, risks, opportunities, and actions
Prepare deal review
Workflow
Help reps and managers review deal status using multiple sources of context
Review a deal before pipeline review or forecast meeting
Deal ID
optional date range
Retrieve all recent calls, emails, and meetings tied to the deal.
Pull structured call summaries, score, action items, and key points.
Pull linked CRM context such as stage, contacts, and account details.
Aggregate open risks, unresolved objections, stakeholder gaps, and next steps.
Format into a review-ready structure.
Deal review document with current status, risks, stakeholders, blockers, and next steps
Weekly team recap
Workflow
Help managers monitor activity and risk across a group of reps or accounts
End-of-week team summary for sales leadership
Team ID
date range
Retrieve calls and structured insights across the team.
Group by rep, account, or deal.
Identify recurring themes, major risks, strong calls, and missed follow-ups.
Highlight calls or deals that need attention.
Team-level recap with patterns, key risks, notable wins, and action areas
Objection analysis across calls
Workflow
Help teams identify patterns across multiple conversations
Analyse pricing or competitor objections across recent calls
Account ID
deal ID
rep ID
keyword/topic
date range
Search calls matching the topic or keyword.
Retrieve summaries, transcripts, and snippets where relevant.
Identify recurring objections and how they were handled.
Assess whether objections were resolved or remain open.
Summarise patterns and examples.
Objection analysis with themes, frequency, examples, and suggested follow-up actions
Build onboarding playlist
Workflow
Help enablement teams curate useful learning content faster
Build a playlist of strong discovery, demo, or pricing calls for new hires
Topic
call type
rep/team filter
optional time period
Search for calls matching the selected criteria.
Rank or filter calls based on score, topics, or key moments.
Identify useful snippets or full recordings.
Add selected calls/snippets into a playlist structure.
Generate short descriptions for each item.
Curated onboarding playlist with selected calls/snippets and descriptions
Deal Inspection Skill
Skill
Give users a consistent, opinionated way to assess a deal
Claude reviews a deal using a repeatable Jiminny methodology
Deal ID or account name
optional review scope
Determine whether the request is suitable for a deal inspection.
Retrieve relevant calls, summaries, CRM context, stakeholders, and risks.
Apply a standard Jiminny review framework to assess deal health.
Look for missing next steps, unresolved objections, stakeholder gaps, and warning signs.
Present findings in a consistent structure with recommended actions.
Structured deal inspection with health assessment, red flags, and recommendations
Manager Coaching Skill
Skill
Help managers review calls consistently and identify coaching moments
Analyse a rep’s call and surface strengths, gaps, and examples for coaching
Call ID
optional rep ID
optional coaching focus
Retrieve transcript, score, summary, and key moments from the call.
Evaluate the conversation against a coaching framework.
Identify what went well and where the rep could improve.
Suggest moments to clip as snippets.
Recommend coaching actions or playlist additions.
Coaching review with strengths, gaps, snippet suggestions, and recommended coaching actions
CSM / QBR Prep Skill
Skill
Help CS or AM teams prepare structured customer reviews from conversations
Generate an account review or QBR-style summary from recent customer interactions
Account ID, optional time period
Retrieve all recent calls, emails, and account-linked context.
Aggregate themes, requests, blockers, sentiment shifts, and opportunities.
Apply a repeatable account review structure.
Summarise outcomes, open issues, and suggested next steps.
Structured QBR/account review summary with themes, risks, opportunities, and actions
Snippet Builder Skill
Skill
Help users consistently capture and label useful moments from calls
Identify useful moments in a call and convert them into reusable snippets
Call ID, optional focus area such as pricing, objection, competitor, discovery
Retrieve transcript, recording timeline, and call insights.
Detect moments matching the requested focus area.
Propose snippet start/end times and titles.
Tag snippets by type or theme.
Optionally save them or add them to a playlist.
One or more proposed or saved snippets with title, timing, and tags
💡 Technical details
Auth model needs specifying. Are API keys scoped per user, per team, or per Jiminny instance? If a key is generated by an admin, does it inherit their visibility level, or provide org-wide? Are permissions evaluated at query time or frozen at key creation? Needs to be query-time, otherwise permission changes won't propagate.
Key lifecycle management is missing. No mention of rotation, expiry, or revocation. A departed employee's active key is a data leak. Need: revocation, optional expiry, alerts on stale keys, and consider whether keys should be tied to service accounts rather than personal users.
Rate limiting should be HIGH. A compromised key or misconfigured automation could bulk-export an entire customer's call history. Need per-key rate limits and anomaly detection on unusual access patterns.
Open Questions
Track unresolved issues or decisions that need to be made. Update as answers become available.
Question
Answer
Date Answered
Competitor research
Competitor
MCP Availability
Core Capabilities
Advanced Capabilities
Positioning
Key Strength
Key Weakness
Gong
✅ Mature MCP
List/search calls
Get transcripts
get Call metadata
Deal intelligence
Scorecards, analytics
CRM context
Enterprise data layer
Deep data + ecosystem integrations
Limited opinionated AI workflows
Avoma
✅ Mature MCP
list_meetings
get_meeting
get_transcript
key topics
Deal fields/Deal level analysis
Coaching/Scoring
CRM context
pushing insights into Notion / Confluence
AI-ready meeting intelligence
Strongest “outputs” layer
Mostly pull-based interactions...
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Platform Sprint 2 Q2 - Platform Team - Scrum Board Platform Sprint 2 Q2 - Platform Team - Scrum Board - Jira
SevenShores\Hubspot\Exceptions\BadRequest: Client error: `POST [URL_WITH_CREDENTIALS] Graham . I made the product related changes in the table and for the rest I left them as a note in the Technical section for the team to look at when they start looking at this. I wonder about your points related to GDPR. Currently multiple customers are using the Customer API/zapier to feed this data to AI and BI tools. They are also manually exporting transcripts and other information from the platform and feeding it to AI tools. I don’t get how MCP is so much different that all of these and why it will introduce new data processors (which are already being utilised) and would require any changes to the consent provided by participants.
You said
Jiminny MCP Connector
Epic
Link to Epik in Jira
Document status
DRAFT
Objective
Enable customers to connect Jiminny data to external AI tools (Claude, OpenAI, Gemini) so it can be used as part of their broader knowledge base and workflows.
Position Jiminny as a data layer for AI-driven revenue workflows, not just a standalone product.
👤 Target user
Revenue teams using AI tools (Sales, CS, RevOps)
Companies already experimenting with Claude / OpenAI
Mid-market & Enterprise customers with multiple data sources (CRM, docs, CI tools, Support tools etc)
🤕 Pain point or problem
Jiminny data is locked in the platform
AI tools lack access to high-value conversation context
Customers must manually export/copy transcripts
No easy way to combine calls with CRM + docs + other info - using the Jiminny API is not suitable for non technical sales people
Peer pressure as almost all competitors have this
💥 Impact and benefits
For customers
Better AI outputs using real customer conversations
Ability to build automated workflows across tools
For Jiminny
Increased product stickiness (embedded in workflows)
Competitive parity with Gong / Avoma etc.
💡 Solution ideas
Build an AI Knowledge Connector (MCP-based) that:
Exposes Jiminny data (calls, transcripts, metadata) to AI tools
Provides structured insights (summaries, action items, scoring etc.)
Supports deal-level context
Allows integration into customer-owned AI stacks (Claude + Zapier, etc.)
Success metrics
List the key goals and how you will measure success. Include both qualitative and quantitative metrics (e.g., user adoption, retention rate, revenue targets).
Goal
Metric
Increase stickiness by ensuring Jiminny is embedded in the customer’s workflows
% of customers connecting external AI tools
Number of MCP/API calls per customer - and which ones are being used the most
Decrease the manual copying of transcripts
decrease by X %
User interaction and design
Simple setup flow:
Generate API key / connect MCP
Clear instructions for Claude / Zapier setup
Provide:
Example prompts for Claude
Pre-built workflow templates for Zapier
Clear documentation - with use cases
👉 Focus: usable by non-technical users
Detailed Requirements
List the functional and non-functional requirements. Prioritize them (e.g., High, Medium, Low) and add notes for clarification.
Requirement
Importance
Notes
Allow customers to connect Jiminny to their AI tools (e.g. Claude, OpenAI)
HIGH
Provide MCP endpoint so customers can easily integrate Jiminny into their AI stack
Allow customers to access call data through AI tools
HIGH
Expose Jiminny data:
list calls (filter by date, user, account, deal)
get call
get transcript (speaker-separated)
get call metadata
search calls (keyword + semantic)
Support filtering by:
account / contact/ lead / deal
jiminny user
date range
Allow customers to search and query calls using AI tools
HIGH
Support keyword and semantic search across conversations
Provide structured insights so customers can generate better outputs
HIGH
For each call, expose:
Summary
Action items
Key points
Activity type
Notes
Call Score
CRM information
Allow customers to understand deal status across multiple calls/emails
HIGH
For each deal expose:
calls/meetings/emails
Identified risks
contacts related to the deal with their job title
linked account details
all CRM field information that we have in DI + fields used for CRM filling
example - get_deal_summary
request -
{
"tool": "get_deal_summary",
"arguments": {
"deal_name": "ACME"
}
}
responce:
{
"deal_name": "ACME",
"stage": "Negotiation",
"recent_activity": [
"Demo call on 2026-04-01",
"Pricing discussion on 2026-04-03"
],
"risks": [
"Pricing concerns",
"Security review pending"
], "next_steps": [
"Send follow-up to VP Sales",
"Share security documentation"
]
}
Ensure the AI can easily understand the schema of the data coming from Jiminny
HIGH
Models perform much better when tools have:
clear names
rich descriptions
predictable schemas
Provide clear, actionable error states for customers when MCP connections fail
HIGH
Error messages should guide agents toward solutions with specific suggestions and next steps.
Expired or revoked key — “Error: Authentication failed. The API key used to access Jiminny has been revoked or has expired. Please ask your Jiminny admin to generate a new API key in Settings > Organization > General and reconnect the MCP server.”
Rate limit hit — “Error: Rate limit exceeded. Too many requests have been made to the Jiminny MCP server in a short period. Please wait 60 seconds before retrying.”
Permissions mismatch — if a user tries to access data outside their team visibility settings - “Error: Access denied. The requested call (call_id: [X]) is outside your team's visibility settings in Jiminny. Only calls within your permitted scope are accessible.”
Trying to access private meeting - “Error: Access denied. This meeting has been marked as private by the host and cannot be accessed through the MCP connector. Try requesting a different call or ask the meeting host to change the visibility settings in Jiminny.”
Downgraded/Capture account — if a customer's plan drops below Scale tier or the Customer is on Capture in the first place - “Error: MCP access unavailable. The Jiminny MCP connector is available on the Scale plan and above. Your account does not currently have an active Scale subscription.”
Jiminny-side outage — “Error:Jiminny is temporarily unavailable (status 503). This is not a data or permissions issue — please retry in a few minutes.”
No data found - “Error:No calls found matching your criteria. Try adjusting your filters — for example, widening the date range, removing the account filter, or checking the rep name is spelled correctly in Jiminny.”
Allow customers to securely control who and what data is accessible externally
HIGH
Ensure MCP only exposes data user has access to - based on team visibility settings. This means that if a user is not allow to access calls/deals in Jiminny UI then they shouldn’t be able to access those through the MCP as well.
Private meetings shouldn’t be exposed via MCP
HIGH
When a meetings is set to Private then the information about it shouldn’t be exposed through the MCP.
Ensure Jiminny data can be combined with other sources (e.g. CRM, docs) in AI workflows
HIGH
Ensure data is structured to be easily combined with:
CRM (accounts, deals)
external docs
Use consistent identifiers:
account IDs
deal IDs
MCP is available only for Scale tier and above
HIGH
Customers who are on Capture tier should be able to access any of their data through MCP.
This should also cover the scenario when a customer has been on Scale but then downgrades to Capture - their MCP access should stop working.
Provide visibility into how external AI tools access Jiminny data
HIGH
Audit logs:
what data was accessed by which external system when
identity - who made the request
specific queries/filters used
failed access attempts (especially cross-visibility-boundary attempts)
Admins should be able to access the logs from the org settings.We can start with a csv export before building a specific page for it.
example from Atlassian -
Provide customers with example prompts to get started quickly
HIGH
MCP prompts are explicitly defined as prompt templates that clients can discover and call with arguments.
See examples in table below.
Expose Jiminny as a Connector in Claude
medium
Competitors like Fathom are listed as Connectors in Claude. This will make it easier for customers to find us and to connect Jiminny
Provide customers with example workflows to get started quickly
medium
A workflow is usually multiple steps, maybe multiple tools, still focused on one outcome.
See examples in table below.
Allow customers to use predefined Jiminny skills for common workflows
medium
Anthropic describes Skills as folders that include instructions, scripts, and resources that Claude can load when relevant, and as a way to teach Claude repeatable workflows, preferences, and domain expertise once instead of re-explaining them every time. Skills - a reusable package of behavior that can include prompts, instructions, resources, and sometimes scripts/tools for a broader job.
Claude skills - https://resources.anthropic.com/hubfs/The-Complete-Guide-to-Building-Skill-for-Claude.pdf?hsLang=en&utm_source=chatgpt.com
See examples in table below.
Jiminny UI widget for OpenAI
medium
The reason to have this is to make certain Jiminny use cases much easier than pure chat.
Instead of ChatGPT only replying with text like “Here are the last 5 ACME calls,” it could also show a visual Jiminny card or mini-app inside the chat. That widget could list calls, show a deal summary, let the user filter by rep/date/account, open a transcript section, or save a snippet—while the conversation continues in normal chat alongside it.
For Jiminny, the best widget use cases are the ones where users need to browse or compare rather than ask one-off questions. A strong example is deal review: the user asks ChatGPT, “What is the status of the ACME deal?” ChatGPT calls your Jiminny MCP tools, and the widget shows a compact deal view with recent calls, risks, next steps, stakeholders, and links to transcripts/snippets. The chat can still summarize the answer in words, but the widget gives a clearer, scannable interface.
Another good Jiminny widget use case is call search and exploration. A text answer can say “I found 12 calls mentioning pricing objections,” but a widget could show a sortable list with date, rep, account, score, and objection count, then let the user click into one call to see the exact excerpt or jump to a transcript section.
Allow customers to run long-running analyses asynchronously and retrieve progress/results
low
Some requests/questions require analysis of Hugh volumes of data. For those, it may be better to:
start the job
let it run in the background
return a status like “in progress”
let the client come back for the result later
For example - User asks in Claude:
“Analyse all calls from this quarter and tell me the top 5 objections by segment.”
That might require:
searching lots of calls
pulling many summaries/transcripts
aggregating results
Instead of making Claude wait 45+ seconds, Jiminny could:
create an analysis job
return: job_id = 123, status = running
We need this in order to support:
large-scale analysis
multi-call aggregation across lots of data
playlist generation across many calls
heavy recap/report generation
Creating a snippet through the MCP
low
Create a shareable snippet from a call recording by specifying a time range. Useful for highlighting key moments — objection handling, pricing discussions, competitive mentions — and sharing them with your team.
example request:
{
"tool": "create_snippet",
"arguments": {
"call_id": "call_123",
"start_time": "00:18:24",
"end_time": "00:19:10",
"title": "Pricing objection"
}
}
example response:
{
"snippet_id": "snip_987",
"title": "Pricing objection",
"share_url": "https://app.jiminny.com/snippets/snip_987"
}
Ability to add recordings or snippets to a playlist
low
Allow customers to create libraries of calls automatically. They can use those for onboarding or other purposes
Allow AI tools to read reusable Jiminny resources
low
fathom
Resources are useful for data that should be read consistently rather than recomputed every time. In Jiminny terms, that could be:
current deal snapshot
account summary
weekly rep recap
approved talk tracks / objection handling guidance
curated playlists or snippet libraries
This is useful because an AI can consume these directly as context, instead of repeatedly stitching together many tool calls.
Ability to write coaching notes in Jiminny through MCP
low
What we want to do for prompts/worflows and skills
Capability
Type
User value / job to be done
Example Jiminny use case
Inputs
Steps performed
Output
Draft follow-up email
Prompt
Help reps quickly create tailored follow-ups after calls
Use the latest customer call to draft an email with recap and next steps
Call ID
optional tone
optional recipient type
Retrieve call summary and action items from Jiminny.
Pull key points, commitments, and next steps.
Apply the chosen tone and structure.
Draft the email in a consistent format.
Customer-ready follow-up email draft
Summarise call
Prompt
Help users quickly extract the most important points from a conversation
Generate a concise summary of one call for internal or external use
Call ID
optional summary style
optional audience
Retrieve transcript, metadata, and structured insights.
Identify key topics, decisions, risks, and next steps.
Format output for the chosen audience.
Short or structured call summary with actions and risks
Generate deal recap
Prompt
Help reps and managers get a fast overview of a deal
Summarise the current state of a deal based on recent calls and linked CRM context
Deal ID or account name
optional date range
Retrieve calls and meetings linked to the deal.
Pull deal metadata and CRM-linked context.
Identify recent changes, blockers, risks, and next steps.
Summarise into a concise recap.
Deal recap with status, blockers, risks, and recommended next steps
Prepare weekly recap
Prompt
Help managers or reps review what changed over a time period
Weekly recap of calls, themes, and actions for one rep, team, or account
Rep ID
team ID or account ID
time period
Retrieve relevant calls and summaries for the selected time period.
Aggregate themes, action items, and changes.
Highlight notable risks, opportunities, and follow-ups.
Weekly recap with top themes, risks, opportunities, and actions
Prepare deal review
Workflow
Help reps and managers review deal status using multiple sources of context
Review a deal before pipeline review or forecast meeting
Deal ID
optional date range
Retrieve all recent calls, emails, and meetings tied to the deal.
Pull structured call summaries, score, action items, and key points.
Pull linked CRM context such as stage, contacts, and account details.
Aggregate open risks, unresolved objections, stakeholder gaps, and next steps.
Format into a review-ready structure.
Deal review document with current status, risks, stakeholders, blockers, and next steps
Weekly team recap
Workflow
Help managers monitor activity and risk across a group of reps or accounts
End-of-week team summary for sales leadership
Team ID
date range
Retrieve calls and structured insights across the team.
Group by rep, account, or deal.
Identify recurring themes, major risks, strong calls, and missed follow-ups.
Highlight calls or deals that need attention.
Team-level recap with patterns, key risks, notable wins, and action areas
Objection analysis across calls
Workflow
Help teams identify patterns across multiple conversations
Analyse pricing or competitor objections across recent calls
Account ID
deal ID
rep ID
keyword/topic
date range
Search calls matching the topic or keyword.
Retrieve summaries, transcripts, and snippets where relevant.
Identify recurring objections and how they were handled.
Assess whether objections were resolved or remain open.
Summarise patterns and examples.
Objection analysis with themes, frequency, examples, and suggested follow-up actions
Build onboarding playlist
Workflow
Help enablement teams curate useful learning content faster
Build a playlist of strong discovery, demo, or pricing calls for new hires
Topic
call type
rep/team filter
optional time period
Search for calls matching the selected criteria.
Rank or filter calls based on score, topics, or key moments.
Identify useful snippets or full recordings.
Add selected calls/snippets into a playlist structure.
Generate short descriptions for each item.
Curated onboarding playlist with selected calls/snippets and descriptions
Deal Inspection Skill
Skill
Give users a consistent, opinionated way to assess a deal
Claude reviews a deal using a repeatable Jiminny methodology
Deal ID or account name
optional review scope
Determine whether the request is suitable for a deal inspection.
Retrieve relevant calls, summaries, CRM context, stakeholders, and risks.
Apply a standard Jiminny review framework to assess deal health.
Look for missing next steps, unresolved objections, stakeholder gaps, and warning signs.
Present findings in a consistent structure with recommended actions.
Structured deal inspection with health assessment, red flags, and recommendations
Manager Coaching Skill
Skill
Help managers review calls consistently and identify coaching moments
Analyse a rep’s call and surface strengths, gaps, and examples for coaching
Call ID
optional rep ID
optional coaching focus
Retrieve transcript, score, summary, and key moments from the call.
Evaluate the conversation against a coaching framework.
Identify what went well and where the rep could improve.
Suggest moments to clip as snippets.
Recommend coaching actions or playlist additions.
Coaching review with strengths, gaps, snippet suggestions, and recommended coaching actions
CSM / QBR Prep Skill
Skill
Help CS or AM teams prepare structured customer reviews from conversations
Generate an account review or QBR-style summary from recent customer interactions
Account ID, optional time period
Retrieve all recent calls, emails, and account-linked context.
Aggregate themes, requests, blockers, sentiment shifts, and opportunities.
Apply a repeatable account review structure.
Summarise outcomes, open issues, and suggested next steps.
Structured QBR/account review summary with themes, risks, opportunities, and actions
Snippet Builder Skill
Skill
Help users consistently capture and label useful moments from calls
Identify useful moments in a call and convert them into reusable snippets
Call ID, optional focus area such as pricing, objection, competitor, discovery
Retrieve transcript, recording timeline, and call insights.
Detect moments matching the requested focus area.
Propose snippet start/end times and titles.
Tag snippets by type or theme.
Optionally save them or add them to a playlist.
One or more proposed or saved snippets with title, timing, and tags
💡 Technical details
Auth model needs specifying. Are API keys scoped per user, per team, or per Jiminny instance? If a key is generated by an admin, does it inherit their visibility level, or provide org-wide? Are permissions evaluated at query time or frozen at key creation? Needs to be query-time, otherwise permission changes won't propagate.
Key lifecycle management is missing. No mention of rotation, expiry, or revocation. A departed employee's active key is a data leak. Need: revocation, optional expiry, alerts on stale keys, and consider whether keys should be tied to service accounts rather than personal users.
Rate limiting should be HIGH. A compromised key or misconfigured automation could bulk-export an entire customer's call history. Need per-key rate limits and anomaly detection on unusual access patterns.
Open Questions
Track unresolved issues or decisions that need to be made. Update as answers become available.
Question
Answer
Date Answered
Competitor research
Competitor
MCP Availability
Core Capabilities
Advanced Capabilities
Positioning
Key Strength
Key Weakness
Gong
✅ Mature MCP
List/search calls
Get transcripts
get Call metadata
Deal intelligence
Scorecards, analytics
CRM context
Enterprise data layer
Deep data + ecosystem integrations
Limited opinionated AI workflows
Avoma
✅ Mature MCP
list_meetings
get_meeting
get_transcript
key topics
Deal fields/Deal level analysis
Coaching/Scoring
CRM context
pushing insights into Notion / Confluence
AI-ready meeting intelligence
Strongest “outputs” layer
Mostly pull-based interactions
Fathom
✅ MCP
list/search meetings
get transcript
get summary/action items
Team/org context
Webhooks (event-based triggers)
get_weekly_recap
aggregated action items across meetings
creating webhooks directly from the MCP server
Lightweight meeting data access
Includes summaries + actions
Limited analytics depth
Grain
✅ Basic MCP
get meetings
download transcripts
Notes
Deals
Scorecards
Data access utility
Simple + accessible
Low sophistication, sometimes browser-based
Outreach
⚠️ MCP (workflow-focused)
Search sequences
Emails
Meetings (Kaia)
account / prospect / opportunity lookups
Workflow automation
Multi-system orchestration
Revenue workflow engine
End-to-end GTM workflows
Less depth in conversation data
Attention
⚠️ Emerging MCP
Meeting data
Transcripts
CRM-linked context
AI insights
Sales assistant workflows
create snippets
AI sales assistant + CRM
Strong CRM linkage
Less focus on external knowledge layer
Planhat -
Related content
Ask Jiminny Anything on Call level
Galya Dimitrova
Hubspot app
Galya Dimitrova
Product Vision & Strategy
Galya Dimitrova
Automated CRM Filling
Simona Georgieva (Deactivated)
Competitive analysis
Galya Dimitrova
AI agent ideas
Steliyan Georgiev
Comments
James Graham
9 Apr
A few areas around Security & Compliance that need more depth before this moves beyond draft:
Auth model needs specifying. Are API keys scoped per user, per team, or per Jiminny instance? If a key is generated by an admin, does it inherit their visibility level, or provide org-wide? Are permissions evaluated at query time or frozen at key creation? Needs to be query-time, otherwise permission changes won't propagate.
Team visibility enforcement should be its own HIGH requirement. The current note under access control ("ensure MCP only exposes data user has access to") is doing too much work as a single line. Every MCP tool response (especially search_calls and deal-level aggregations) must be filtered through the same visibility engine as the UI. Semantic search is the riskiest here; it could surface results across team boundaries if not properly scoped.
No data minimisation or scoping controls. We're exposing transcripts, CRM fields, contact details with job titles, deal context - significant PII and commercial data leaving the platform. Can customers configure which data types are exposed? Can transcripts be PII-stripped before they leave Jiminny? Given we position GDPR consent as a differentiator, we should be thinking about this.
GDPR downstream processing is unaddressed. Piping transcripts to OpenAI/Gemini introduces new data processors. Customers need to acknowledge responsibility for downstream processing during setup. We should also consider whether call participants' recording consent covers onward sharing to third-party AI - it almost certainly doesn't by default. This is one for me to pick up.
Key lifecycle management is missing. No mention of rotation, expiry, or revocation. A departed employee's active key is a data leak. Need: revocation, optional expiry, alerts on stale keys, and consider whether keys should be tied to service accounts rather than personal users.
Rate limiting should be HIGH. A compromised key or misconfigured automation could bulk-export an entire customer's call history. Need per-key rate limits and anomaly detection on unusual ac...
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Objective Enable customers to connect Jiminny data to external AI tools (Claude, OpenAI, Gemini) so it can be used as part of their broader knowledge base and workflows. Position Jiminny as a data layer for AI-driven revenue workflows, not just a standalone product. 👤 Target user Revenue teams using AI tools (Sales, CS, RevOps) Companies already experimenting with Claude / OpenAI Mid-market & Enterprise customers with multiple data sources (CRM, docs, CI tools, Support tools etc) 🤕 Pain point or problem Jiminny data is locked in the platform AI tools lack access to high-value conversation context Customers must manually export/copy transcripts No easy way to combine calls with CRM + docs + other info - using the Jiminny API is not suitable for non technical sales people Peer pressure as almost all competitors have this 💥 Impact and benefits For customers Better AI outputs using real customer conversations Ability to build automated workflows across tools For Jiminny Increased product stickiness (embedded in workflows) Competitive parity with Gong / Avoma etc. 💡 Solution ideas Build an AI Knowledge Connector (MCP-based) that: Exposes Jiminny data (calls, transcripts, metadata) to AI tools Provides structured insights (summaries, action items, scoring etc.) Supports deal-level context Allows integration into customer-owned AI stacks (Claude + Zapier, etc.) Success metrics List the key goals and how you will measure success. Include both qualitative and quantitative metrics (e.g., user adoption, retention rate, revenue targets). Goal Metric Increase stickiness by ensuring Jiminny is embedded in the customer’s workflows % of customers connecting external AI tools Number of MCP/API calls per customer - and which ones are being used the most Decrease the manual copying of transcripts decrease by X % User interaction and design Simple setup flow: Generate API key / connect MCP Clear instructions for Claude / Zapier setup Provide: Example prompts for Claude Pre-built workflow templates for Zapier Clear documentation - with use cases 👉 Focus: usable by non-technical users Detailed Requirements List the functional and non-functional requirements. Prioritize them (e.g., High, Medium, Low) and add notes for clarification. Requirement Importance Notes Allow customers to connect Jiminny to their AI tools (e.g. Claude, OpenAI) HIGH Provide MCP endpoint so customers can easily integrate Jiminny into their AI stack Allow customers to access call data through AI tools HIGH Expose Jiminny data: list calls (filter by date, user, account, deal) get call get transcript (speaker-separated) get call metadata search calls (keyword + semantic) Support filtering by: account / contact/ lead / deal jiminny user date range Allow customers to search and query calls using AI tools HIGH Support keyword and semantic search across conversations Provide structured insights so customers can generate better outputs HIGH For each call, expose: Summary Action items Key points Activity type Notes Call Score CRM information Allow customers to understand deal status across multiple calls/emails HIGH For each deal expose: calls/meetings/emails Identified risks contacts related to the deal with their job title linked account details all CRM field information that we have in DI + fields used for CRM filling example - get_deal_summary request - { \"tool\": \"get_deal_summary\", \"arguments\": { \"deal_name\": \"ACME\" } } responce: { \"deal_name\": \"ACME\", \"stage\": \"Negotiation\", \"recent_activity\": [ \"Demo call on 2026-04-01\", \"Pricing discussion on 2026-04-03\" ], \"risks\": [ \"Pricing concerns\", \"Security review pending\" ], \"next_steps\": [ \"Send follow-up to VP Sales\", \"Share security documentation\" ] } Ensure the AI can easily understand the schema of the data coming from Jiminny HIGH Models perform much better when tools have: clear names rich descriptions predictable schemas Provide clear, actionable error states for customers when MCP connections fail HIGH Error messages should guide agents toward solutions with specific suggestions and next steps. Expired or revoked key — “Error: Authentication failed. The API key used to access Jiminny has been revoked or has expired. Please ask your Jiminny admin to generate a new API key in Settings > Organization > General and reconnect the MCP server.” Rate limit hit — “Error: Rate limit exceeded. Too many requests have been made to the Jiminny MCP server in a short period. Please wait 60 seconds before retrying.” Permissions mismatch — if a user tries to access data outside their team visibility settings - “Error: Access denied. The requested call (call_id: [X]) is outside your team's visibility settings in Jiminny. Only calls within your permitted scope are accessible.” Trying to access private meeting - “Error: Access denied. This meeting has been marked as private by the host and cannot be accessed through the MCP connector. Try requesting a different call or ask the meeting host to change the visibility settings in Jiminny.” Downgraded/Capture account — if a customer's plan drops below Scale tier or the Customer is on Capture in the first place - “Error: MCP access unavailable. The Jiminny MCP connector is available on the Scale plan and above. Your account does not currently have an active Scale subscription.” Jiminny-side outage — “Error:Jiminny is temporarily unavailable (status 503). This is not a data or permissions issue — please retry in a few minutes.” No data found - “Error:No calls found matching your criteria. Try adjusting your filters — for example, widening the date range, removing the account filter, or checking the rep name is spelled correctly in Jiminny.” Allow customers to securely control who and what data is accessible externally HIGH Ensure MCP only exposes data user has access to - based on team visibility settings. This means that if a user is not allow to access calls/deals in Jiminny UI then they shouldn’t be able to access those through the MCP as well. Private meetings shouldn’t be exposed via MCP HIGH When a meetings is set to Private then the information about it shouldn’t be exposed through the MCP. Ensure Jiminny data can be combined with other sources (e.g. CRM, docs) in AI workflows HIGH Ensure data is structured to be easily combined with: CRM (accounts, deals) external docs Use consistent identifiers: account IDs deal IDs MCP is available only for Scale tier and above HIGH Customers who are on Capture tier should be able to access any of their data through MCP. This should also cover the scenario when a customer has been on Scale but then downgrades to Capture - their MCP access should stop working. Provide visibility into how external AI tools access Jiminny data HIGH Audit logs: what data was accessed by which external system when identity - who made the request specific queries/filters used failed access attempts (especially cross-visibility-boundary attempts) Admins should be able to access the logs from the org settings.We can start with a csv export before building a specific page for it. example from Atlassian - Provide customers with example prompts to get started quickly HIGH MCP prompts are explicitly defined as prompt templates that clients can discover and call with arguments. See examples in table below. Expose Jiminny as a Connector in Claude medium Competitors like Fathom are listed as Connectors in Claude. This will make it easier for customers to find us and to connect Jiminny Provide customers with example workflows to get started quickly medium A workflow is usually multiple steps, maybe multiple tools, still focused on one outcome. See examples in table below. Allow customers to use predefined Jiminny skills for common workflows medium Anthropic describes Skills as folders that include instructions, scripts, and resources that Claude can load when relevant, and as a way to teach Claude repeatable workflows, preferences, and domain expertise once instead of re-explaining them every time. Skills - a reusable package of behavior that can include prompts, instructions, resources, and sometimes scripts/tools for a broader job. Claude skills - https://resources.anthropic.com/hubfs/The-Complete-Guide-to-Building-Skill-for-Claude.pdf?hsLang=en&utm_source=chatgpt.com See examples in table below. Jiminny UI widget for OpenAI medium The reason to have this is to make certain Jiminny use cases much easier than pure chat. Instead of ChatGPT only replying with text like “Here are the last 5 ACME calls,” it could also show a visual Jiminny card or mini-app inside the chat. That widget could list calls, show a deal summary, let the user filter by rep/date/account, open a transcript section, or save a snippet—while the conversation continues in normal chat alongside it. For Jiminny, the best widget use cases are the ones where users need to browse or compare rather than ask one-off questions. A strong example is deal review: the user asks ChatGPT, “What is the status of the ACME deal?” ChatGPT calls your Jiminny MCP tools, and the widget shows a compact deal view with recent calls, risks, next steps, stakeholders, and links to transcripts/snippets. The chat can still summarize the answer in words, but the widget gives a clearer, scannable interface. Another good Jiminny widget use case is call search and exploration. A text answer can say “I found 12 calls mentioning pricing objections,” but a widget could show a sortable list with date, rep, account, score, and objection count, then let the user click into one call to see the exact excerpt or jump to a transcript section. Allow customers to run long-running analyses asynchronously and retrieve progress/results low Some requests/questions require analysis of Hugh volumes of data. For those, it may be better to: start the job let it run in the background return a status like “in progress” let the client come back for the result later For example - User asks in Claude: “Analyse all calls from this quarter and tell me the top 5 objections by segment.” That might require: searching lots of calls pulling many summaries/transcripts aggregating results Instead of making Claude wait 45+ seconds, Jiminny could: create an analysis job return: job_id = 123, status = running We need this in order to support: large-scale analysis multi-call aggregation across lots of data playlist generation across many calls heavy recap/report generation Creating a snippet through the MCP low Create a shareable snippet from a call recording by specifying a time range. Useful for highlighting key moments — objection handling, pricing discussions, competitive mentions — and sharing them with your team. example request: { \"tool\": \"create_snippet\", \"arguments\": { \"call_id\": \"call_123\", \"start_time\": \"00:18:24\", \"end_time\": \"00:19:10\", \"title\": \"Pricing objection\" } } example response: { \"snippet_id\": \"snip_987\", \"title\": \"Pricing objection\", \"share_url\": \"https://app.jiminny.com/snippets/snip_987\" } Ability to add recordings or snippets to a playlist low Allow customers to create libraries of calls automatically. They can use those for onboarding or other purposes Allow AI tools to read reusable Jiminny resources low fathom Resources are useful for data that should be read consistently rather than recomputed every time. In Jiminny terms, that could be: current deal snapshot account summary weekly rep recap approved talk tracks / objection handling guidance curated playlists or snippet libraries This is useful because an AI can consume these directly as context, instead of repeatedly stitching together many tool calls. Ability to write coaching notes in Jiminny through MCP low What we want to do for prompts/worflows and skills Capability Type User value / job to be done Example Jiminny use case Inputs Steps performed Output Draft follow-up email Prompt Help reps quickly create tailored follow-ups after calls Use the latest customer call to draft an email with recap and next steps Call ID optional tone optional recipient type Retrieve call summary and action items from Jiminny. Pull key points, commitments, and next steps. Apply the chosen tone and structure. Draft the email in a consistent format. Customer-ready follow-up email draft Summarise call Prompt Help users quickly extract the most important points from a conversation Generate a concise summary of one call for internal or external use Call ID optional summary style optional audience Retrieve transcript, metadata, and structured insights. Identify key topics, decisions, risks, and next steps. Format output for the chosen audience. Short or structured call summary with actions and risks Generate deal recap Prompt Help reps and managers get a fast overview of a deal Summarise the current state of a deal based on recent calls and linked CRM context Deal ID or account name optional date range Retrieve calls and meetings linked to the deal. Pull deal metadata and CRM-linked context. Identify recent changes, blockers, risks, and next steps. Summarise into a concise recap. Deal recap with status, blockers, risks, and recommended next steps Prepare weekly recap Prompt Help managers or reps review what changed over a time period Weekly recap of calls, themes, and actions for one rep, team, or account Rep ID team ID or account ID time period Retrieve relevant calls and summaries for the selected time period. Aggregate themes, action items, and changes. Highlight notable risks, opportunities, and follow-ups. Weekly recap with top themes, risks, opportunities, and actions Prepare deal review Workflow Help reps and managers review deal status using multiple sources of context Review a deal before pipeline review or forecast meeting Deal ID optional date range Retrieve all recent calls, emails, and meetings tied to the deal. Pull structured call summaries, score, action items, and key points. Pull linked CRM context such as stage, contacts, and account details. Aggregate open risks, unresolved objections, stakeholder gaps, and next steps. Format into a review-ready structure. Deal review document with current status, risks, stakeholders, blockers, and next steps Weekly team recap Workflow Help managers monitor activity and risk across a group of reps or accounts End-of-week team summary for sales leadership Team ID date range Retrieve calls and structured insights across the team. Group by rep, account, or deal. Identify recurring themes, major risks, strong calls, and missed follow-ups. Highlight calls or deals that need attention. Team-level recap with patterns, key risks, notable wins, and action areas Objection analysis across calls Workflow Help teams identify patterns across multiple conversations Analyse pricing or competitor objections across recent calls Account ID deal ID rep ID keyword/topic date range Search calls matching the topic or keyword. Retrieve summaries, transcripts, and snippets where relevant. Identify recurring objections and how they were handled. Assess whether objections were resolved or remain open. Summarise patterns and examples. Objection analysis with themes, frequency, examples, and suggested follow-up actions Build onboarding playlist Workflow Help enablement teams curate useful learning content faster Build a playlist of strong discovery, demo, or pricing calls for new hires Topic call type rep/team filter optional time period Search for calls matching the selected criteria. Rank or filter calls based on score, topics, or key moments. Identify useful snippets or full recordings. Add selected calls/snippets into a playlist structure. Generate short descriptions for each item. Curated onboarding playlist with selected calls/snippets and descriptions Deal Inspection Skill Skill Give users a consistent, opinionated way to assess a deal Claude reviews a deal using a repeatable Jiminny methodology Deal ID or account name optional review scope Determine whether the request is suitable for a deal inspection. Retrieve relevant calls, summaries, CRM context, stakeholders, and risks. Apply a standard Jiminny review framework to assess deal health. Look for missing next steps, unresolved objections, stakeholder gaps, and warning signs. Present findings in a consistent structure with recommended actions. Structured deal inspection with health assessment, red flags, and recommendations Manager Coaching Skill Skill Help managers review calls consistently and identify coaching moments Analyse a rep’s call and surface strengths, gaps, and examples for coaching Call ID optional rep ID optional coaching focus Retrieve transcript, score, summary, and key moments from the call. Evaluate the conversation against a coaching framework. Identify what went well and where the rep could improve. Suggest moments to clip as snippets. Recommend coaching actions or playlist additions. Coaching review with strengths, gaps, snippet suggestions, and recommended coaching actions CSM / QBR Prep Skill Skill Help CS or AM teams prepare structured customer reviews from conversations Generate an account review or QBR-style summary from recent customer interactions Account ID, optional time period Retrieve all recent calls, emails, and account-linked context. Aggregate themes, requests, blockers, sentiment shifts, and opportunities. Apply a repeatable account review structure. Summarise outcomes, open issues, and suggested next steps. Structured QBR/account review summary with themes, risks, opportunities, and actions Snippet Builder Skill Skill Help users consistently capture and label useful moments from calls Identify useful moments in a call and convert them into reusable snippets Call ID, optional focus area such as pricing, objection, competitor, discovery Retrieve transcript, recording timeline, and call insights. Detect moments matching the requested focus area. Propose snippet start/end times and titles. Tag snippets by type or theme. Optionally save them or add them to a playlist. One or more proposed or saved snippets with title, timing, and tags 💡 Technical details Auth model needs specifying. Are API keys scoped per user, per team, or per Jiminny instance? If a key is generated by an admin, does it inherit their visibility level, or provide org-wide? Are permissions evaluated at query time or frozen at key creation? Needs to be query-time, otherwise permission changes won't propagate. Key lifecycle management is missing. No mention of rotation, expiry, or revocation. A departed employee's active key is a data leak. Need: revocation, optional expiry, alerts on stale keys, and consider whether keys should be tied to service accounts rather than personal users. Rate limiting should be HIGH. A compromised key or misconfigured automation could bulk-export an entire customer's call history. Need per-key rate limits and anomaly detection on unusual access patterns. Open Questions Track unresolved issues or decisions that need to be made. Update as answers become available. Question Answer Date Answered Competitor research Competitor MCP Availability Core Capabilities Advanced Capabilities Positioning Key Strength Key Weakness Gong ✅ Mature MCP List/search calls Get transcripts get Call metadata Deal intelligence Scorecards, analytics CRM context Enterprise data layer Deep data + ecosystem integrations Limited opinionated AI workflows Avoma ✅ Mature MCP list_meetings get_meeting get_transcript key topics Deal fields/Deal level analysis Coaching/Scoring CRM context pushing insights into Notion / Confluence AI-ready meeting intelligence Strongest “outputs” layer Mostly pull-based interactions Fathom ✅ MCP list/search meetings get transcript get summary/action items Team/org context Webhooks (event-based triggers) get_weekly_recap aggregated action items across meetings creating webhooks directly from the MCP server Lightweight meeting data access Includes summaries + actions Limited analytics depth Grain ✅ Basic MCP get meetings download transcripts Notes Deals Scorecards Data access utility Simple + accessible Low sophistication, sometimes browser-based Outreach ⚠️ MCP (workflow-focused) Search sequences Emails Meetings (Kaia) account / prospect / opportunity lookups Workflow automation Multi-system orchestration Revenue workflow engine End-to-end GTM workflows Less depth in conversation data Attention ⚠️ Emerging MCP Meeting data Transcripts CRM-linked context AI insights Sales assistant workflows create snippets AI sales assistant + CRM Strong CRM linkage Less focus on external knowledge layer Planhat - Related content Ask Jiminny Anything on Call level Galya Dimitrova Hubspot app Galya Dimitrova Product Vision & Strategy Galya Dimitrova Automated CRM Filling Simona Georgieva (Deactivated) Competitive analysis Galya Dimitrova AI agent ideas Steliyan Georgiev Comments James Graham 9 Apr A few areas around Security & Compliance that need more depth before this moves beyond draft: Auth model needs specifying. Are API keys scoped per user, per team, or per Jiminny instance? If a key is generated by an admin, does it inherit their visibility level, or provide org-wide? Are permissions evaluated at query time or frozen at key creation? Needs to be query-time, otherwise permission changes won't propagate. Team visibility enforcement should be its own HIGH requirement. The current note under access control (\"ensure MCP only exposes data user has access to\") is doing too much work as a single line. Every MCP tool response (especially search_calls and deal-level aggregations) must be filtered through the same visibility engine as the UI. Semantic search is the riskiest here; it could surface results across team boundaries if not properly scoped. No data minimisation or scoping controls. We're exposing transcripts, CRM fields, contact details with job titles, deal context - significant PII and commercial data leaving the platform. Can customers configure which data types are exposed? Can transcripts be PII-stripped before they leave Jiminny? Given we position GDPR consent as a differentiator, we should be thinking about this. GDPR downstream processing is unaddressed. Piping transcripts to OpenAI/Gemini introduces new data processors. Customers need to acknowledge responsibility for downstream processing during setup. We should also consider whether call participants' recording consent covers onward sharing to third-party AI - it almost certainly doesn't by default. This is one for me to pick up. Key lifecycle management is missing. No mention of rotation, expiry, or revocation. A departed employee's active key is a data leak. Need: revocation, optional expiry, alerts on stale keys, and consider whether keys should be tied to service accounts rather than personal users. Rate limiting should be HIGH. A compromised key or misconfigured automation could bulk-export an entire customer's call history. Need per-key rate limits and anomaly detection on unusual access patterns. Audit logs should go deeper. Current spec (what data, which system, when) is a start. Add: identity behind the key, specific queries/filters used, and failed access attempts (especially cross-visibility-boundary attempts). Enterprise compliance teams will expect this. Downgrade handling. Doc says Scale tier and above, but doesn't say what happens on downgrade. Keys should auto-deactivate. Happy to help draft a dedicated Security & Compliance section if useful. Galya Dimitrova 15 Apr Thanks for the input @James Graham . I made the product related changes in the table and for the rest I left them as a note in the Technical section for the team to look at when they start looking at this. I wonder about your points related to GDPR. Currently multiple customers are using the Customer API/zapier to feed this data to AI and BI tools. They are also manually exporting transcripts and other information from the platform and feeding it to AI tools. I don’t get how MCP is so much different that all of these and why it will introduce new data processors (which are already being utilised) and would require any changes to the consent provided by participants.","depth":21,"bounds":{"left":0.41805187,"top":0.19313647,"width":0.051861703,"height":0.11173184},"help_text":"","role_description":"heading","subrole":"AXUnknown"},{"role":"AXStaticText","text":"You said","depth":23,"bounds":{"left":0.36053857,"top":0.19553073,"width":0.019946808,"height":0.016360734},"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"Jiminny MCP Connector","depth":23,"bounds":{"left":0.41805187,"top":0.1963288,"width":0.03125,"height":0.038707104},"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"Epic","depth":23,"bounds":{"left":0.41805187,"top":0.30806065,"width":0.010305851,"height":0.016360734},"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"Link to Epik in Jira","depth":23,"bounds":{"left":0.41805187,"top":0.33040702,"width":0.043218084,"height":0.016360734},"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"Document status","depth":23,"bounds":{"left":0.41805187,"top":0.3527534,"width":0.04105718,"height":0.016360734},"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"DRAFT","depth":23,"bounds":{"left":0.41805187,"top":0.37509975,"width":0.016289894,"height":0.016360734},"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"Objective","depth":23,"bounds":{"left":0.41805187,"top":0.39744613,"width":0.024268618,"height":0.016360734},"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"Enable customers to connect Jiminny data to external AI tools (Claude, OpenAI, Gemini) so it can be used as part of their broader knowledge base and workflows.","depth":23,"bounds":{"left":0.41805187,"top":0.4197925,"width":0.051529255,"height":0.17278531},"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"Position Jiminny as a data layer for AI-driven revenue workflows, not just a standalone product.","depth":23,"bounds":{"left":0.41805187,"top":0.59856343,"width":0.049700797,"height":0.10574621},"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"👤 Target user","depth":23,"bounds":{"left":0.41805187,"top":0.75458896,"width":0.033909574,"height":0.016759777},"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"Revenue teams using AI tools (Sales, CS, RevOps)","depth":23,"bounds":{"left":0.41805187,"top":0.7773344,"width":0.051030584,"height":0.061053474},"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"Companies already experimenting with Claude / OpenAI","depth":23,"bounds":{"left":0.41805187,"top":0.8443735,"width":0.04637633,"height":0.061053474},"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"Mid-market & Enterprise customers with multiple data sources (CRM, docs, CI tools, Support tools etc)","depth":23,"bounds":{"left":0.41805187,"top":0.9114126,"width":0.051363032,"height":0.0885874},"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"🤕 Pain point or problem","depth":23,"bounds":{"left":0.41805187,"top":1.0,"width":0.03706782,"height":-0.0897845},"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"Jiminny data is locked in the platform","depth":23,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"AI tools lack access to high-value conversation context","depth":23,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"Customers must manually export/copy transcripts","depth":23,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"No easy way to combine calls with CRM + docs + other info - 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The API key used to access Jiminny has been revoked or has expired. Please ask your Jiminny admin to generate a new API key in Settings > Organization > General and reconnect the MCP server.”","depth":23,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"Rate limit hit — “Error: Rate limit exceeded. Too many requests have been made to the Jiminny MCP server in a short period. Please wait 60 seconds before retrying.”","depth":23,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"Permissions mismatch — if a user tries to access data outside their team visibility settings - “Error: Access denied. The requested call (call_id: [X]) is outside your team's visibility settings in Jiminny. Only calls within your permitted scope are accessible.”","depth":23,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"Trying to access private meeting - “Error: Access denied. 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This is not a data or permissions issue — please retry in a few minutes.”","depth":23,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"No data found - “Error:No calls found matching your criteria. Try adjusting your filters — for example, widening the date range, removing the account filter, or checking the rep name is spelled correctly in Jiminny.”","depth":23,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"Allow customers to securely control who and what data is accessible externally","depth":23,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"HIGH","depth":23,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"Ensure MCP only exposes data user has access to - based on team visibility settings. This means that if a user is not allow to access calls/deals in Jiminny UI then they shouldn’t be able to access those through the MCP as well.","depth":23,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"Private meetings shouldn’t be exposed via MCP","depth":23,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"HIGH","depth":23,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"When a meetings is set to Private then the information about it shouldn’t be exposed through the MCP.","depth":23,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"Ensure Jiminny data can be combined with other sources (e.g. CRM, docs) in AI workflows","depth":23,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"HIGH","depth":23,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"Ensure data is structured to be easily combined with:","depth":23,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"CRM (accounts, deals)","depth":23,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"external docs","depth":23,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"Use consistent identifiers:","depth":23,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"account IDs","depth":23,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"deal IDs","depth":23,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"MCP is available only for Scale tier and above","depth":23,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"HIGH","depth":23,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"Customers who are on Capture tier should be able to access any of their data through MCP.","depth":23,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"This should also cover the scenario when a customer has been on Scale but then downgrades to Capture - their MCP access should stop working.","depth":23,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"Provide visibility into how external AI tools access Jiminny data","depth":23,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"HIGH","depth":23,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"Audit logs:","depth":23,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"what data was accessed by which external system when","depth":23,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"identity - who made the request","depth":23,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"specific queries/filters used","depth":23,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"failed access attempts (especially cross-visibility-boundary attempts)","depth":23,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"Admins should be able to access the logs from the org settings.We can start with a csv export before building a specific page for it.","depth":23,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"example from Atlassian -","depth":23,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"Provide customers with example prompts to get started quickly","depth":23,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"HIGH","depth":23,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"MCP prompts are explicitly defined as prompt templates that clients can discover and call with arguments.","depth":23,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"See examples in table below.","depth":23,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"Expose Jiminny as a Connector in Claude","depth":23,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"medium","depth":23,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"Competitors like Fathom are listed as Connectors in Claude. This will make it easier for customers to find us and to connect Jiminny","depth":23,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"Provide customers with example workflows to get started quickly","depth":23,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"medium","depth":23,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"A workflow is usually multiple steps, maybe multiple tools, still focused on one outcome.","depth":23,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"See examples in table below.","depth":23,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"Allow customers to use predefined Jiminny skills for common workflows","depth":23,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"medium","depth":23,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"Anthropic describes Skills as folders that include instructions, scripts, and resources that Claude can load when relevant, and as a way to teach Claude repeatable workflows, preferences, and domain expertise once instead of re-explaining them every time. Skills - a reusable package of behavior that can include prompts, instructions, resources, and sometimes scripts/tools for a broader job.","depth":23,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"Claude skills - https://resources.anthropic.com/hubfs/The-Complete-Guide-to-Building-Skill-for-Claude.pdf?hsLang=en&utm_source=chatgpt.com","depth":23,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"See examples in table below.","depth":23,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"Jiminny UI widget for OpenAI","depth":23,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"medium","depth":23,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"The reason to have this is to make certain Jiminny use cases much easier than pure chat.","depth":23,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"Instead of ChatGPT only replying with text like “Here are the last 5 ACME calls,” it could also show a visual Jiminny card or mini-app inside the chat. That widget could list calls, show a deal summary, let the user filter by rep/date/account, open a transcript section, or save a snippet—while the conversation continues in normal chat alongside it.","depth":23,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"For Jiminny, the best widget use cases are the ones where users need to browse or compare rather than ask one-off questions. A strong example is deal review: the user asks ChatGPT, “What is the status of the ACME deal?” ChatGPT calls your Jiminny MCP tools, and the widget shows a compact deal view with recent calls, risks, next steps, stakeholders, and links to transcripts/snippets. The chat can still summarize the answer in words, but the widget gives a clearer, scannable interface.","depth":23,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"Another good Jiminny widget use case is call search and exploration. A text answer can say “I found 12 calls mentioning pricing objections,” but a widget could show a sortable list with date, rep, account, score, and objection count, then let the user click into one call to see the exact excerpt or jump to a transcript section.","depth":23,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"Allow customers to run long-running analyses asynchronously and retrieve progress/results","depth":23,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"low","depth":23,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"Some requests/questions require analysis of Hugh volumes of data. For those, it may be better to:","depth":23,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"start the job","depth":23,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"let it run in the background","depth":23,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"return a status like “in progress”","depth":23,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"let the client come back for the result later","depth":23,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"For example - User asks in Claude:","depth":23,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"“Analyse all calls from this quarter and tell me the top 5 objections by segment.”","depth":23,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"That might require:","depth":23,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"searching lots of calls","depth":23,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"pulling many summaries/transcripts","depth":23,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"aggregating results","depth":23,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"Instead of making Claude wait 45+ seconds, Jiminny could:","depth":23,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"create an analysis job","depth":23,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"return: job_id = 123, status = running","depth":23,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"We need this in order to support:","depth":23,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"large-scale analysis","depth":23,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"multi-call aggregation across lots of data","depth":23,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"playlist generation across many calls","depth":23,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"heavy recap/report generation","depth":23,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"Creating a snippet through the MCP","depth":23,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"low","depth":23,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"Create a shareable snippet from a call recording by specifying a time range. Useful for highlighting key moments — objection handling, pricing discussions, competitive mentions — and sharing them with your team.","depth":23,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"example request:","depth":23,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"{","depth":23,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"\"tool\": \"create_snippet\",","depth":23,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"\"arguments\": {","depth":23,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"\"call_id\": \"call_123\",","depth":23,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"\"start_time\": \"00:18:24\",","depth":23,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"\"end_time\": \"00:19:10\",","depth":23,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"\"title\": \"Pricing objection\"","depth":23,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"}","depth":23,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"}","depth":23,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"example response:","depth":23,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"{","depth":23,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"\"snippet_id\": \"snip_987\",","depth":23,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"\"title\": \"Pricing objection\",","depth":23,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"\"share_url\": \"https://app.jiminny.com/snippets/snip_987\"","depth":23,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"}","depth":23,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"Ability to add recordings or snippets to a playlist","depth":23,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"low","depth":23,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"Allow customers to create libraries of calls automatically. They can use those for onboarding or other purposes","depth":23,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"Allow AI tools to read reusable Jiminny resources","depth":23,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"low","depth":23,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"fathom","depth":23,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"Resources are useful for data that should be read consistently rather than recomputed every time. In Jiminny terms, that could be:","depth":23,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"current deal snapshot","depth":23,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"account summary","depth":23,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"weekly rep recap","depth":23,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"approved talk tracks / objection handling guidance","depth":23,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"curated playlists or snippet libraries","depth":23,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"This is useful because an AI can consume these directly as context, instead of repeatedly stitching together many tool calls.","depth":23,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"Ability to write coaching notes in Jiminny through MCP","depth":23,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"low","depth":23,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"What we want to do for prompts/worflows and skills","depth":23,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"Capability","depth":23,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"Type","depth":23,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"User value / job to be done","depth":23,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"Example Jiminny use 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Are API keys scoped per user, per team, or per Jiminny instance? If a key is generated by an admin, does it inherit their visibility level, or provide org-wide? Are permissions evaluated at query time or frozen at key creation? Needs to be query-time, otherwise permission changes won't propagate.","depth":23,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"Team visibility enforcement should be its own HIGH requirement. The current note under access control (\"ensure MCP only exposes data user has access to\") is doing too much work as a single line. Every MCP tool response (especially search_calls and deal-level aggregations) must be filtered through the same visibility engine as the UI. Semantic search is the riskiest here; it could surface results across team boundaries if not properly scoped.","depth":23,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"No data minimisation or scoping controls. We're exposing transcripts, CRM fields, contact details with job titles, deal context - significant PII and commercial data leaving the platform. Can customers configure which data types are exposed? Can transcripts be PII-stripped before they leave Jiminny? Given we position GDPR consent as a differentiator, we should be thinking about this.","depth":23,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"GDPR downstream processing is unaddressed. Piping transcripts to OpenAI/Gemini introduces new data processors. Customers need to acknowledge responsibility for downstream processing during setup. We should also consider whether call participants' recording consent covers onward sharing to third-party AI - it almost certainly doesn't by default. This is one for me to pick up.","depth":23,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"Key lifecycle management is missing. No mention of rotation, expiry, or revocation. A departed employee's active key is a data leak. Need: revocation, optional expiry, alerts on stale keys, and consider whether keys should be tied to service accounts rather than personal users.","depth":23,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"Rate limiting should be HIGH. A compromised key or misconfigured automation could bulk-export an entire customer's call history. Need per-key rate limits and anomaly detection on unusual access patterns.","depth":23,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"Audit logs should go deeper. Current spec (what data, which system, when) is a start. Add: identity behind the key, specific queries/filters used, and failed access attempts (especially cross-visibility-boundary attempts). Enterprise compliance teams will expect this.","depth":23,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"Downgrade handling. Doc says Scale tier and above, but doesn't say what happens on downgrade. Keys should auto-deactivate.","depth":23,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"Happy to help draft a dedicated Security & Compliance section if useful.","depth":23,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"Galya Dimitrova","depth":23,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"15 Apr","depth":23,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"Thanks for the input @James Graham . I made the product related changes in the table and for the rest I left them as a note in the Technical section for the team to look at when they start looking at this.","depth":23,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"I wonder about your points related to GDPR. Currently multiple customers are using the Customer API/zapier to feed this data to AI and BI tools. They are also manually exporting transcripts and other information from the platform and feeding it to AI tools. I don’t get how MCP is so much different that all of these and why it will introduce new data processors (which are already being utilised) and would require any changes to the consent provided by participants.","depth":23,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXButton","text":"Expand","depth":21,"bounds":{"left":0.46991357,"top":0.19313647,"width":0.013297873,"height":0.031923383},"role_description":"button","subrole":"AXUnknown","is_enabled":true,"is_focused":false,"is_selected":false},{"role":"AXButton","text":"Listen","depth":22,"bounds":{"left":0.47523272,"top":0.3367917,"width":0.013297873,"height":0.031923383},"help_text":"","role_description":"button","subrole":"AXUnknown","is_enabled":true,"is_focused":false,"is_selected":false},{"role":"AXButton","text":"Show more options","depth":20,"bounds":{"left":0.47523272,"top":0.3312051,"width":0.013297873,"height":0.031923383},"role_description":"button","subrole":"AXUnknown","is_enabled":true,"is_focused":false,"is_selected":false}]...
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4479374102923647883
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-2099241112984464807
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idle
|
accessibility
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NULL
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Platform Sprint 2 Q2 - Platform Team - Scrum Board Platform Sprint 2 Q2 - Platform Team - Scrum Board - Jira
SevenShores\Hubspot\Exceptions\BadRequest: Client error: `POST [URL_WITH_CREDENTIALS] Graham . I made the product related changes in the table and for the rest I left them as a note in the Technical section for the team to look at when they start looking at this. I wonder about your points related to GDPR. Currently multiple customers are using the Customer API/zapier to feed this data to AI and BI tools. They are also manually exporting transcripts and other information from the platform and feeding it to AI tools. I don’t get how MCP is so much different that all of these and why it will introduce new data processors (which are already being utilised) and would require any changes to the consent provided by participants.
You said
Jiminny MCP Connector
Epic
Link to Epik in Jira
Document status
DRAFT
Objective
Enable customers to connect Jiminny data to external AI tools (Claude, OpenAI, Gemini) so it can be used as part of their broader knowledge base and workflows.
Position Jiminny as a data layer for AI-driven revenue workflows, not just a standalone product.
👤 Target user
Revenue teams using AI tools (Sales, CS, RevOps)
Companies already experimenting with Claude / OpenAI
Mid-market & Enterprise customers with multiple data sources (CRM, docs, CI tools, Support tools etc)
🤕 Pain point or problem
Jiminny data is locked in the platform
AI tools lack access to high-value conversation context
Customers must manually export/copy transcripts
No easy way to combine calls with CRM + docs + other info - using the Jiminny API is not suitable for non technical sales people
Peer pressure as almost all competitors have this
💥 Impact and benefits
For customers
Better AI outputs using real customer conversations
Ability to build automated workflows across tools
For Jiminny
Increased product stickiness (embedded in workflows)
Competitive parity with Gong / Avoma etc.
💡 Solution ideas
Build an AI Knowledge Connector (MCP-based) that:
Exposes Jiminny data (calls, transcripts, metadata) to AI tools
Provides structured insights (summaries, action items, scoring etc.)
Supports deal-level context
Allows integration into customer-owned AI stacks (Claude + Zapier, etc.)
Success metrics
List the key goals and how you will measure success. Include both qualitative and quantitative metrics (e.g., user adoption, retention rate, revenue targets).
Goal
Metric
Increase stickiness by ensuring Jiminny is embedded in the customer’s workflows
% of customers connecting external AI tools
Number of MCP/API calls per customer - and which ones are being used the most
Decrease the manual copying of transcripts
decrease by X %
User interaction and design
Simple setup flow:
Generate API key / connect MCP
Clear instructions for Claude / Zapier setup
Provide:
Example prompts for Claude
Pre-built workflow templates for Zapier
Clear documentation - with use cases
👉 Focus: usable by non-technical users
Detailed Requirements
List the functional and non-functional requirements. Prioritize them (e.g., High, Medium, Low) and add notes for clarification.
Requirement
Importance
Notes
Allow customers to connect Jiminny to their AI tools (e.g. Claude, OpenAI)
HIGH
Provide MCP endpoint so customers can easily integrate Jiminny into their AI stack
Allow customers to access call data through AI tools
HIGH
Expose Jiminny data:
list calls (filter by date, user, account, deal)
get call
get transcript (speaker-separated)
get call metadata
search calls (keyword + semantic)
Support filtering by:
account / contact/ lead / deal
jiminny user
date range
Allow customers to search and query calls using AI tools
HIGH
Support keyword and semantic search across conversations
Provide structured insights so customers can generate better outputs
HIGH
For each call, expose:
Summary
Action items
Key points
Activity type
Notes
Call Score
CRM information
Allow customers to understand deal status across multiple calls/emails
HIGH
For each deal expose:
calls/meetings/emails
Identified risks
contacts related to the deal with their job title
linked account details
all CRM field information that we have in DI + fields used for CRM filling
example - get_deal_summary
request -
{
"tool": "get_deal_summary",
"arguments": {
"deal_name": "ACME"
}
}
responce:
{
"deal_name": "ACME",
"stage": "Negotiation",
"recent_activity": [
"Demo call on 2026-04-01",
"Pricing discussion on 2026-04-03"
],
"risks": [
"Pricing concerns",
"Security review pending"
], "next_steps": [
"Send follow-up to VP Sales",
"Share security documentation"
]
}
Ensure the AI can easily understand the schema of the data coming from Jiminny
HIGH
Models perform much better when tools have:
clear names
rich descriptions
predictable schemas
Provide clear, actionable error states for customers when MCP connections fail
HIGH
Error messages should guide agents toward solutions with specific suggestions and next steps.
Expired or revoked key — “Error: Authentication failed. The API key used to access Jiminny has been revoked or has expired. Please ask your Jiminny admin to generate a new API key in Settings > Organization > General and reconnect the MCP server.”
Rate limit hit — “Error: Rate limit exceeded. Too many requests have been made to the Jiminny MCP server in a short period. Please wait 60 seconds before retrying.”
Permissions mismatch — if a user tries to access data outside their team visibility settings - “Error: Access denied. The requested call (call_id: [X]) is outside your team's visibility settings in Jiminny. Only calls within your permitted scope are accessible.”
Trying to access private meeting - “Error: Access denied. This meeting has been marked as private by the host and cannot be accessed through the MCP connector. Try requesting a different call or ask the meeting host to change the visibility settings in Jiminny.”
Downgraded/Capture account — if a customer's plan drops below Scale tier or the Customer is on Capture in the first place - “Error: MCP access unavailable. The Jiminny MCP connector is available on the Scale plan and above. Your account does not currently have an active Scale subscription.”
Jiminny-side outage — “Error:Jiminny is temporarily unavailable (status 503). This is not a data or permissions issue — please retry in a few minutes.”
No data found - “Error:No calls found matching your criteria. Try adjusting your filters — for example, widening the date range, removing the account filter, or checking the rep name is spelled correctly in Jiminny.”
Allow customers to securely control who and what data is accessible externally
HIGH
Ensure MCP only exposes data user has access to - based on team visibility settings. This means that if a user is not allow to access calls/deals in Jiminny UI then they shouldn’t be able to access those through the MCP as well.
Private meetings shouldn’t be exposed via MCP
HIGH
When a meetings is set to Private then the information about it shouldn’t be exposed through the MCP.
Ensure Jiminny data can be combined with other sources (e.g. CRM, docs) in AI workflows
HIGH
Ensure data is structured to be easily combined with:
CRM (accounts, deals)
external docs
Use consistent identifiers:
account IDs
deal IDs
MCP is available only for Scale tier and above
HIGH
Customers who are on Capture tier should be able to access any of their data through MCP.
This should also cover the scenario when a customer has been on Scale but then downgrades to Capture - their MCP access should stop working.
Provide visibility into how external AI tools access Jiminny data
HIGH
Audit logs:
what data was accessed by which external system when
identity - who made the request
specific queries/filters used
failed access attempts (especially cross-visibility-boundary attempts)
Admins should be able to access the logs from the org settings.We can start with a csv export before building a specific page for it.
example from Atlassian -
Provide customers with example prompts to get started quickly
HIGH
MCP prompts are explicitly defined as prompt templates that clients can discover and call with arguments.
See examples in table below.
Expose Jiminny as a Connector in Claude
medium
Competitors like Fathom are listed as Connectors in Claude. This will make it easier for customers to find us and to connect Jiminny
Provide customers with example workflows to get started quickly
medium
A workflow is usually multiple steps, maybe multiple tools, still focused on one outcome.
See examples in table below.
Allow customers to use predefined Jiminny skills for common workflows
medium
Anthropic describes Skills as folders that include instructions, scripts, and resources that Claude can load when relevant, and as a way to teach Claude repeatable workflows, preferences, and domain expertise once instead of re-explaining them every time. Skills - a reusable package of behavior that can include prompts, instructions, resources, and sometimes scripts/tools for a broader job.
Claude skills - https://resources.anthropic.com/hubfs/The-Complete-Guide-to-Building-Skill-for-Claude.pdf?hsLang=en&utm_source=chatgpt.com
See examples in table below.
Jiminny UI widget for OpenAI
medium
The reason to have this is to make certain Jiminny use cases much easier than pure chat.
Instead of ChatGPT only replying with text like “Here are the last 5 ACME calls,” it could also show a visual Jiminny card or mini-app inside the chat. That widget could list calls, show a deal summary, let the user filter by rep/date/account, open a transcript section, or save a snippet—while the conversation continues in normal chat alongside it.
For Jiminny, the best widget use cases are the ones where users need to browse or compare rather than ask one-off questions. A strong example is deal review: the user asks ChatGPT, “What is the status of the ACME deal?” ChatGPT calls your Jiminny MCP tools, and the widget shows a compact deal view with recent calls, risks, next steps, stakeholders, and links to transcripts/snippets. The chat can still summarize the answer in words, but the widget gives a clearer, scannable interface.
Another good Jiminny widget use case is call search and exploration. A text answer can say “I found 12 calls mentioning pricing objections,” but a widget could show a sortable list with date, rep, account, score, and objection count, then let the user click into one call to see the exact excerpt or jump to a transcript section.
Allow customers to run long-running analyses asynchronously and retrieve progress/results
low
Some requests/questions require analysis of Hugh volumes of data. For those, it may be better to:
start the job
let it run in the background
return a status like “in progress”
let the client come back for the result later
For example - User asks in Claude:
“Analyse all calls from this quarter and tell me the top 5 objections by segment.”
That might require:
searching lots of calls
pulling many summaries/transcripts
aggregating results
Instead of making Claude wait 45+ seconds, Jiminny could:
create an analysis job
return: job_id = 123, status = running
We need this in order to support:
large-scale analysis
multi-call aggregation across lots of data
playlist generation across many calls
heavy recap/report generation
Creating a snippet through the MCP
low
Create a shareable snippet from a call recording by specifying a time range. Useful for highlighting key moments — objection handling, pricing discussions, competitive mentions — and sharing them with your team.
example request:
{
"tool": "create_snippet",
"arguments": {
"call_id": "call_123",
"start_time": "00:18:24",
"end_time": "00:19:10",
"title": "Pricing objection"
}
}
example response:
{
"snippet_id": "snip_987",
"title": "Pricing objection",
"share_url": "https://app.jiminny.com/snippets/snip_987"
}
Ability to add recordings or snippets to a playlist
low
Allow customers to create libraries of calls automatically. They can use those for onboarding or other purposes
Allow AI tools to read reusable Jiminny resources
low
fathom
Resources are useful for data that should be read consistently rather than recomputed every time. In Jiminny terms, that could be:
current deal snapshot
account summary
weekly rep recap
approved talk tracks / objection handling guidance
curated playlists or snippet libraries
This is useful because an AI can consume these directly as context, instead of repeatedly stitching together many tool calls.
Ability to write coaching notes in Jiminny through MCP
low
What we want to do for prompts/worflows and skills
Capability
Type
User value / job to be done
Example Jiminny use case
Inputs
Steps performed
Output
Draft follow-up email
Prompt
Help reps quickly create tailored follow-ups after calls
Use the latest customer call to draft an email with recap and next steps
Call ID
optional tone
optional recipient type
Retrieve call summary and action items from Jiminny.
Pull key points, commitments, and next steps.
Apply the chosen tone and structure.
Draft the email in a consistent format.
Customer-ready follow-up email draft
Summarise call
Prompt
Help users quickly extract the most important points from a conversation
Generate a concise summary of one call for internal or external use
Call ID
optional summary style
optional audience
Retrieve transcript, metadata, and structured insights.
Identify key topics, decisions, risks, and next steps.
Format output for the chosen audience.
Short or structured call summary with actions and risks
Generate deal recap
Prompt
Help reps and managers get a fast overview of a deal
Summarise the current state of a deal based on recent calls and linked CRM context
Deal ID or account name
optional date range
Retrieve calls and meetings linked to the deal.
Pull deal metadata and CRM-linked context.
Identify recent changes, blockers, risks, and next steps.
Summarise into a concise recap.
Deal recap with status, blockers, risks, and recommended next steps
Prepare weekly recap
Prompt
Help managers or reps review what changed over a time period
Weekly recap of calls, themes, and actions for one rep, team, or account
Rep ID
team ID or account ID
time period
Retrieve relevant calls and summaries for the selected time period.
Aggregate themes, action items, and changes.
Highlight notable risks, opportunities, and follow-ups.
Weekly recap with top themes, risks, opportunities, and actions
Prepare deal review
Workflow
Help reps and managers review deal status using multiple sources of context
Review a deal before pipeline review or forecast meeting
Deal ID
optional date range
Retrieve all recent calls, emails, and meetings tied to the deal.
Pull structured call summaries, score, action items, and key points.
Pull linked CRM context such as stage, contacts, and account details.
Aggregate open risks, unresolved objections, stakeholder gaps, and next steps.
Format into a review-ready structure.
Deal review document with current status, risks, stakeholders, blockers, and next steps
Weekly team recap
Workflow
Help managers monitor activity and risk across a group of reps or accounts
End-of-week team summary for sales leadership
Team ID
date range
Retrieve calls and structured insights across the team.
Group by rep, account, or deal.
Identify recurring themes, major risks, strong calls, and missed follow-ups.
Highlight calls or deals that need attention.
Team-level recap with patterns, key risks, notable wins, and action areas
Objection analysis across calls
Workflow
Help teams identify patterns across multiple conversations
Analyse pricing or competitor objections across recent calls
Account ID
deal ID
rep ID
keyword/topic
date range
Search calls matching the topic or keyword.
Retrieve summaries, transcripts, and snippets where relevant.
Identify recurring objections and how they were handled.
Assess whether objections were resolved or remain open.
Summarise patterns and examples.
Objection analysis with themes, frequency, examples, and suggested follow-up actions
Build onboarding playlist
Workflow
Help enablement teams curate useful learning content faster
Build a playlist of strong discovery, demo, or pricing calls for new hires
Topic
call type
rep/team filter
optional time period
Search for calls matching the selected criteria.
Rank or filter calls based on score, topics, or key moments.
Identify useful snippets or full recordings.
Add selected calls/snippets into a playlist structure.
Generate short descriptions for each item.
Curated onboarding playlist with selected calls/snippets and descriptions
Deal Inspection Skill
Skill
Give users a consistent, opinionated way to assess a deal
Claude reviews a deal using a repeatable Jiminny methodology
Deal ID or account name
optional review scope
Determine whether the request is suitable for a deal inspection.
Retrieve relevant calls, summaries, CRM context, stakeholders, and risks.
Apply a standard Jiminny review framework to assess deal health.
Look for missing next steps, unresolved objections, stakeholder gaps, and warning signs.
Present findings in a consistent structure with recommended actions.
Structured deal inspection with health assessment, red flags, and recommendations
Manager Coaching Skill
Skill
Help managers review calls consistently and identify coaching moments
Analyse a rep’s call and surface strengths, gaps, and examples for coaching
Call ID
optional rep ID
optional coaching focus
Retrieve transcript, score, summary, and key moments from the call.
Evaluate the conversation against a coaching framework.
Identify what went well and where the rep could improve.
Suggest moments to clip as snippets.
Recommend coaching actions or playlist additions.
Coaching review with strengths, gaps, snippet suggestions, and recommended coaching actions
CSM / QBR Prep Skill
Skill
Help CS or AM teams prepare structured customer reviews from conversations
Generate an account review or QBR-style summary from recent customer interactions
Account ID, optional time period
Retrieve all recent calls, emails, and account-linked context.
Aggregate themes, requests, blockers, sentiment shifts, and opportunities.
Apply a repeatable account review structure.
Summarise outcomes, open issues, and suggested next steps.
Structured QBR/account review summary with themes, risks, opportunities, and actions
Snippet Builder Skill
Skill
Help users consistently capture and label useful moments from calls
Identify useful moments in a call and convert them into reusable snippets
Call ID, optional focus area such as pricing, objection, competitor, discovery
Retrieve transcript, recording timeline, and call insights.
Detect moments matching the requested focus area.
Propose snippet start/end times and titles.
Tag snippets by type or theme.
Optionally save them or add them to a playlist.
One or more proposed or saved snippets with title, timing, and tags
💡 Technical details
Auth model needs specifying. Are API keys scoped per user, per team, or per Jiminny instance? If a key is generated by an admin, does it inherit their visibility level, or provide org-wide? Are permissions evaluated at query time or frozen at key creation? Needs to be query-time, otherwise permission changes won't propagate.
Key lifecycle management is missing. No mention of rotation, expiry, or revocation. A departed employee's active key is a data leak. Need: revocation, optional expiry, alerts on stale keys, and consider whether keys should be tied to service accounts rather than personal users.
Rate limiting should be HIGH. A compromised key or misconfigured automation could bulk-export an entire customer's call history. Need per-key rate limits and anomaly detection on unusual access patterns.
Open Questions
Track unresolved issues or decisions that need to be made. Update as answers become available.
Question
Answer
Date Answered
Competitor research
Competitor
MCP Availability
Core Capabilities
Advanced Capabilities
Positioning
Key Strength
Key Weakness
Gong
✅ Mature MCP
List/search calls
Get transcripts
get Call metadata
Deal intelligence
Scorecards, analytics
CRM context
Enterprise data layer
Deep data + ecosystem integrations
Limited opinionated AI workflows
Avoma
✅ Mature MCP
list_meetings
get_meeting
get_transcript
key topics
Deal fields/Deal level analysis
Coaching/Scoring
CRM context
pushing insights into Notion / Confluence
AI-ready meeting intelligence
Strongest “outputs” layer
Mostly pull-based interactions
Fathom
✅ MCP
list/search meetings
get transcript
get summary/action items
Team/org context
Webhooks (event-based triggers)
get_weekly_recap
aggregated action items across meetings
creating webhooks directly from the MCP server
Lightweight meeting data access
Includes summaries + actions
Limited analytics depth
Grain
✅ Basic MCP
get meetings
download transcripts
Notes
Deals
Scorecards
Data access utility
Simple + accessible
Low sophistication, sometimes browser-based
Outreach
⚠️ MCP (workflow-focused)
Search sequences
Emails
Meetings (Kaia)
account / prospect / opportunity lookups
Workflow automation
Multi-system orchestration
Revenue workflow engine
End-to-end GTM workflows
Less depth in conversation data
Attention
⚠️ Emerging MCP
Meeting data
Transcripts
CRM-linked context
AI insights
Sales assistant workflows
create snippets
AI sales assistant + CRM
Strong CRM linkage
Less focus on external knowledge layer
Planhat -
Related content
Ask Jiminny Anything on Call level
Galya Dimitrova
Hubspot app
Galya Dimitrova
Product Vision & Strategy
Galya Dimitrova
Automated CRM Filling
Simona Georgieva (Deactivated)
Competitive analysis
Galya Dimitrova
AI agent ideas
Steliyan Georgiev
Comments
James Graham
9 Apr
A few areas around Security & Compliance that need more depth before this moves beyond draft:
Auth model needs specifying. Are API keys scoped per user, per team, or per Jiminny instance? If a key is generated by an admin, does it inherit their visibility level, or provide org-wide? Are permissions evaluated at query time or frozen at key creation? Needs to be query-time, otherwise permission changes won't propagate.
Team visibility enforcement should be its own HIGH requirement. The current note under access control ("ensure MCP only exposes data user has access to") is doing too much work as a single line. Every MCP tool response (especially search_calls and deal-level aggregations) must be filtered through the same visibility engine as the UI. Semantic search is the riskiest here; it could surface results across team boundaries if not properly scoped.
No data minimisation or scoping controls. We're exposing transcripts, CRM fields, contact details with job titles, deal context - significant PII and commercial data leaving the platform. Can customers configure which data types are exposed? Can transcripts be PII-stripped before they leave Jiminny? Given we position GDPR consent as a differentiator, we should be thinking about this.
GDPR downstream processing is unaddressed. Piping transcripts to OpenAI/Gemini introduces new data processors. Customers need to acknowledge responsibility for downstream processing during setup. We should also consider whether call participants' recording consent covers onward sharing to third-party AI - it almost certainly doesn't by default. This is one for me to pick up.
Key lifecycle management is missing. No mention of rotation, expiry, or revocation. A departed employee's active key is a data leak. Need: revocation, optional expiry, alerts on stale keys, and consider whether keys should be tied to service accounts rather than personal users.
Rate limiting should be HIGH. A compromised key or misconfigured automation could bulk-export an entire customer's call history. Need per-key rate limits and anomaly detection on unusual ac...
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Platform Sprint 2 Q2 - Platform Team - Scrum Board Platform Sprint 2 Q2 - Platform Team - Scrum Board - Jira
SevenShores\Hubspot\Exceptions\BadRequest: Client error: `POST [URL_WITH_CREDENTIALS] Graham . I made the product related changes in the table and for the rest I left them as a note in the Technical section for the team to look at when they start looking at this. I wonder about your points related to GDPR. Currently multiple customers are using the Customer API/zapier to feed this data to AI and BI tools. They are also manually exporting transcripts and other information from the platform and feeding it to AI tools. I don’t get how MCP is so much different that all of these and why it will introduce new data processors (which are already being utilised) and would require any changes to the consent provided by participants.
You said
Jiminny MCP Connector
Epic
Link to Epik in Jira
Document status
DRAFT
Objective
Enable customers to connect Jiminny data to external AI tools (Claude, OpenAI, Gemini) so it can be used as part of their broader knowledge base and workflows.
Position Jiminny as a data layer for AI-driven revenue workflows, not just a standalone product.
👤 Target user
Revenue teams using AI tools (Sales, CS, RevOps)
Companies already experimenting with Claude / OpenAI
Mid-market & Enterprise customers with multiple data sources (CRM, docs, CI tools, Support tools etc)
🤕 Pain point or problem
Jiminny data is locked in the platform
AI tools lack access to high-value conversation context
Customers must manually export/copy transcripts
No easy way to combine calls with CRM + docs + other info - using the Jiminny API is not suitable for non technical sales people
Peer pressure as almost all competitors have this
💥 Impact and benefits
For customers
Better AI outputs using real customer conversations
Ability to build automated workflows across tools
For Jiminny
Increased product stickiness (embedded in workflows)
Competitive parity with Gong / Avoma etc.
💡 Solution ideas
Build an AI Knowledge Connector (MCP-based) that:
Exposes Jiminny data (calls, transcripts, metadata) to AI tools
Provides structured insights (summaries, action items, scoring etc.)
Supports deal-level context
Allows integration into customer-owned AI stacks (Claude + Zapier, etc.)
Success metrics
List the key goals and how you will measure success. Include both qualitative and quantitative metrics (e.g., user adoption, retention rate, revenue targets).
Goal
Metric
Increase stickiness by ensuring Jiminny is embedded in the customer’s workflows
% of customers connecting external AI tools
Number of MCP/API calls per customer - and which ones are being used the most
Decrease the manual copying of transcripts
decrease by X %
User interaction and design
Simple setup flow:
Generate API key / connect MCP
Clear instructions for Claude / Zapier setup
Provide:
Example prompts for Claude
Pre-built workflow templates for Zapier
Clear documentation - with use cases
👉 Focus: usable by non-technical users
Detailed Requirements
List the functional and non-functional requirements. Prioritize them (e.g., High, Medium, Low) and add notes for clarification.
Requirement
Importance
Notes
Allow customers to connect Jiminny to their AI tools (e.g. Claude, OpenAI)
HIGH
Provide MCP endpoint so customers can easily integrate Jiminny into their AI stack
Allow customers to access call data through AI tools
HIGH
Expose Jiminny data:
list calls (filter by date, user, account, deal)
get call
get transcript (speaker-separated)
get call metadata
search calls (keyword + semantic)
Support filtering by:
account / contact/ lead / deal
jiminny user
date range
Allow customers to search and query calls using AI tools
HIGH
Support keyword and semantic search across conversations
Provide structured insights so customers can generate better outputs
HIGH
For each call, expose:
Summary
Action items
Key points
Activity type
Notes
Call Score
CRM information
Allow customers to understand deal status across multiple calls/emails
HIGH
For each deal expose:
calls/meetings/emails
Identified risks
contacts related to the deal with their job title
linked account details
all CRM field information that we have in DI + fields used for CRM filling
example - get_deal_summary
request -
{
"tool": "get_deal_summary",
"arguments": {
"deal_name": "ACME"
}
}
responce:
{
"deal_name": "ACME",
"stage": "Negotiation",
"recent_activity": [
"Demo call on 2026-04-01",
"Pricing discussion on 2026-04-03"
],
"risks": [
"Pricing concerns",
"Security review pending"
], "next_steps": [
"Send follow-up to VP Sales",
"Share security documentation"
]
}
Ensure the AI can easily understand the schema of the data coming from Jiminny
HIGH
Models perform much better when tools have:
clear names
rich descriptions
predictable schemas
Provide clear, actionable error states for customers when MCP connections fail
HIGH
Error messages should guide agents toward solutions with specific suggestions and next steps.
Expired or revoked key — “Error: Authentication failed. The API key used to access Jiminny has been revoked or has expired. Please ask your Jiminny admin to generate a new API key in Settings > Organization > General and reconnect the MCP server.”
Rate limit hit — “Error: Rate limit exceeded. Too many requests have been made to the Jiminny MCP server in a short period. Please wait 60 seconds before retrying.”
Permissions mismatch — if a user tries to access data outside their team visibility settings - “Error: Access denied. The requested call (call_id: [X]) is outside your team's visibility settings in Jiminny. Only calls within your permitted scope are accessible.”
Trying to access private meeting - “Error: Access denied. This meeting has been marked as private by the host and cannot be accessed through the MCP connector. Try requesting a different call or ask the meeting host to change the visibility settings in Jiminny.”
Downgraded/Capture account — if a customer's plan drops below Scale tier or the Customer is on Capture in the first place - “Error: MCP access unavailable. The Jiminny MCP connector is available on the Scale plan and above. Your account does not currently have an active Scale subscription.”
Jiminny-side outage — “Error:Jiminny is temporarily unavailable (status 503). This is not a data or permissions issue — please retry in a few minutes.”
No data found - “Error:No calls found matching your criteria. Try adjusting your filters — for example, widening the date range, removing the account filter, or checking the rep name is spelled correctly in Jiminny.”
Allow customers to securely control who and what data is accessible externally
HIGH
Ensure MCP only exposes data user has access to - based on team visibility settings. This means that if a user is not allow to access calls/deals in Jiminny UI then they shouldn’t be able to access those through the MCP as well.
Private meetings shouldn’t be exposed via MCP
HIGH
When a meetings is set to Private then the information about it shouldn’t be exposed through the MCP.
Ensure Jiminny data can be combined with other sources (e.g. CRM, docs) in AI workflows
HIGH
Ensure data is structured to be easily combined with:
CRM (accounts, deals)
external docs
Use consistent identifiers:
account IDs
deal IDs
MCP is available only for Scale tier and above
HIGH
Customers who are on Capture tier should be able to access any of their data through MCP.
This should also cover the scenario when a customer has been on Scale but then downgrades to Capture - their MCP access should stop working.
Provide visibility into how external AI tools access Jiminny data
HIGH
Audit logs:
what data was accessed by which external system when
identity - who made the request
specific queries/filters used
failed access attempts (especially cross-visibility-boundary attempts)
Admins should be able to access the logs from the org settings.We can start with a csv export before building a specific page for it.
example from Atlassian -
Provide customers with example prompts to get started quickly
HIGH
MCP prompts are explicitly defined as prompt templates that clients can discover and call with arguments.
See examples in table below.
Expose Jiminny as a Connector in Claude
medium
Competitors like Fathom are listed as Connectors in Claude. This will make it easier for customers to find us and to connect Jiminny
Provide customers with example workflows to get started quickly
medium
A workflow is usually multiple steps, maybe multiple tools, still focused on one outcome.
See examples in table below.
Allow customers to use predefined Jiminny skills for common workflows
medium
Anthropic describes Skills as folders that include instructions, scripts, and resources that Claude can load when relevant, and as a way to teach Claude repeatable workflows, preferences, and domain expertise once instead of re-explaining them every time. Skills - a reusable package of behavior that can include prompts, instructions, resources, and sometimes scripts/tools for a broader job.
Claude skills - https://resources.anthropic.com/hubfs/The-Complete-Guide-to-Building-Skill-for-Claude.pdf?hsLang=en&utm_source=chatgpt.com
See examples in table below.
Jiminny UI widget for OpenAI
medium
The reason to have this is to make certain Jiminny use cases much easier than pure chat.
Instead of ChatGPT only replying with text like “Here are the last 5 ACME calls,” it could also show a visual Jiminny card or mini-app inside the chat. That widget could list calls, show a deal summary, let the user filter by rep/date/account, open a transcript section, or save a snippet—while the conversation continues in normal chat alongside it.
For Jiminny, the best widget use cases are the ones where users need to browse or compare rather than ask one-off questions. A strong example is deal review: the user asks ChatGPT, “What is the status of the ACME deal?” ChatGPT calls your Jiminny MCP tools, and the widget shows a compact deal view with recent calls, risks, next steps, stakeholders, and links to transcripts/snippets. The chat can still summarize the answer in words, but the widget gives a clearer, scannable interface.
Another good Jiminny widget use case is call search and exploration. A text answer can say “I found 12 calls mentioning pricing objections,” but a widget could show a sortable list with date, rep, account, score, and objection count, then let the user click into one call to see the exact excerpt or jump to a transcript section.
Allow customers to run long-running analyses asynchronously and retrieve progress/results
low
Some requests/questions require analysis of Hugh volumes of data. For those, it may be better to:
start the job
let it run in the background
return a status like “in progress”
let the client come back for the result later
For example - User asks in Claude:
“Analyse all calls from this quarter and tell me the top 5 objections by segment.”
That might require:
searching lots of calls
pulling many summaries/transcripts
aggregating results
Instead of making Claude wait 45+ seconds, Jiminny could:
create an analysis job
return: job_id = 123, status = running
We need this in order to support:
large-scale analysis
multi-call aggregation across lots of data
playlist generation across many calls
heavy recap/report generation
Creating a snippet through the MCP
low
Create a shareable snippet from a call recording by specifying a time range. Useful for highlighting key moments — objection handling, pricing discussions, competitive mentions — and sharing them with your team.
example request:
{
"tool": "create_snippet",
"arguments": {
"call_id": "call_123",
"start_time": "00:18:24",
"end_time": "00:19:10",
"title": "Pricing objection"
}
}
example response:
{
"snippet_id": "snip_987",
"title": "Pricing objection",
"share_url": "https://app.jiminny.com/snippets/snip_987"
}
Ability to add recordings or snippets to a playlist
low
Allow customers to create libraries of calls automatically. They can use those for onboarding or other purposes
Allow AI tools to read reusable Jiminny resources
low
fathom
Resources are useful for data that should be read consistently rather than recomputed every time. In Jiminny terms, that could be:
current deal snapshot
account summary
weekly rep recap
approved talk tracks / objection handling guidance
curated playlists or snippet libraries
This is useful because an AI can consume these directly as context, instead of repeatedly stitching together many tool calls.
Ability to write coaching notes in Jiminny through MCP
low
What we want to do for prompts/worflows and skills
Capability
Type
User value / job to be done
Example Jiminny use case
Inputs
Steps performed
Output
Draft follow-up email
Prompt
Help reps quickly create tailored follow-ups after calls
Use the latest customer call to draft an email with recap and next steps
Call ID
optional tone
optional recipient type
Retrieve call summary and action items from Jiminny.
Pull key points, commitments, and next steps.
Apply the chosen tone and structure.
Draft the email in a consistent format.
Customer-ready follow-up email draft
Summarise call
Prompt
Help users quickly extract the most important points from a conversation
Generate a concise summary of one call for internal or external use
Call ID
optional summary style
optional audience
Retrieve transcript, metadata, and structured insights.
Identify key topics, decisions, risks, and next steps.
Format output for the chosen audience.
Short or structured call summary with actions and risks
Generate deal recap
Prompt
Help reps and managers get a fast overview of a deal
Summarise the current state of a deal based on recent calls and linked CRM context
Deal ID or account name
optional date range
Retrieve calls and meetings linked to the deal.
Pull deal metadata and CRM-linked context.
Identify recent changes, blockers, risks, and next steps.
Summarise into a concise recap.
Deal recap with status, blockers, risks, and recommended next steps
Prepare weekly recap
Prompt
Help managers or reps review what changed over a time period
Weekly recap of calls, themes, and actions for one rep, team, or account
Rep ID
team ID or account ID
time period
Retrieve relevant calls and summaries for the selected time period.
Aggregate themes, action items, and changes.
Highlight notable risks, opportunities, and follow-ups.
Weekly recap with top themes, risks, opportunities, and actions
Prepare deal review
Workflow
Help reps and managers review deal status using multiple sources of context
Review a deal before pipeline review or forecast meeting
Deal ID
optional date range
Retrieve all recent calls, emails, and meetings tied to the deal.
Pull structured call summaries, score, action items, and key points.
Pull linked CRM context such as stage, contacts, and account details.
Aggregate open risks, unresolved objections, stakeholder gaps, and next steps.
Format into a review-ready structure.
Deal review document with current status, risks, stakeholders, blockers, and next steps
Weekly team recap
Workflow
Help managers monitor activity and risk across a group of reps or accounts
End-of-week team summary for sales leadership
Team ID
date range
Retrieve calls and structured insights across the team.
Group by rep, account, or deal.
Identify recurring themes, major risks, strong calls, and missed follow-ups.
Highlight calls or deals that need attention.
Team-level recap with patterns, key risks, notable wins, and action areas
Objection analysis across calls
Workflow
Help teams identify patterns across multiple conversations
Analyse pricing or competitor objections across recent calls
Account ID
deal ID
rep ID
keyword/topic
date range
Search calls matching the topic or keyword.
Retrieve summaries, transcripts, and snippets where relevant.
Identify recurring objections and how they were handled.
Assess whether objections were resolved or remain open.
Summarise patterns and examples.
Objection analysis with themes, frequency, examples, and suggested follow-up actions
Build onboarding playlist
Workflow
Help enablement teams curate useful learning content faster
Build a playlist of strong discovery, demo, or pricing calls for new hires
Topic
call type
rep/team filter
optional time period
Search for calls matching the selected criteria.
Rank or filter calls based on score, topics, or key moments.
Identify useful snippets or full recordings.
Add selected calls/snippets into a playlist structure.
Generate short descriptions for each item.
Curated onboarding playlist with selected calls/snippets and descriptions
Deal Inspection Skill
Skill
Give users a consistent, opinionated way to assess a deal
Claude reviews a deal using a repeatable Jiminny methodology
Deal ID or account name
optional review scope
Determine whether the request is suitable for a deal inspection.
Retrieve relevant calls, summaries, CRM context, stakeholders, and risks.
Apply a standard Jiminny review framework to assess deal health.
Look for missing next steps, unresolved objections, stakeholder gaps, and warning signs.
Present findings in a consistent structure with recommended actions.
Structured deal inspection with health assessment, red flags, and recommendations
Manager Coaching Skill
Skill
Help managers review calls consistently and identify coaching moments
Analyse a rep’s call and surface strengths, gaps, and examples for coaching
Call ID
optional rep ID
optional coaching focus
Retrieve transcript, score, summary, and key moments from the call.
Evaluate the conversation against a coaching framework.
Identify what went well and where the rep could improve.
Suggest moments to clip as snippets.
Recommend coaching actions or playlist additions.
Coaching review with strengths, gaps, snippet suggestions, and recommended coaching actions
CSM / QBR Prep Skill
Skill
Help CS or AM teams prepare structured customer reviews from conversations
Generate an account review or QBR-style summary from recent customer interactions
Account ID, optional time period
Retrieve all recent calls, emails, and account-linked context.
Aggregate themes, requests, blockers, sentiment shifts, and opportunities.
Apply a repeatable account review structure.
Summarise outcomes, open issues, and suggested next steps.
Structured QBR/account review summary with themes, risks, opportunities, and actions
Snippet Builder Skill
Skill
Help users consistently capture and label useful moments from calls
Identify useful moments in a call and convert them into reusable snippets
Call ID, optional focus area such as pricing, objection, competitor, discovery
Retrieve transcript, recording timeline, and call insights.
Detect moments matching the requested focus area.
Propose snippet start/end times and titles.
Tag snippets by type or theme.
Optionally save them or add them to a playlist.
One or more proposed or saved snippets with title, timing, and tags
💡 Technical details
Auth model needs specifying. Are API keys scoped per user, per team, or per Jiminny instance? If a key is generated by an admin, does it inherit their visibility level, or provide org-wide? Are permissions evaluated at query time or frozen at key creation? Needs to be query-time, otherwise permission changes won't propagate.
Key lifecycle management is missing. No mention of rotation, expiry, or revocation. A departed employee's active key is a data leak. Need: revocation, optional expiry, alerts on stale keys, and consider whether keys should be tied to service accounts rather than personal users.
Rate limiting should be HIGH. A compromised key or misconfigured automation could bulk-export an entire customer's call history. Need per-key rate limits and anomaly detection on unusual access patterns.
Open Questions
Track unresolved issues or decisions that need to be made. Update as answers become available.
Question
Answer
Date Answered
Competitor research
Competitor
MCP Availability
Core Capabilities
Advanced Capabilities
Positioning
Key Strength
Key Weakness
Gong
✅ Mature MCP
List/search calls
Get transcripts
get Call metadata
Deal intelligence
Scorecards, analytics
CRM context
Enterprise data layer
Deep data + ecosystem integrations
Limited opinionated AI workflows
Avoma
✅ Mature MCP
list_meetings
get_meeting
get_transcript
key topics
Deal fields/Deal level analysis
Coaching/Scoring
CRM context
pushing insights into Notion / Confluence
AI-ready meeting intelligence
Strongest “outputs” layer
Mostly pull-based interactions
Fathom
✅ MCP
list/search meetings
get transcript
get summary/action items
Team/org context
Webhooks (event-based triggers)
get_weekly_recap
aggregated action items across meetings
creating webhooks directly from the MCP server
Lightweight meeting data access
Includes summaries + actions
Limited analytics depth
Grain
✅ Basic MCP
get meetings
download transcripts
Notes
Deals
Scorecards
Data access utility
Simple + accessible
Low sophistication, sometimes browser-based
Outreach
⚠️ MCP (workflow-focused)
Search sequences
Emails
Meetings (Kaia)
account / prospect / opportunity lookups
Workflow automation
Multi-system orchestration
Revenue workflow engine
End-to-end GTM workflows
Less depth in conversation data
Attention
⚠️ Emerging MCP
Meeting data
Transcripts
CRM-linked context
AI insights
Sales assistant workflows
create snippets
AI sales assistant + CRM
Strong CRM linkage
Less focus on external knowledge layer
Planhat -
Related content
Ask Jiminny Anything on Call level
Galya Dimitrova
Hubspot app
Galya Dimitrova
Product Vision & Strategy
Galya Dimitrova
Automated CRM Filling
Simona Georgieva (Deactivated)
Competitive analysis
Galya Dimitrova
AI agent ideas
Steliyan Georgiev
Comments
James Graham
9 Apr
A few areas around Security & Compliance that need more depth before this moves beyond draft:
Auth model needs specifying. Are API keys scoped per user, per team, or per Jiminny instance? If a key is generated by an admin, does it inherit their visibility level, or provide org-wide? Are permissions evaluated at query time or frozen at key creation? Needs to be query-time, otherwise permission changes won't propagate.
Team visibility enforcement should be its own HIGH requirement. The current note under access control ("ensure MCP only exposes data user has access to") is doing too much work as a single line. Every MCP tool response (especially search_calls and deal-level aggregations) must be filtered through the same visibility engine as the UI. Semantic search is the riskiest here; it could surface results across team boundaries if not properly scoped.
No data minimisation or scoping controls. We're exposing transcripts, CRM fields, contact details with job titles, deal context - significant PII and commercial data leaving the platform. Can customers configure which data types are exposed? Can transcripts be PII-stripped before they leave Jiminny? Given we position GDPR consent as a differentiator, we should be thinking about this.
GDPR downstream processing is unaddressed. Piping transcripts to OpenAI/Gemini introduces new data processors. Customers need to acknowledge responsibility for downstream processing during setup. We should also consider whether call participants' recording consent covers onward sharing to third-party AI - it almost certainly doesn't by default. This is one for me to pick up.
Key lifecycle management is missing. No mention of rotation, expiry, or revocation. A departed employee's active key is a data leak. Need: revocation, optional expiry, alerts on stale keys, and consider whether keys should be tied to service accounts rather than personal users.
Rate limiting should be HIGH. A compromised key or misconfigured automation could bulk-export an entire customer's call history. Need per-key rate limits and anomaly detection on unusual ac...
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Position Jiminny as a data layer for AI-driven revenue workflows, not just a standalone product. 👤 Target user Revenue teams using AI tools (Sales, CS, RevOps) Companies already experimenting with Claude / OpenAI Mid-market & Enterprise customers with multiple data sources (CRM, docs, CI tools, Support tools etc) 🤕 Pain point or problem Jiminny data is locked in the platform AI tools lack access to high-value conversation context Customers must manually export/copy transcripts No easy way to combine calls with CRM + docs + other info - using the Jiminny API is not suitable for non technical sales people Peer pressure as almost all competitors have this 💥 Impact and benefits For customers Better AI outputs using real customer conversations Ability to build automated workflows across tools For Jiminny Increased product stickiness (embedded in workflows) Competitive parity with Gong / Avoma etc. 💡 Solution ideas Build an AI Knowledge Connector (MCP-based) that: Exposes Jiminny data (calls, transcripts, metadata) to AI tools Provides structured insights (summaries, action items, scoring etc.) Supports deal-level context Allows integration into customer-owned AI stacks (Claude + Zapier, etc.) Success metrics List the key goals and how you will measure success. Include both qualitative and quantitative metrics (e.g., user adoption, retention rate, revenue targets). Goal Metric Increase stickiness by ensuring Jiminny is embedded in the customer’s workflows % of customers connecting external AI tools Number of MCP/API calls per customer - and which ones are being used the most Decrease the manual copying of transcripts decrease by X % User interaction and design Simple setup flow: Generate API key / connect MCP Clear instructions for Claude / Zapier setup Provide: Example prompts for Claude Pre-built workflow templates for Zapier Clear documentation - with use cases 👉 Focus: usable by non-technical users Detailed Requirements List the functional and non-functional requirements. Prioritize them (e.g., High, Medium, Low) and add notes for clarification. Requirement Importance Notes Allow customers to connect Jiminny to their AI tools (e.g. Claude, OpenAI) HIGH Provide MCP endpoint so customers can easily integrate Jiminny into their AI stack Allow customers to access call data through AI tools HIGH Expose Jiminny data: list calls (filter by date, user, account, deal) get call get transcript (speaker-separated) get call metadata search calls (keyword + semantic) Support filtering by: account / contact/ lead / deal jiminny user date range Allow customers to search and query calls using AI tools HIGH Support keyword and semantic search across conversations Provide structured insights so customers can generate better outputs HIGH For each call, expose: Summary Action items Key points Activity type Notes Call Score CRM information Allow customers to understand deal status across multiple calls/emails HIGH For each deal expose: calls/meetings/emails Identified risks contacts related to the deal with their job title linked account details all CRM field information that we have in DI + fields used for CRM filling example - get_deal_summary request - { \"tool\": \"get_deal_summary\", \"arguments\": { \"deal_name\": \"ACME\" } } responce: { \"deal_name\": \"ACME\", \"stage\": \"Negotiation\", \"recent_activity\": [ \"Demo call on 2026-04-01\", \"Pricing discussion on 2026-04-03\" ], \"risks\": [ \"Pricing concerns\", \"Security review pending\" ], \"next_steps\": [ \"Send follow-up to VP Sales\", \"Share security documentation\" ] } Ensure the AI can easily understand the schema of the data coming from Jiminny HIGH Models perform much better when tools have: clear names rich descriptions predictable schemas Provide clear, actionable error states for customers when MCP connections fail HIGH Error messages should guide agents toward solutions with specific suggestions and next steps. Expired or revoked key — “Error: Authentication failed. The API key used to access Jiminny has been revoked or has expired. Please ask your Jiminny admin to generate a new API key in Settings > Organization > General and reconnect the MCP server.” Rate limit hit — “Error: Rate limit exceeded. Too many requests have been made to the Jiminny MCP server in a short period. Please wait 60 seconds before retrying.” Permissions mismatch — if a user tries to access data outside their team visibility settings - “Error: Access denied. The requested call (call_id: [X]) is outside your team's visibility settings in Jiminny. Only calls within your permitted scope are accessible.” Trying to access private meeting - “Error: Access denied. This meeting has been marked as private by the host and cannot be accessed through the MCP connector. Try requesting a different call or ask the meeting host to change the visibility settings in Jiminny.” Downgraded/Capture account — if a customer's plan drops below Scale tier or the Customer is on Capture in the first place - “Error: MCP access unavailable. The Jiminny MCP connector is available on the Scale plan and above. Your account does not currently have an active Scale subscription.” Jiminny-side outage — “Error:Jiminny is temporarily unavailable (status 503). This is not a data or permissions issue — please retry in a few minutes.” No data found - “Error:No calls found matching your criteria. Try adjusting your filters — for example, widening the date range, removing the account filter, or checking the rep name is spelled correctly in Jiminny.” Allow customers to securely control who and what data is accessible externally HIGH Ensure MCP only exposes data user has access to - based on team visibility settings. This means that if a user is not allow to access calls/deals in Jiminny UI then they shouldn’t be able to access those through the MCP as well. Private meetings shouldn’t be exposed via MCP HIGH When a meetings is set to Private then the information about it shouldn’t be exposed through the MCP. Ensure Jiminny data can be combined with other sources (e.g. CRM, docs) in AI workflows HIGH Ensure data is structured to be easily combined with: CRM (accounts, deals) external docs Use consistent identifiers: account IDs deal IDs MCP is available only for Scale tier and above HIGH Customers who are on Capture tier should be able to access any of their data through MCP. This should also cover the scenario when a customer has been on Scale but then downgrades to Capture - their MCP access should stop working. Provide visibility into how external AI tools access Jiminny data HIGH Audit logs: what data was accessed by which external system when identity - who made the request specific queries/filters used failed access attempts (especially cross-visibility-boundary attempts) Admins should be able to access the logs from the org settings.We can start with a csv export before building a specific page for it. example from Atlassian - Provide customers with example prompts to get started quickly HIGH MCP prompts are explicitly defined as prompt templates that clients can discover and call with arguments. See examples in table below. Expose Jiminny as a Connector in Claude medium Competitors like Fathom are listed as Connectors in Claude. This will make it easier for customers to find us and to connect Jiminny Provide customers with example workflows to get started quickly medium A workflow is usually multiple steps, maybe multiple tools, still focused on one outcome. See examples in table below. Allow customers to use predefined Jiminny skills for common workflows medium Anthropic describes Skills as folders that include instructions, scripts, and resources that Claude can load when relevant, and as a way to teach Claude repeatable workflows, preferences, and domain expertise once instead of re-explaining them every time. Skills - a reusable package of behavior that can include prompts, instructions, resources, and sometimes scripts/tools for a broader job. Claude skills - https://resources.anthropic.com/hubfs/The-Complete-Guide-to-Building-Skill-for-Claude.pdf?hsLang=en&utm_source=chatgpt.com See examples in table below. Jiminny UI widget for OpenAI medium The reason to have this is to make certain Jiminny use cases much easier than pure chat. Instead of ChatGPT only replying with text like “Here are the last 5 ACME calls,” it could also show a visual Jiminny card or mini-app inside the chat. That widget could list calls, show a deal summary, let the user filter by rep/date/account, open a transcript section, or save a snippet—while the conversation continues in normal chat alongside it. For Jiminny, the best widget use cases are the ones where users need to browse or compare rather than ask one-off questions. A strong example is deal review: the user asks ChatGPT, “What is the status of the ACME deal?” ChatGPT calls your Jiminny MCP tools, and the widget shows a compact deal view with recent calls, risks, next steps, stakeholders, and links to transcripts/snippets. The chat can still summarize the answer in words, but the widget gives a clearer, scannable interface. Another good Jiminny widget use case is call search and exploration. A text answer can say “I found 12 calls mentioning pricing objections,” but a widget could show a sortable list with date, rep, account, score, and objection count, then let the user click into one call to see the exact excerpt or jump to a transcript section. Allow customers to run long-running analyses asynchronously and retrieve progress/results low Some requests/questions require analysis of Hugh volumes of data. For those, it may be better to: start the job let it run in the background return a status like “in progress” let the client come back for the result later For example - User asks in Claude: “Analyse all calls from this quarter and tell me the top 5 objections by segment.” That might require: searching lots of calls pulling many summaries/transcripts aggregating results Instead of making Claude wait 45+ seconds, Jiminny could: create an analysis job return: job_id = 123, status = running We need this in order to support: large-scale analysis multi-call aggregation across lots of data playlist generation across many calls heavy recap/report generation Creating a snippet through the MCP low Create a shareable snippet from a call recording by specifying a time range. Useful for highlighting key moments — objection handling, pricing discussions, competitive mentions — and sharing them with your team. example request: { \"tool\": \"create_snippet\", \"arguments\": { \"call_id\": \"call_123\", \"start_time\": \"00:18:24\", \"end_time\": \"00:19:10\", \"title\": \"Pricing objection\" } } example response: { \"snippet_id\": \"snip_987\", \"title\": \"Pricing objection\", \"share_url\": \"https://app.jiminny.com/snippets/snip_987\" } Ability to add recordings or snippets to a playlist low Allow customers to create libraries of calls automatically. They can use those for onboarding or other purposes Allow AI tools to read reusable Jiminny resources low fathom Resources are useful for data that should be read consistently rather than recomputed every time. In Jiminny terms, that could be: current deal snapshot account summary weekly rep recap approved talk tracks / objection handling guidance curated playlists or snippet libraries This is useful because an AI can consume these directly as context, instead of repeatedly stitching together many tool calls. Ability to write coaching notes in Jiminny through MCP low What we want to do for prompts/worflows and skills Capability Type User value / job to be done Example Jiminny use case Inputs Steps performed Output Draft follow-up email Prompt Help reps quickly create tailored follow-ups after calls Use the latest customer call to draft an email with recap and next steps Call ID optional tone optional recipient type Retrieve call summary and action items from Jiminny. Pull key points, commitments, and next steps. Apply the chosen tone and structure. Draft the email in a consistent format. Customer-ready follow-up email draft Summarise call Prompt Help users quickly extract the most important points from a conversation Generate a concise summary of one call for internal or external use Call ID optional summary style optional audience Retrieve transcript, metadata, and structured insights. Identify key topics, decisions, risks, and next steps. Format output for the chosen audience. Short or structured call summary with actions and risks Generate deal recap Prompt Help reps and managers get a fast overview of a deal Summarise the current state of a deal based on recent calls and linked CRM context Deal ID or account name optional date range Retrieve calls and meetings linked to the deal. Pull deal metadata and CRM-linked context. Identify recent changes, blockers, risks, and next steps. Summarise into a concise recap. Deal recap with status, blockers, risks, and recommended next steps Prepare weekly recap Prompt Help managers or reps review what changed over a time period Weekly recap of calls, themes, and actions for one rep, team, or account Rep ID team ID or account ID time period Retrieve relevant calls and summaries for the selected time period. Aggregate themes, action items, and changes. Highlight notable risks, opportunities, and follow-ups. Weekly recap with top themes, risks, opportunities, and actions Prepare deal review Workflow Help reps and managers review deal status using multiple sources of context Review a deal before pipeline review or forecast meeting Deal ID optional date range Retrieve all recent calls, emails, and meetings tied to the deal. Pull structured call summaries, score, action items, and key points. Pull linked CRM context such as stage, contacts, and account details. Aggregate open risks, unresolved objections, stakeholder gaps, and next steps. Format into a review-ready structure. Deal review document with current status, risks, stakeholders, blockers, and next steps Weekly team recap Workflow Help managers monitor activity and risk across a group of reps or accounts End-of-week team summary for sales leadership Team ID date range Retrieve calls and structured insights across the team. Group by rep, account, or deal. Identify recurring themes, major risks, strong calls, and missed follow-ups. Highlight calls or deals that need attention. Team-level recap with patterns, key risks, notable wins, and action areas Objection analysis across calls Workflow Help teams identify patterns across multiple conversations Analyse pricing or competitor objections across recent calls Account ID deal ID rep ID keyword/topic date range Search calls matching the topic or keyword. Retrieve summaries, transcripts, and snippets where relevant. Identify recurring objections and how they were handled. Assess whether objections were resolved or remain open. Summarise patterns and examples. Objection analysis with themes, frequency, examples, and suggested follow-up actions Build onboarding playlist Workflow Help enablement teams curate useful learning content faster Build a playlist of strong discovery, demo, or pricing calls for new hires Topic call type rep/team filter optional time period Search for calls matching the selected criteria. Rank or filter calls based on score, topics, or key moments. Identify useful snippets or full recordings. Add selected calls/snippets into a playlist structure. Generate short descriptions for each item. Curated onboarding playlist with selected calls/snippets and descriptions Deal Inspection Skill Skill Give users a consistent, opinionated way to assess a deal Claude reviews a deal using a repeatable Jiminny methodology Deal ID or account name optional review scope Determine whether the request is suitable for a deal inspection. Retrieve relevant calls, summaries, CRM context, stakeholders, and risks. Apply a standard Jiminny review framework to assess deal health. Look for missing next steps, unresolved objections, stakeholder gaps, and warning signs. Present findings in a consistent structure with recommended actions. Structured deal inspection with health assessment, red flags, and recommendations Manager Coaching Skill Skill Help managers review calls consistently and identify coaching moments Analyse a rep’s call and surface strengths, gaps, and examples for coaching Call ID optional rep ID optional coaching focus Retrieve transcript, score, summary, and key moments from the call. Evaluate the conversation against a coaching framework. Identify what went well and where the rep could improve. Suggest moments to clip as snippets. Recommend coaching actions or playlist additions. Coaching review with strengths, gaps, snippet suggestions, and recommended coaching actions CSM / QBR Prep Skill Skill Help CS or AM teams prepare structured customer reviews from conversations Generate an account review or QBR-style summary from recent customer interactions Account ID, optional time period Retrieve all recent calls, emails, and account-linked context. Aggregate themes, requests, blockers, sentiment shifts, and opportunities. Apply a repeatable account review structure. Summarise outcomes, open issues, and suggested next steps. Structured QBR/account review summary with themes, risks, opportunities, and actions Snippet Builder Skill Skill Help users consistently capture and label useful moments from calls Identify useful moments in a call and convert them into reusable snippets Call ID, optional focus area such as pricing, objection, competitor, discovery Retrieve transcript, recording timeline, and call insights. Detect moments matching the requested focus area. Propose snippet start/end times and titles. Tag snippets by type or theme. Optionally save them or add them to a playlist. One or more proposed or saved snippets with title, timing, and tags 💡 Technical details Auth model needs specifying. Are API keys scoped per user, per team, or per Jiminny instance? If a key is generated by an admin, does it inherit their visibility level, or provide org-wide? Are permissions evaluated at query time or frozen at key creation? Needs to be query-time, otherwise permission changes won't propagate. Key lifecycle management is missing. No mention of rotation, expiry, or revocation. A departed employee's active key is a data leak. Need: revocation, optional expiry, alerts on stale keys, and consider whether keys should be tied to service accounts rather than personal users. Rate limiting should be HIGH. A compromised key or misconfigured automation could bulk-export an entire customer's call history. Need per-key rate limits and anomaly detection on unusual access patterns. Open Questions Track unresolved issues or decisions that need to be made. Update as answers become available. Question Answer Date Answered Competitor research Competitor MCP Availability Core Capabilities Advanced Capabilities Positioning Key Strength Key Weakness Gong ✅ Mature MCP List/search calls Get transcripts get Call metadata Deal intelligence Scorecards, analytics CRM context Enterprise data layer Deep data + ecosystem integrations Limited opinionated AI workflows Avoma ✅ Mature MCP list_meetings get_meeting get_transcript key topics Deal fields/Deal level analysis Coaching/Scoring CRM context pushing insights into Notion / Confluence AI-ready meeting intelligence Strongest “outputs” layer Mostly pull-based interactions Fathom ✅ MCP list/search meetings get transcript get summary/action items Team/org context Webhooks (event-based triggers) get_weekly_recap aggregated action items across meetings creating webhooks directly from the MCP server Lightweight meeting data access Includes summaries + actions Limited analytics depth Grain ✅ Basic MCP get meetings download transcripts Notes Deals Scorecards Data access utility Simple + accessible Low sophistication, sometimes browser-based Outreach ⚠️ MCP (workflow-focused) Search sequences Emails Meetings (Kaia) account / prospect / opportunity lookups Workflow automation Multi-system orchestration Revenue workflow engine End-to-end GTM workflows Less depth in conversation data Attention ⚠️ Emerging MCP Meeting data Transcripts CRM-linked context AI insights Sales assistant workflows create snippets AI sales assistant + CRM Strong CRM linkage Less focus on external knowledge layer Planhat - Related content Ask Jiminny Anything on Call level Galya Dimitrova Hubspot app Galya Dimitrova Product Vision & Strategy Galya Dimitrova Automated CRM Filling Simona Georgieva (Deactivated) Competitive analysis Galya Dimitrova AI agent ideas Steliyan Georgiev Comments James Graham 9 Apr A few areas around Security & Compliance that need more depth before this moves beyond draft: Auth model needs specifying. Are API keys scoped per user, per team, or per Jiminny instance? If a key is generated by an admin, does it inherit their visibility level, or provide org-wide? Are permissions evaluated at query time or frozen at key creation? Needs to be query-time, otherwise permission changes won't propagate. Team visibility enforcement should be its own HIGH requirement. The current note under access control (\"ensure MCP only exposes data user has access to\") is doing too much work as a single line. Every MCP tool response (especially search_calls and deal-level aggregations) must be filtered through the same visibility engine as the UI. Semantic search is the riskiest here; it could surface results across team boundaries if not properly scoped. No data minimisation or scoping controls. We're exposing transcripts, CRM fields, contact details with job titles, deal context - significant PII and commercial data leaving the platform. Can customers configure which data types are exposed? Can transcripts be PII-stripped before they leave Jiminny? Given we position GDPR consent as a differentiator, we should be thinking about this. GDPR downstream processing is unaddressed. Piping transcripts to OpenAI/Gemini introduces new data processors. Customers need to acknowledge responsibility for downstream processing during setup. We should also consider whether call participants' recording consent covers onward sharing to third-party AI - it almost certainly doesn't by default. This is one for me to pick up. Key lifecycle management is missing. No mention of rotation, expiry, or revocation. A departed employee's active key is a data leak. Need: revocation, optional expiry, alerts on stale keys, and consider whether keys should be tied to service accounts rather than personal users. Rate limiting should be HIGH. A compromised key or misconfigured automation could bulk-export an entire customer's call history. Need per-key rate limits and anomaly detection on unusual access patterns. Audit logs should go deeper. Current spec (what data, which system, when) is a start. Add: identity behind the key, specific queries/filters used, and failed access attempts (especially cross-visibility-boundary attempts). Enterprise compliance teams will expect this. Downgrade handling. Doc says Scale tier and above, but doesn't say what happens on downgrade. Keys should auto-deactivate. Happy to help draft a dedicated Security & Compliance section if useful. Galya Dimitrova 15 Apr Thanks for the input @James Graham . I made the product related changes in the table and for the rest I left them as a note in the Technical section for the team to look at when they start looking at this. I wonder about your points related to GDPR. Currently multiple customers are using the Customer API/zapier to feed this data to AI and BI tools. They are also manually exporting transcripts and other information from the platform and feeding it to AI tools. I don’t get how MCP is so much different that all of these and why it will introduce new data processors (which are already being utilised) and would require any changes to the consent provided by participants.","depth":21,"help_text":"","role_description":"heading","subrole":"AXUnknown"},{"role":"AXStaticText","text":"You said","depth":23,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"Jiminny MCP Connector","depth":23,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"Epic","depth":23,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"Link to Epik in Jira","depth":23,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"Document status","depth":23,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"DRAFT","depth":23,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"Objective","depth":23,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"Enable customers to connect Jiminny data to external AI tools (Claude, OpenAI, Gemini) so it can be used as part of their broader knowledge base and workflows.","depth":23,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"Position Jiminny as a data layer for AI-driven revenue workflows, not just a standalone product.","depth":23,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"👤 Target user","depth":23,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"Revenue teams using AI tools (Sales, CS, RevOps)","depth":23,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"Companies already experimenting with Claude / OpenAI","depth":23,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"Mid-market & Enterprise customers with multiple data sources (CRM, docs, CI tools, Support tools etc)","depth":23,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"🤕 Pain point or problem","depth":23,"bounds":{"left":0.30868056,"top":0.125,"width":0.077430554,"height":0.054444443},"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"Jiminny data is locked in the platform","depth":23,"bounds":{"left":0.30868056,"top":0.18777777,"width":0.074652776,"height":0.085},"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"AI tools lack access to high-value conversation context","depth":23,"bounds":{"left":0.30868056,"top":0.28111112,"width":0.10555556,"height":0.085},"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"Customers must manually export/copy transcripts","depth":23,"bounds":{"left":0.30868056,"top":0.37444445,"width":0.108333334,"height":0.085},"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"No easy way to combine calls with CRM + docs + other info - 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The API key used to access Jiminny has been revoked or has expired. Please ask your Jiminny admin to generate a new API key in Settings > Organization > General and reconnect the MCP server.”","depth":23,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"Rate limit hit — “Error: Rate limit exceeded. Too many requests have been made to the Jiminny MCP server in a short period. Please wait 60 seconds before retrying.”","depth":23,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"Permissions mismatch — if a user tries to access data outside their team visibility settings - “Error: Access denied. The requested call (call_id: [X]) is outside your team's visibility settings in Jiminny. Only calls within your permitted scope are accessible.”","depth":23,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"Trying to access private meeting - “Error: Access denied. 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This is not a data or permissions issue — please retry in a few minutes.”","depth":23,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"No data found - “Error:No calls found matching your criteria. Try adjusting your filters — for example, widening the date range, removing the account filter, or checking the rep name is spelled correctly in Jiminny.”","depth":23,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"Allow customers to securely control who and what data is accessible externally","depth":23,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"HIGH","depth":23,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"Ensure MCP only exposes data user has access to - based on team visibility settings. 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This will make it easier for customers to find us and to connect Jiminny","depth":23,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"Provide customers with example workflows to get started quickly","depth":23,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"medium","depth":23,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"A workflow is usually multiple steps, maybe multiple tools, still focused on one outcome.","depth":23,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"See examples in table below.","depth":23,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"Allow customers to use predefined Jiminny skills for common workflows","depth":23,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"medium","depth":23,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"Anthropic describes Skills as folders that include instructions, scripts, and resources that Claude can load when relevant, and as a way to teach Claude repeatable workflows, preferences, and domain expertise once instead of re-explaining them every time. Skills - a reusable package of behavior that can include prompts, instructions, resources, and sometimes scripts/tools for a broader job.","depth":23,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"Claude skills - https://resources.anthropic.com/hubfs/The-Complete-Guide-to-Building-Skill-for-Claude.pdf?hsLang=en&utm_source=chatgpt.com","depth":23,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"See examples in table below.","depth":23,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"Jiminny UI widget for OpenAI","depth":23,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"medium","depth":23,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"The reason to have this is to make certain Jiminny use cases much easier than pure chat.","depth":23,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"Instead of ChatGPT only replying with text like “Here are the last 5 ACME calls,” it could also show a visual Jiminny card or mini-app inside the chat. That widget could list calls, show a deal summary, let the user filter by rep/date/account, open a transcript section, or save a snippet—while the conversation continues in normal chat alongside it.","depth":23,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"For Jiminny, the best widget use cases are the ones where users need to browse or compare rather than ask one-off questions. A strong example is deal review: the user asks ChatGPT, “What is the status of the ACME deal?” ChatGPT calls your Jiminny MCP tools, and the widget shows a compact deal view with recent calls, risks, next steps, stakeholders, and links to transcripts/snippets. The chat can still summarize the answer in words, but the widget gives a clearer, scannable interface.","depth":23,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"Another good Jiminny widget use case is call search and exploration. A text answer can say “I found 12 calls mentioning pricing objections,” but a widget could show a sortable list with date, rep, account, score, and objection count, then let the user click into one call to see the exact excerpt or jump to a transcript section.","depth":23,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"Allow customers to run long-running analyses asynchronously and retrieve progress/results","depth":23,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"low","depth":23,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"Some requests/questions require analysis of Hugh volumes of data. 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Useful for highlighting key moments — objection handling, pricing discussions, competitive mentions — and sharing them with your team.","depth":23,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"example request:","depth":23,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"{","depth":23,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"\"tool\": \"create_snippet\",","depth":23,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"\"arguments\": {","depth":23,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"\"call_id\": \"call_123\",","depth":23,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"\"start_time\": \"00:18:24\",","depth":23,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"\"end_time\": \"00:19:10\",","depth":23,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"\"title\": \"Pricing objection\"","depth":23,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"}","depth":23,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"}","depth":23,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"example response:","depth":23,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"{","depth":23,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"\"snippet_id\": \"snip_987\",","depth":23,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"\"title\": \"Pricing objection\",","depth":23,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"\"share_url\": \"https://app.jiminny.com/snippets/snip_987\"","depth":23,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"}","depth":23,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"Ability to add recordings or snippets to a playlist","depth":23,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"low","depth":23,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"Allow customers to create libraries of calls automatically. They can use those for onboarding or other purposes","depth":23,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"Allow AI tools to read reusable Jiminny resources","depth":23,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"low","depth":23,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"fathom","depth":23,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"Resources are useful for data that should be read consistently rather than recomputed every time. 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triggers)","depth":23,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"get_weekly_recap","depth":23,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"aggregated action items across meetings","depth":23,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"creating webhooks directly from the MCP server","depth":23,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"Lightweight meeting data access","depth":23,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"Includes summaries + actions","depth":23,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"Limited analytics depth","depth":23,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"Grain","depth":23,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"✅ Basic MCP","depth":23,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"get meetings","depth":23,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"download transcripts","depth":23,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"Notes","depth":23,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"Deals","depth":23,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"Scorecards","depth":23,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"Data access utility","depth":23,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"Simple + accessible","depth":23,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"Low sophistication, sometimes browser-based","depth":23,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"Outreach","depth":23,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"⚠️ MCP (workflow-focused)","depth":23,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"Search sequences","depth":23,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"Emails","depth":23,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"Meetings (Kaia)","depth":23,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"account / prospect / opportunity lookups","depth":23,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"Workflow automation","depth":23,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"Multi-system orchestration","depth":23,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"Revenue workflow engine","depth":23,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"End-to-end GTM workflows","depth":23,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"Less depth in conversation data","depth":23,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"Attention","depth":23,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"⚠️ Emerging MCP","depth":23,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"Meeting data","depth":23,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"Transcripts","depth":23,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"CRM-linked context","depth":23,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"AI insights","depth":23,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"Sales assistant workflows","depth":23,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"create snippets","depth":23,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"AI sales assistant + CRM","depth":23,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"Strong CRM linkage","depth":23,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"Less focus on external knowledge layer","depth":23,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"Planhat -","depth":23,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"Related content","depth":23,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"Ask Jiminny Anything on Call level","depth":23,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"Galya Dimitrova","depth":23,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"Hubspot app","depth":23,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"Galya Dimitrova","depth":23,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"Product Vision & Strategy","depth":23,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"Galya Dimitrova","depth":23,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"Automated CRM Filling","depth":23,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"Simona Georgieva (Deactivated)","depth":23,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"Competitive analysis","depth":23,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"Galya Dimitrova","depth":23,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"AI agent ideas","depth":23,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"Steliyan Georgiev","depth":23,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"Comments","depth":23,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"James Graham","depth":23,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"9 Apr","depth":23,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"A few areas around Security & Compliance that need more depth before this moves beyond draft:","depth":23,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"Auth model needs specifying. Are API keys scoped per user, per team, or per Jiminny instance? If a key is generated by an admin, does it inherit their visibility level, or provide org-wide? Are permissions evaluated at query time or frozen at key creation? Needs to be query-time, otherwise permission changes won't propagate.","depth":23,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"Team visibility enforcement should be its own HIGH requirement. The current note under access control (\"ensure MCP only exposes data user has access to\") is doing too much work as a single line. Every MCP tool response (especially search_calls and deal-level aggregations) must be filtered through the same visibility engine as the UI. Semantic search is the riskiest here; it could surface results across team boundaries if not properly scoped.","depth":23,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"No data minimisation or scoping controls. We're exposing transcripts, CRM fields, contact details with job titles, deal context - significant PII and commercial data leaving the platform. Can customers configure which data types are exposed? Can transcripts be PII-stripped before they leave Jiminny? Given we position GDPR consent as a differentiator, we should be thinking about this.","depth":23,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"GDPR downstream processing is unaddressed. Piping transcripts to OpenAI/Gemini introduces new data processors. Customers need to acknowledge responsibility for downstream processing during setup. We should also consider whether call participants' recording consent covers onward sharing to third-party AI - it almost certainly doesn't by default. This is one for me to pick up.","depth":23,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"Key lifecycle management is missing. No mention of rotation, expiry, or revocation. A departed employee's active key is a data leak. Need: revocation, optional expiry, alerts on stale keys, and consider whether keys should be tied to service accounts rather than personal users.","depth":23,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"Rate limiting should be HIGH. A compromised key or misconfigured automation could bulk-export an entire customer's call history. Need per-key rate limits and anomaly detection on unusual access patterns.","depth":23,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"Audit logs should go deeper. Current spec (what data, which system, when) is a start. Add: identity behind the key, specific queries/filters used, and failed access attempts (especially cross-visibility-boundary attempts). Enterprise compliance teams will expect this.","depth":23,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"Downgrade handling. Doc says Scale tier and above, but doesn't say what happens on downgrade. Keys should auto-deactivate.","depth":23,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"Happy to help draft a dedicated Security & Compliance section if useful.","depth":23,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"Galya Dimitrova","depth":23,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"15 Apr","depth":23,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"Thanks for the input @James Graham . I made the product related changes in the table and for the rest I left them as a note in the Technical section for the team to look at when they start looking at this.","depth":23,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"I wonder about your points related to GDPR. Currently multiple customers are using the Customer API/zapier to feed this data to AI and BI tools. They are also manually exporting transcripts and other information from the platform and feeding it to AI tools. I don’t get how MCP is so much different that all of these and why it will introduce new data processors (which are already being utilised) and would require any changes to the consent provided by participants.","depth":23,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXButton","text":"Expand","depth":21,"role_description":"button","subrole":"AXUnknown","is_enabled":true,"is_focused":false,"is_selected":false},{"role":"AXButton","text":"Listen","depth":22,"help_text":"","role_description":"button","subrole":"AXUnknown","is_enabled":true,"is_focused":false,"is_selected":false},{"role":"AXButton","text":"Show more options","depth":20,"role_description":"button","subrole":"AXUnknown","is_enabled":true,"is_focused":false,"is_selected":false},{"role":"AXStaticText","text":"Show thinking","depth":26,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXHeading","text":"Gemini said","depth":20,"help_text":"","role_description":"heading","subrole":"AXUnknown"},{"role":"AXStaticText","text":"Gemini said","depth":21,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"Thank you for sharing the draft PRD for the","depth":24,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"Jiminny MCP Connector","depth":24,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":". It looks like a highly strategic initiative to transition Jiminny from a standalone platform into a foundational data layer for AI-driven revenue workflows.","depth":24,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"Here is a quick breakdown of the document as it currently stands:","depth":24,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXHeading","text":"Executive Summary","depth":23,"help_text":"","role_description":"heading","subrole":"AXUnknown"},{"role":"AXStaticText","text":"Executive Summary","depth":24,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"Core Objective:","depth":26,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"Build an MCP-based AI Knowledge Connector to expose Jiminny data (transcripts, summaries, deal context) to external AI tools like Claude, OpenAI, and Gemini.","depth":26,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"Target Value:","depth":26,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"Increases product stickiness, reduces manual data entry/copy-pasting, and achieves competitive parity with platforms like Gong and Avoma.","depth":26,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"Key Capabilities:","depth":26,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"* Call and deal-level data retrieval.","depth":26,"help_text":"","role_description":"text","subrole":"AXUnknown"}]...
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Platform Sprint 2 Q2 - Platform Team - Scrum Board Platform Sprint 2 Q2 - Platform Team - Scrum Board - Jira
SevenShores\Hubspot\Exceptions\BadRequest: Client error: `POST [URL_WITH_CREDENTIALS] Graham . I made the product related changes in the table and for the rest I left them as a note in the Technical section for the team to look at when they start looking at this. I wonder about your points related to GDPR. Currently multiple customers are using the Customer API/zapier to feed this data to AI and BI tools. They are also manually exporting transcripts and other information from the platform and feeding it to AI tools. I don’t get how MCP is so much different that all of these and why it will introduce new data processors (which are already being utilised) and would require any changes to the consent provided by participants.
You said
Jiminny MCP Connector
Epic
Link to Epik in Jira
Document status
DRAFT
Objective
Enable customers to connect Jiminny data to external AI tools (Claude, OpenAI, Gemini) so it can be used as part of their broader knowledge base and workflows.
Position Jiminny as a data layer for AI-driven revenue workflows, not just a standalone product.
👤 Target user
Revenue teams using AI tools (Sales, CS, RevOps)
Companies already experimenting with Claude / OpenAI
Mid-market & Enterprise customers with multiple data sources (CRM, docs, CI tools, Support tools etc)
🤕 Pain point or problem
Jiminny data is locked in the platform
AI tools lack access to high-value conversation context
Customers must manually export/copy transcripts
No easy way to combine calls with CRM + docs + other info - using the Jiminny API is not suitable for non technical sales people
Peer pressure as almost all competitors have this
💥 Impact and benefits
For customers
Better AI outputs using real customer conversations
Ability to build automated workflows across tools
For Jiminny
Increased product stickiness (embedded in workflows)
Competitive parity with Gong / Avoma etc.
💡 Solution ideas
Build an AI Knowledge Connector (MCP-based) that:
Exposes Jiminny data (calls, transcripts, metadata) to AI tools
Provides structured insights (summaries, action items, scoring etc.)
Supports deal-level context
Allows integration into customer-owned AI stacks (Claude + Zapier, etc.)
Success metrics
List the key goals and how you will measure success. Include both qualitative and quantitative metrics (e.g., user adoption, retention rate, revenue targets).
Goal
Metric
Increase stickiness by ensuring Jiminny is embedded in the customer’s workflows
% of customers connecting external AI tools
Number of MCP/API calls per customer - and which ones are being used the most
Decrease the manual copying of transcripts
decrease by X %
User interaction and design
Simple setup flow:
Generate API key / connect MCP
Clear instructions for Claude / Zapier setup
Provide:
Example prompts for Claude
Pre-built workflow templates for Zapier
Clear documentation - with use cases
👉 Focus: usable by non-technical users
Detailed Requirements
List the functional and non-functional requirements. Prioritize them (e.g., High, Medium, Low) and add notes for clarification.
Requirement
Importance
Notes
Allow customers to connect Jiminny to their AI tools (e.g. Claude, OpenAI)
HIGH
Provide MCP endpoint so customers can easily integrate Jiminny into their AI stack
Allow customers to access call data through AI tools
HIGH
Expose Jiminny data:
list calls (filter by date, user, account, deal)
get call
get transcript (speaker-separated)
get call metadata
search calls (keyword + semantic)
Support filtering by:
account / contact/ lead / deal
jiminny user
date range
Allow customers to search and query calls using AI tools
HIGH
Support keyword and semantic search across conversations
Provide structured insights so customers can generate better outputs
HIGH
For each call, expose:
Summary
Action items
Key points
Activity type
Notes
Call Score
CRM information
Allow customers to understand deal status across multiple calls/emails
HIGH
For each deal expose:
calls/meetings/emails
Identified risks
contacts related to the deal with their job title
linked account details
all CRM field information that we have in DI + fields used for CRM filling
example - get_deal_summary
request -
{
"tool": "get_deal_summary",
"arguments": {
"deal_name": "ACME"
}
}
responce:
{
"deal_name": "ACME",
"stage": "Negotiation",
"recent_activity": [
"Demo call on 2026-04-01",
"Pricing discussion on 2026-04-03"
],
"risks": [
"Pricing concerns",
"Security review pending"
], "next_steps": [
"Send follow-up to VP Sales",
"Share security documentation"
]
}
Ensure the AI can easily understand the schema of the data coming from Jiminny
HIGH
Models perform much better when tools have:
clear names
rich descriptions
predictable schemas
Provide clear, actionable error states for customers when MCP connections fail
HIGH
Error messages should guide agents toward solutions with specific suggestions and next steps.
Expired or revoked key — “Error: Authentication failed. The API key used to access Jiminny has been revoked or has expired. Please ask your Jiminny admin to generate a new API key in Settings > Organization > General and reconnect the MCP server.”
Rate limit hit — “Error: Rate limit exceeded. Too many requests have been made to the Jiminny MCP server in a short period. Please wait 60 seconds before retrying.”
Permissions mismatch — if a user tries to access data outside their team visibility settings - “Error: Access denied. The requested call (call_id: [X]) is outside your team's visibility settings in Jiminny. Only calls within your permitted scope are accessible.”
Trying to access private meeting - “Error: Access denied. This meeting has been marked as private by the host and cannot be accessed through the MCP connector. Try requesting a different call or ask the meeting host to change the visibility settings in Jiminny.”
Downgraded/Capture account — if a customer's plan drops below Scale tier or the Customer is on Capture in the first place - “Error: MCP access unavailable. The Jiminny MCP connector is available on the Scale plan and above. Your account does not currently have an active Scale subscription.”
Jiminny-side outage — “Error:Jiminny is temporarily unavailable (status 503). This is not a data or permissions issue — please retry in a few minutes.”
No data found - “Error:No calls found matching your criteria. Try adjusting your filters — for example, widening the date range, removing the account filter, or checking the rep name is spelled correctly in Jiminny.”
Allow customers to securely control who and what data is accessible externally
HIGH
Ensure MCP only exposes data user has access to - based on team visibility settings. This means that if a user is not allow to access calls/deals in Jiminny UI then they shouldn’t be able to access those through the MCP as well.
Private meetings shouldn’t be exposed via MCP
HIGH
When a meetings is set to Private then the information about it shouldn’t be exposed through the MCP.
Ensure Jiminny data can be combined with other sources (e.g. CRM, docs) in AI workflows
HIGH
Ensure data is structured to be easily combined with:
CRM (accounts, deals)
external docs
Use consistent identifiers:
account IDs
deal IDs
MCP is available only for Scale tier and above
HIGH
Customers who are on Capture tier should be able to access any of their data through MCP.
This should also cover the scenario when a customer has been on Scale but then downgrades to Capture - their MCP access should stop working.
Provide visibility into how external AI tools access Jiminny data
HIGH
Audit logs:
what data was accessed by which external system when
identity - who made the request
specific queries/filters used
failed access attempts (especially cross-visibility-boundary attempts)
Admins should be able to access the logs from the org settings.We can start with a csv export before building a specific page for it.
example from Atlassian -
Provide customers with example prompts to get started quickly
HIGH
MCP prompts are explicitly defined as prompt templates that clients can discover and call with arguments.
See examples in table below.
Expose Jiminny as a Connector in Claude
medium
Competitors like Fathom are listed as Connectors in Claude. This will make it easier for customers to find us and to connect Jiminny
Provide customers with example workflows to get started quickly
medium
A workflow is usually multiple steps, maybe multiple tools, still focused on one outcome.
See examples in table below.
Allow customers to use predefined Jiminny skills for common workflows
medium
Anthropic describes Skills as folders that include instructions, scripts, and resources that Claude can load when relevant, and as a way to teach Claude repeatable workflows, preferences, and domain expertise once instead of re-explaining them every time. Skills - a reusable package of behavior that can include prompts, instructions, resources, and sometimes scripts/tools for a broader job.
Claude skills - https://resources.anthropic.com/hubfs/The-Complete-Guide-to-Building-Skill-for-Claude.pdf?hsLang=en&utm_source=chatgpt.com
See examples in table below.
Jiminny UI widget for OpenAI
medium
The reason to have this is to make certain Jiminny use cases much easier than pure chat.
Instead of ChatGPT only replying with text like “Here are the last 5 ACME calls,” it could also show a visual Jiminny card or mini-app inside the chat. That widget could list calls, show a deal summary, let the user filter by rep/date/account, open a transcript section, or save a snippet—while the conversation continues in normal chat alongside it.
For Jiminny, the best widget use cases are the ones where users need to browse or compare rather than ask one-off questions. A strong example is deal review: the user asks ChatGPT, “What is the status of the ACME deal?” ChatGPT calls your Jiminny MCP tools, and the widget shows a compact deal view with recent calls, risks, next steps, stakeholders, and links to transcripts/snippets. The chat can still summarize the answer in words, but the widget gives a clearer, scannable interface.
Another good Jiminny widget use case is call search and exploration. A text answer can say “I found 12 calls mentioning pricing objections,” but a widget could show a sortable list with date, rep, account, score, and objection count, then let the user click into one call to see the exact excerpt or jump to a transcript section.
Allow customers to run long-running analyses asynchronously and retrieve progress/results
low
Some requests/questions require analysis of Hugh volumes of data. For those, it may be better to:
start the job
let it run in the background
return a status like “in progress”
let the client come back for the result later
For example - User asks in Claude:
“Analyse all calls from this quarter and tell me the top 5 objections by segment.”
That might require:
searching lots of calls
pulling many summaries/transcripts
aggregating results
Instead of making Claude wait 45+ seconds, Jiminny could:
create an analysis job
return: job_id = 123, status = running
We need this in order to support:
large-scale analysis
multi-call aggregation across lots of data
playlist generation across many calls
heavy recap/report generation
Creating a snippet through the MCP
low
Create a shareable snippet from a call recording by specifying a time range. Useful for highlighting key moments — objection handling, pricing discussions, competitive mentions — and sharing them with your team.
example request:
{
"tool": "create_snippet",
"arguments": {
"call_id": "call_123",
"start_time": "00:18:24",
"end_time": "00:19:10",
"title": "Pricing objection"
}
}
example response:
{
"snippet_id": "snip_987",
"title": "Pricing objection",
"share_url": "https://app.jiminny.com/snippets/snip_987"
}
Ability to add recordings or snippets to a playlist
low
Allow customers to create libraries of calls automatically. They can use those for onboarding or other purposes
Allow AI tools to read reusable Jiminny resources
low
fathom
Resources are useful for data that should be read consistently rather than recomputed every time. In Jiminny terms, that could be:
current deal snapshot
account summary
weekly rep recap
approved talk tracks / objection handling guidance
curated playlists or snippet libraries
This is useful because an AI can consume these directly as context, instead of repeatedly stitching together many tool calls.
Ability to write coaching notes in Jiminny through MCP
low
What we want to do for prompts/worflows and skills
Capability
Type
User value / job to be done
Example Jiminny use case
Inputs
Steps performed
Output
Draft follow-up email
Prompt
Help reps quickly create tailored follow-ups after calls
Use the latest customer call to draft an email with recap and next steps
Call ID
optional tone
optional recipient type
Retrieve call summary and action items from Jiminny.
Pull key points, commitments, and next steps.
Apply the chosen tone and structure.
Draft the email in a consistent format.
Customer-ready follow-up email draft
Summarise call
Prompt
Help users quickly extract the most important points from a conversation
Generate a concise summary of one call for internal or external use
Call ID
optional summary style
optional audience
Retrieve transcript, metadata, and structured insights.
Identify key topics, decisions, risks, and next steps.
Format output for the chosen audience.
Short or structured call summary with actions and risks
Generate deal recap
Prompt
Help reps and managers get a fast overview of a deal
Summarise the current state of a deal based on recent calls and linked CRM context
Deal ID or account name
optional date range
Retrieve calls and meetings linked to the deal.
Pull deal metadata and CRM-linked context.
Identify recent changes, blockers, risks, and next steps.
Summarise into a concise recap.
Deal recap with status, blockers, risks, and recommended next steps
Prepare weekly recap
Prompt
Help managers or reps review what changed over a time period
Weekly recap of calls, themes, and actions for one rep, team, or account
Rep ID
team ID or account ID
time period
Retrieve relevant calls and summaries for the selected time period.
Aggregate themes, action items, and changes.
Highlight notable risks, opportunities, and follow-ups.
Weekly recap with top themes, risks, opportunities, and actions
Prepare deal review
Workflow
Help reps and managers review deal status using multiple sources of context
Review a deal before pipeline review or forecast meeting
Deal ID
optional date range
Retrieve all recent calls, emails, and meetings tied to the deal.
Pull structured call summaries, score, action items, and key points.
Pull linked CRM context such as stage, contacts, and account details.
Aggregate open risks, unresolved objections, stakeholder gaps, and next steps.
Format into a review-ready structure.
Deal review document with current status, risks, stakeholders, blockers, and next steps
Weekly team recap
Workflow
Help managers monitor activity and risk across a group of reps or accounts
End-of-week team summary for sales leadership
Team ID
date range
Retrieve calls and structured insights across the team.
Group by rep, account, or deal.
Identify recurring themes, major risks, strong calls, and missed follow-ups.
Highlight calls or deals that need attention.
Team-level recap with patterns, key risks, notable wins, and action areas
Objection analysis across calls
Workflow
Help teams identify patterns across multiple conversations
Analyse pricing or competitor objections across recent calls
Account ID
deal ID
rep ID
keyword/topic
date range
Search calls matching the topic or keyword.
Retrieve summaries, transcripts, and snippets where relevant.
Identify recurring objections and how they were handled.
Assess whether objections were resolved or remain open.
Summarise patterns and examples.
Objection analysis with themes, frequency, examples, and suggested follow-up actions
Build onboarding playlist
Workflow
Help enablement teams curate useful learning content faster
Build a playlist of strong discovery, demo, or pricing calls for new hires
Topic
call type
rep/team filter
optional time period
Search for calls matching the selected criteria.
Rank or filter calls based on score, topics, or key moments.
Identify useful snippets or full recordings.
Add selected calls/snippets into a playlist structure.
Generate short descriptions for each item.
Curated onboarding playlist with selected calls/snippets and descriptions
Deal Inspection Skill
Skill
Give users a consistent, opinionated way to assess a deal
Claude reviews a deal using a repeatable Jiminny methodology
Deal ID or account name
optional review scope
Determine whether the request is suitable for a deal inspection.
Retrieve relevant calls, summaries, CRM context, stakeholders, and risks.
Apply a standard Jiminny review framework to assess deal health.
Look for missing next steps, unresolved objections, stakeholder gaps, and warning signs.
Present findings in a consistent structure with recommended actions.
Structured deal inspection with health assessment, red flags, and recommendations
Manager Coaching Skill
Skill
Help managers review calls consistently and identify coaching moments
Analyse a rep’s call and surface strengths, gaps, and examples for coaching
Call ID
optional rep ID
optional coaching focus
Retrieve transcript, score, summary, and key moments from the call.
Evaluate the conversation against a coaching framework.
Identify what went well and where the rep could improve.
Suggest moments to clip as snippets.
Recommend coaching actions or playlist additions.
Coaching review with strengths, gaps, snippet suggestions, and recommended coaching actions
CSM / QBR Prep Skill
Skill
Help CS or AM teams prepare structured customer reviews from conversations
Generate an account review or QBR-style summary from recent customer interactions
Account ID, optional time period
Retrieve all recent calls, emails, and account-linked context.
Aggregate themes, requests, blockers, sentiment shifts, and opportunities.
Apply a repeatable account review structure.
Summarise outcomes, open issues, and suggested next steps.
Structured QBR/account review summary with themes, risks, opportunities, and actions
Snippet Builder Skill
Skill
Help users consistently capture and label useful moments from calls
Identify useful moments in a call and convert them into reusable snippets
Call ID, optional focus area such as pricing, objection, competitor, discovery
Retrieve transcript, recording timeline, and call insights.
Detect moments matching the requested focus area.
Propose snippet start/end times and titles.
Tag snippets by type or theme.
Optionally save them or add them to a playlist.
One or more proposed or saved snippets with title, timing, and tags
💡 Technical details
Auth model needs specifying. Are API keys scoped per user, per team, or per Jiminny instance? If a key is generated by an admin, does it inherit their visibility level, or provide org-wide? Are permissions evaluated at query time or frozen at key creation? Needs to be query-time, otherwise permission changes won't propagate.
Key lifecycle management is missing. No mention of rotation, expiry, or revocation. A departed employee's active key is a data leak. Need: revocation, optional expiry, alerts on stale keys, and consider whether keys should be tied to service accounts rather than personal users.
Rate limiting should be HIGH. A compromised key or misconfigured automation could bulk-export an entire customer's call history. Need per-key rate limits and anomaly detection on unusual access patterns.
Open Questions
Track unresolved issues or decisions that need to be made. Update as answers become available.
Question
Answer
Date Answered
Competitor research
Competitor
MCP Availability
Core Capabilities
Advanced Capabilities
Positioning
Key Strength
Key Weakness
Gong
✅ Mature MCP
List/search calls
Get transcripts
get Call metadata
Deal intelligence
Scorecards, analytics
CRM context
Enterprise data layer
Deep data + ecosystem integrations
Limited opinionated AI workflows
Avoma
✅ Mature MCP
list_meetings
get_meeting
get_transcript
key topics
Deal fields/Deal level analysis
Coaching/Scoring
CRM context
pushing insights into Notion / Confluence
AI-ready meeting intelligence
Strongest “outputs” layer
Mostly pull-based interactions
Fathom
✅ MCP
list/search meetings
get transcript
get summary/action items
Team/org context
Webhooks (event-based triggers)
get_weekly_recap
aggregated action items across meetings
creating webhooks directly from the MCP server
Lightweight meeting data access
Includes summaries + actions
Limited analytics depth
Grain
✅ Basic MCP
get meetings
download transcripts
Notes
Deals
Scorecards
Data access utility
Simple + accessible
Low sophistication, sometimes browser-based
Outreach
⚠️ MCP (workflow-focused)
Search sequences
Emails
Meetings (Kaia)
account / prospect / opportunity lookups
Workflow automation
Multi-system orchestration
Revenue workflow engine
End-to-end GTM workflows
Less depth in conversation data
Attention
⚠️ Emerging MCP
Meeting data
Transcripts
CRM-linked context
AI insights
Sales assistant workflows
create snippets
AI sales assistant + CRM
Strong CRM linkage
Less focus on external knowledge layer
Planhat -
Related content
Ask Jiminny Anything on Call level
Galya Dimitrova
Hubspot app
Galya Dimitrova
Product Vision & Strategy
Galya Dimitrova
Automated CRM Filling
Simona Georgieva (Deactivated)
Competitive analysis
Galya Dimitrova
AI agent ideas
Steliyan Georgiev
Comments
James Graham
9 Apr
A few areas around Security & Compliance that need more depth before this moves beyond draft:
Auth model needs specifying. Are API keys scoped per user, per team, or per Jiminny instance? If a key is generated by an admin, does it inherit their visibility level, or provide org-wide? Are permissions evaluated at query time or frozen at key creation? Needs to be query-time, otherwise permission changes won't propagate.
Team visibility enforcement should be its own HIGH requirement. The current note under access control ("ensure MCP only exposes data user has access to") is doing too much work as a single line. Every MCP tool response (especially search_calls and deal-level aggregations) must be filtered through the same visibility engine as the UI. Semantic search is the riskiest here; it could surface results across team boundaries if not properly scoped.
No data minimisation or scoping controls. We're exposing transcripts, CRM fields, contact details with job titles, deal context - significant PII and commercial data leaving the platform. Can customers configure which data types are exposed? Can transcripts be PII-stripped before they leave Jiminny? Given we position GDPR consent as a differentiator, we should be thinking about this.
GDPR downstream processing is unaddressed. Piping transcripts to OpenAI/Gemini introduces new data processors. Customers need to acknowledge responsibility for downstream processing during setup. We should also consider whether call participants' recording consent covers onward sharing to third-party AI - it almost certainly doesn't by default. This is one for me to pick up.
Key lifecycle management is missing. No mention of rotation, expiry, or revocation. A departed employee's active key is a data leak. Need: revocation, optional expiry, alerts on stale keys, and consider whether keys should be tied to service accounts rather than personal users.
Rate limiting should be HIGH. A compromised key or misconfigured automation could bulk-export an entire customer's call history. Need per-key rate limits and anomaly detection on unusual ac...
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Platform Sprint 2 Q2 - Platform Team - Scrum Board Platform Sprint 2 Q2 - Platform Team - Scrum Board - Jira
SevenShores\Hubspot\Exceptions\BadRequest: Client error: `POST [URL_WITH_CREDENTIALS] Graham . I made the product related changes in the table and for the rest I left them as a note in the Technical section for the team to look at when they start looking at this. I wonder about your points related to GDPR. Currently multiple customers are using the Customer API/zapier to feed this data to AI and BI tools. They are also manually exporting transcripts and other information from the platform and feeding it to AI tools. I don’t get how MCP is so much different that all of these and why it will introduce new data processors (which are already being utilised) and would require any changes to the consent provided by participants.
You said
Jiminny MCP Connector
Epic
Link to Epik in Jira
Document status
DRAFT
Objective
Enable customers to connect Jiminny data to external AI tools (Claude, OpenAI, Gemini) so it can be used as part of their broader knowledge base and workflows.
Position Jiminny as a data layer for AI-driven revenue workflows, not just a standalone product.
👤 Target user
Revenue teams using AI tools (Sales, CS, RevOps)
Companies already experimenting with Claude / OpenAI
Mid-market & Enterprise customers with multiple data sources (CRM, docs, CI tools, Support tools etc)
🤕 Pain point or problem
Jiminny data is locked in the platform
AI tools lack access to high-value conversation context
Customers must manually export/copy transcripts
No easy way to combine calls with CRM + docs + other info - using the Jiminny API is not suitable for non technical sales people
Peer pressure as almost all competitors have this
💥 Impact and benefits
For customers
Better AI outputs using real customer conversations
Ability to build automated workflows across tools
For Jiminny
Increased product stickiness (embedded in workflows)
Competitive parity with Gong / Avoma etc.
💡 Solution ideas
Build an AI Knowledge Connector (MCP-based) that:
Exposes Jiminny data (calls, transcripts, metadata) to AI tools
Provides structured insights (summaries, action items, scoring etc.)
Supports deal-level context
Allows integration into customer-owned AI stacks (Claude + Zapier, etc.)
Success metrics
List the key goals and how you will measure success. Include both qualitative and quantitative metrics (e.g., user adoption, retention rate, revenue targets).
Goal
Metric
Increase stickiness by ensuring Jiminny is embedded in the customer’s workflows
% of customers connecting external AI tools
Number of MCP/API calls per customer - and which ones are being used the most
Decrease the manual copying of transcripts
decrease by X %
User interaction and design
Simple setup flow:
Generate API key / connect MCP
Clear instructions for Claude / Zapier setup
Provide:
Example prompts for Claude
Pre-built workflow templates for Zapier
Clear documentation - with use cases
👉 Focus: usable by non-technical users
Detailed Requirements
List the functional and non-functional requirements. Prioritize them (e.g., High, Medium, Low) and add notes for clarification.
Requirement
Importance
Notes
Allow customers to connect Jiminny to their AI tools (e.g. Claude, OpenAI)
HIGH
Provide MCP endpoint so customers can easily integrate Jiminny into their AI stack
Allow customers to access call data through AI tools
HIGH
Expose Jiminny data:
list calls (filter by date, user, account, deal)
get call
get transcript (speaker-separated)
get call metadata
search calls (keyword + semantic)
Support filtering by:
account / contact/ lead / deal
jiminny user
date range
Allow customers to search and query calls using AI tools
HIGH
Support keyword and semantic search across conversations
Provide structured insights so customers can generate better outputs
HIGH
For each call, expose:
Summary
Action items
Key points
Activity type
Notes
Call Score
CRM information
Allow customers to understand deal status across multiple calls/emails
HIGH
For each deal expose:
calls/meetings/emails
Identified risks
contacts related to the deal with their job title
linked account details
all CRM field information that we have in DI + fields used for CRM filling
example - get_deal_summary
request -
{
"tool": "get_deal_summary",
"arguments": {
"deal_name": "ACME"
}
}
responce:
{
"deal_name": "ACME",
"stage": "Negotiation",
"recent_activity": [
"Demo call on 2026-04-01",
"Pricing discussion on 2026-04-03"
],
"risks": [
"Pricing concerns",
"Security review pending"
], "next_steps": [
"Send follow-up to VP Sales",
"Share security documentation"
]
}
Ensure the AI can easily understand the schema of the data coming from Jiminny
HIGH
Models perform much better when tools have:
clear names
rich descriptions
predictable schemas
Provide clear, actionable error states for customers when MCP connections fail
HIGH
Error messages should guide agents toward solutions with specific suggestions and next steps.
Expired or revoked key — “Error: Authentication failed. The API key used to access Jiminny has been revoked or has expired. Please ask your Jiminny admin to generate a new API key in Settings > Organization > General and reconnect the MCP server.”
Rate limit hit — “Error: Rate limit exceeded. Too many requests have been made to the Jiminny MCP server in a short period. Please wait 60 seconds before retrying.”
Permissions mismatch — if a user tries to access data outside their team visibility settings - “Error: Access denied. The requested call (call_id: [X]) is outside your team's visibility settings in Jiminny. Only calls within your permitted scope are accessible.”
Trying to access private meeting - “Error: Access denied. This meeting has been marked as private by the host and cannot be accessed through the MCP connector. Try requesting a different call or ask the meeting host to change the visibility settings in Jiminny.”
Downgraded/Capture account — if a customer's plan drops below Scale tier or the Customer is on Capture in the first place - “Error: MCP access unavailable. The Jiminny MCP connector is available on the Scale plan and above. Your account does not currently have an active Scale subscription.”
Jiminny-side outage — “Error:Jiminny is temporarily unavailable (status 503). This is not a data or permissions issue — please retry in a few minutes.”
No data found - “Error:No calls found matching your criteria. Try adjusting your filters — for example, widening the date range, removing the account filter, or checking the rep name is spelled correctly in Jiminny.”
Allow customers to securely control who and what data is accessible externally
HIGH
Ensure MCP only exposes data user has access to - based on team visibility settings. This means that if a user is not allow to access calls/deals in Jiminny UI then they shouldn’t be able to access those through the MCP as well.
Private meetings shouldn’t be exposed via MCP
HIGH
When a meetings is set to Private then the information about it shouldn’t be exposed through the MCP.
Ensure Jiminny data can be combined with other sources (e.g. CRM, docs) in AI workflows
HIGH
Ensure data is structured to be easily combined with:
CRM (accounts, deals)
external docs
Use consistent identifiers:
account IDs
deal IDs
MCP is available only for Scale tier and above
HIGH
Customers who are on Capture tier should be able to access any of their data through MCP.
This should also cover the scenario when a customer has been on Scale but then downgrades to Capture - their MCP access should stop working.
Provide visibility into how external AI tools access Jiminny data
HIGH
Audit logs:
what data was accessed by which external system when
identity - who made the request
specific queries/filters used
failed access attempts (especially cross-visibility-boundary attempts)
Admins should be able to access the logs from the org settings.We can start with a csv export before building a specific page for it.
example from Atlassian -
Provide customers with example prompts to get started quickly
HIGH
MCP prompts are explicitly defined as prompt templates that clients can discover and call with arguments.
See examples in table below.
Expose Jiminny as a Connector in Claude
medium
Competitors like Fathom are listed as Connectors in Claude. This will make it easier for customers to find us and to connect Jiminny
Provide customers with example workflows to get started quickly
medium
A workflow is usually multiple steps, maybe multiple tools, still focused on one outcome.
See examples in table below.
Allow customers to use predefined Jiminny skills for common workflows
medium
Anthropic describes Skills as folders that include instructions, scripts, and resources that Claude can load when relevant, and as a way to teach Claude repeatable workflows, preferences, and domain expertise once instead of re-explaining them every time. Skills - a reusable package of behavior that can include prompts, instructions, resources, and sometimes scripts/tools for a broader job.
Claude skills - https://resources.anthropic.com/hubfs/The-Complete-Guide-to-Building-Skill-for-Claude.pdf?hsLang=en&utm_source=chatgpt.com
See examples in table below.
Jiminny UI widget for OpenAI
medium
The reason to have this is to make certain Jiminny use cases much easier than pure chat.
Instead of ChatGPT only replying with text like “Here are the last 5 ACME calls,” it could also show a visual Jiminny card or mini-app inside the chat. That widget could list calls, show a deal summary, let the user filter by rep/date/account, open a transcript section, or save a snippet—while the conversation continues in normal chat alongside it.
For Jiminny, the best widget use cases are the ones where users need to browse or compare rather than ask one-off questions. A strong example is deal review: the user asks ChatGPT, “What is the status of the ACME deal?” ChatGPT calls your Jiminny MCP tools, and the widget shows a compact deal view with recent calls, risks, next steps, stakeholders, and links to transcripts/snippets. The chat can still summarize the answer in words, but the widget gives a clearer, scannable interface.
Another good Jiminny widget use case is call search and exploration. A text answer can say “I found 12 calls mentioning pricing objections,” but a widget could show a sortable list with date, rep, account, score, and objection count, then let the user click into one call to see the exact excerpt or jump to a transcript section.
Allow customers to run long-running analyses asynchronously and retrieve progress/results
low
Some requests/questions require analysis of Hugh volumes of data. For those, it may be better to:
start the job
let it run in the background
return a status like “in progress”
let the client come back for the result later
For example - User asks in Claude:
“Analyse all calls from this quarter and tell me the top 5 objections by segment.”
That might require:
searching lots of calls
pulling many summaries/transcripts
aggregating results
Instead of making Claude wait 45+ seconds, Jiminny could:
create an analysis job
return: job_id = 123, status = running
We need this in order to support:
large-scale analysis
multi-call aggregation across lots of data
playlist generation across many calls
heavy recap/report generation
Creating a snippet through the MCP
low
Create a shareable snippet from a call recording by specifying a time range. Useful for highlighting key moments — objection handling, pricing discussions, competitive mentions — and sharing them with your team.
example request:
{
"tool": "create_snippet",
"arguments": {
"call_id": "call_123",
"start_time": "00:18:24",
"end_time": "00:19:10",
"title": "Pricing objection"
}
}
example response:
{
"snippet_id": "snip_987",
"title": "Pricing objection",
"share_url": "https://app.jiminny.com/snippets/snip_987"
}
Ability to add recordings or snippets to a playlist
low
Allow customers to create libraries of calls automatically. They can use those for onboarding or other purposes
Allow AI tools to read reusable Jiminny resources
low
fathom
Resources are useful for data that should be read consistently rather than recomputed every time. In Jiminny terms, that could be:
current deal snapshot
account summary
weekly rep recap
approved talk tracks / objection handling guidance
curated playlists or snippet libraries
This is useful because an AI can consume these directly as context, instead of repeatedly stitching together many tool calls.
Ability to write coaching notes in Jiminny through MCP
low
What we want to do for prompts/worflows and skills
Capability
Type
User value / job to be done
Example Jiminny use case
Inputs
Steps performed
Output
Draft follow-up email
Prompt
Help reps quickly create tailored follow-ups after calls
Use the latest customer call to draft an email with recap and next steps
Call ID
optional tone
optional recipient type
Retrieve call summary and action items from Jiminny.
Pull key points, commitments, and next steps.
Apply the chosen tone and structure.
Draft the email in a consistent format.
Customer-ready follow-up email draft
Summarise call
Prompt
Help users quickly extract the most important points from a conversation
Generate a concise summary of one call for internal or external use
Call ID
optional summary style
optional audience
Retrieve transcript, metadata, and structured insights.
Identify key topics, decisions, risks, and next steps.
Format output for the chosen audience.
Short or structured call summary with actions and risks
Generate deal recap
Prompt
Help reps and managers get a fast overview of a deal
Summarise the current state of a deal based on recent calls and linked CRM context
Deal ID or account name
optional date range
Retrieve calls and meetings linked to the deal.
Pull deal metadata and CRM-linked context.
Identify recent changes, blockers, risks, and next steps.
Summarise into a concise recap.
Deal recap with status, blockers, risks, and recommended next steps
Prepare weekly recap
Prompt
Help managers or reps review what changed over a time period
Weekly recap of calls, themes, and actions for one rep, team, or account
Rep ID
team ID or account ID
time period
Retrieve relevant calls and summaries for the selected time period.
Aggregate themes, action items, and changes.
Highlight notable risks, opportunities, and follow-ups.
Weekly recap with top themes, risks, opportunities, and actions
Prepare deal review
Workflow
Help reps and managers review deal status using multiple sources of context
Review a deal before pipeline review or forecast meeting
Deal ID
optional date range
Retrieve all recent calls, emails, and meetings tied to the deal.
Pull structured call summaries, score, action items, and key points.
Pull linked CRM context such as stage, contacts, and account details.
Aggregate open risks, unresolved objections, stakeholder gaps, and next steps.
Format into a review-ready structure.
Deal review document with current status, risks, stakeholders, blockers, and next steps
Weekly team recap
Workflow
Help managers monitor activity and risk across a group of reps or accounts
End-of-week team summary for sales leadership
Team ID
date range
Retrieve calls and structured insights across the team.
Group by rep, account, or deal.
Identify recurring themes, major risks, strong calls, and missed follow-ups.
Highlight calls or deals that need attention.
Team-level recap with patterns, key risks, notable wins, and action areas
Objection analysis across calls
Workflow
Help teams identify patterns across multiple conversations
Analyse pricing or competitor objections across recent calls
Account ID
deal ID
rep ID
keyword/topic
date range
Search calls matching the topic or keyword.
Retrieve summaries, transcripts, and snippets where relevant.
Identify recurring objections and how they were handled.
Assess whether objections were resolved or remain open.
Summarise patterns and examples.
Objection analysis with themes, frequency, examples, and suggested follow-up actions
Build onboarding playlist
Workflow
Help enablement teams curate useful learning content faster
Build a playlist of strong discovery, demo, or pricing calls for new hires
Topic
call type
rep/team filter
optional time period
Search for calls matching the selected criteria.
Rank or filter calls based on score, topics, or key moments.
Identify useful snippets or full recordings.
Add selected calls/snippets into a playlist structure.
Generate short descriptions for each item.
Curated onboarding playlist with selected calls/snippets and descriptions
Deal Inspection Skill
Skill
Give users a consistent, opinionated way to assess a deal
Claude reviews a deal using a repeatable Jiminny methodology
Deal ID or account name
optional review scope
Determine whether the request is suitable for a deal inspection.
Retrieve relevant calls, summaries, CRM context, stakeholders, and risks.
Apply a standard Jiminny review framework to assess deal health.
Look for missing next steps, unresolved objections, stakeholder gaps, and warning signs.
Present findings in a consistent structure with recommended actions.
Structured deal inspection with health assessment, red flags, and recommendations
Manager Coaching Skill
Skill
Help managers review calls consistently and identify coaching moments
Analyse a rep’s call and surface strengths, gaps, and examples for coaching
Call ID
optional rep ID
optional coaching focus
Retrieve transcript, score, summary, and key moments from the call.
Evaluate the conversation against a coaching framework.
Identify what went well and where the rep could improve.
Suggest moments to clip as snippets.
Recommend coaching actions or playlist additions.
Coaching review with strengths, gaps, snippet suggestions, and recommended coaching actions
CSM / QBR Prep Skill
Skill
Help CS or AM teams prepare structured customer reviews from conversations
Generate an account review or QBR-style summary from recent customer interactions
Account ID, optional time period
Retrieve all recent calls, emails, and account-linked context.
Aggregate themes, requests, blockers, sentiment shifts, and opportunities.
Apply a repeatable account review structure.
Summarise outcomes, open issues, and suggested next steps.
Structured QBR/account review summary with themes, risks, opportunities, and actions
Snippet Builder Skill
Skill
Help users consistently capture and label useful moments from calls
Identify useful moments in a call and convert them into reusable snippets
Call ID, optional focus area such as pricing, objection, competitor, discovery
Retrieve transcript, recording timeline, and call insights.
Detect moments matching the requested focus area.
Propose snippet start/end times and titles.
Tag snippets by type or theme.
Optionally save them or add them to a playlist.
One or more proposed or saved snippets with title, timing, and tags
💡 Technical details
Auth model needs specifying. Are API keys scoped per user, per team, or per Jiminny instance? If a key is generated by an admin, does it inherit their visibility level, or provide org-wide? Are permissions evaluated at query time or frozen at key creation? Needs to be query-time, otherwise permission changes won't propagate.
Key lifecycle management is missing. No mention of rotation, expiry, or revocation. A departed employee's active key is a data leak. Need: revocation, optional expiry, alerts on stale keys, and consider whether keys should be tied to service accounts rather than personal users.
Rate limiting should be HIGH. A compromised key or misconfigured automation could bulk-export an entire customer's call history. Need per-key rate limits and anomaly detection on unusual access patterns.
Open Questions
Track unresolved issues or decisions that need to be made. Update as answers become available.
Question
Answer
Date Answered
Competitor research
Competitor
MCP Availability
Core Capabilities
Advanced Capabilities
Positioning
Key Strength
Key Weakness
Gong
✅ Mature MCP
List/search calls
Get transcripts
get Call metadata
Deal intelligence
Scorecards, analytics
CRM context
Enterprise data layer
Deep data + ecosystem integrations
Limited opinionated AI workflows
Avoma
✅ Mature MCP
list_meetings
get_meeting
get_transcript
key topics
Deal fields/Deal level analysis
Coaching/Scoring
CRM context
pushing insights into Notion / Confluence
AI-ready meeting intelligence
Strongest “outputs” layer
Mostly pull-based interactions
Fathom
✅ MCP
list/search meetings
get transcript
get summary/action items
Team/org context
Webhooks (event-based triggers)
get_weekly_recap
aggregated action items across meetings
creating webhooks directly from the MCP server
Lightweight meeting data access
Includes summaries + actions
Limited analytics depth
Grain
✅ Basic MCP
get meetings
download transcripts
Notes
Deals
Scorecards
Data access utility
Simple + accessible
Low sophistication, sometimes browser-based
Outreach
⚠️ MCP (workflow-focused)
Search sequences
Emails
Meetings (Kaia)
account / prospect / opportunity lookups
Workflow automation
Multi-system orchestration
Revenue workflow engine
End-to-end GTM workflows
Less depth in conversation data
Attention
⚠️ Emerging MCP
Meeting data
Transcripts
CRM-linked context
AI insights
Sales assistant workflows
create snippets
AI sales assistant + CRM
Strong CRM linkage
Less focus on external knowledge layer
Planhat -
Related content
Ask Jiminny Anything on Call level
Galya Dimitrova
Hubspot app
Galya Dimitrova
Product Vision & Strategy
Galya Dimitrova
Automated CRM Filling
Simona Georgieva (Deactivated)
Competitive analysis
Galya Dimitrova
AI agent ideas
Steliyan Georgiev
Comments
James Graham
9 Apr
A few areas around Security & Compliance that need more depth before this moves beyond draft:
Auth model needs specifying. Are API keys scoped per user, per team, or per Jiminny instance? If a key is generated by an admin, does it inherit their visibility level, or provide org-wide? Are permissions evaluated at query time or frozen at key creation? Needs to be query-time, otherwise permission changes won't propagate.
Team visibility enforcement should be its own HIGH requirement. The current note under access control ("ensure MCP only exposes data user has access to") is doing too much work as a single line. Every MCP tool response (especially search_calls and deal-level aggregations) must be filtered through the same visibility engine as the UI. Semantic search is the riskiest here; it could surface results across team boundaries if not properly scoped....
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Objective Enable customers to connect Jiminny data to external AI tools (Claude, OpenAI, Gemini) so it can be used as part of their broader knowledge base and workflows. Position Jiminny as a data layer for AI-driven revenue workflows, not just a standalone product. 👤 Target user Revenue teams using AI tools (Sales, CS, RevOps) Companies already experimenting with Claude / OpenAI Mid-market & Enterprise customers with multiple data sources (CRM, docs, CI tools, Support tools etc) 🤕 Pain point or problem Jiminny data is locked in the platform AI tools lack access to high-value conversation context Customers must manually export/copy transcripts No easy way to combine calls with CRM + docs + other info - using the Jiminny API is not suitable for non technical sales people Peer pressure as almost all competitors have this 💥 Impact and benefits For customers Better AI outputs using real customer conversations Ability to build automated workflows across tools For Jiminny Increased product stickiness (embedded in workflows) Competitive parity with Gong / Avoma etc. 💡 Solution ideas Build an AI Knowledge Connector (MCP-based) that: Exposes Jiminny data (calls, transcripts, metadata) to AI tools Provides structured insights (summaries, action items, scoring etc.) Supports deal-level context Allows integration into customer-owned AI stacks (Claude + Zapier, etc.) Success metrics List the key goals and how you will measure success. Include both qualitative and quantitative metrics (e.g., user adoption, retention rate, revenue targets). Goal Metric Increase stickiness by ensuring Jiminny is embedded in the customer’s workflows % of customers connecting external AI tools Number of MCP/API calls per customer - and which ones are being used the most Decrease the manual copying of transcripts decrease by X % User interaction and design Simple setup flow: Generate API key / connect MCP Clear instructions for Claude / Zapier setup Provide: Example prompts for Claude Pre-built workflow templates for Zapier Clear documentation - with use cases 👉 Focus: usable by non-technical users Detailed Requirements List the functional and non-functional requirements. Prioritize them (e.g., High, Medium, Low) and add notes for clarification. Requirement Importance Notes Allow customers to connect Jiminny to their AI tools (e.g. Claude, OpenAI) HIGH Provide MCP endpoint so customers can easily integrate Jiminny into their AI stack Allow customers to access call data through AI tools HIGH Expose Jiminny data: list calls (filter by date, user, account, deal) get call get transcript (speaker-separated) get call metadata search calls (keyword + semantic) Support filtering by: account / contact/ lead / deal jiminny user date range Allow customers to search and query calls using AI tools HIGH Support keyword and semantic search across conversations Provide structured insights so customers can generate better outputs HIGH For each call, expose: Summary Action items Key points Activity type Notes Call Score CRM information Allow customers to understand deal status across multiple calls/emails HIGH For each deal expose: calls/meetings/emails Identified risks contacts related to the deal with their job title linked account details all CRM field information that we have in DI + fields used for CRM filling example - get_deal_summary request - { \"tool\": \"get_deal_summary\", \"arguments\": { \"deal_name\": \"ACME\" } } responce: { \"deal_name\": \"ACME\", \"stage\": \"Negotiation\", \"recent_activity\": [ \"Demo call on 2026-04-01\", \"Pricing discussion on 2026-04-03\" ], \"risks\": [ \"Pricing concerns\", \"Security review pending\" ], \"next_steps\": [ \"Send follow-up to VP Sales\", \"Share security documentation\" ] } Ensure the AI can easily understand the schema of the data coming from Jiminny HIGH Models perform much better when tools have: clear names rich descriptions predictable schemas Provide clear, actionable error states for customers when MCP connections fail HIGH Error messages should guide agents toward solutions with specific suggestions and next steps. Expired or revoked key — “Error: Authentication failed. The API key used to access Jiminny has been revoked or has expired. Please ask your Jiminny admin to generate a new API key in Settings > Organization > General and reconnect the MCP server.” Rate limit hit — “Error: Rate limit exceeded. Too many requests have been made to the Jiminny MCP server in a short period. Please wait 60 seconds before retrying.” Permissions mismatch — if a user tries to access data outside their team visibility settings - “Error: Access denied. The requested call (call_id: [X]) is outside your team's visibility settings in Jiminny. Only calls within your permitted scope are accessible.” Trying to access private meeting - “Error: Access denied. This meeting has been marked as private by the host and cannot be accessed through the MCP connector. Try requesting a different call or ask the meeting host to change the visibility settings in Jiminny.” Downgraded/Capture account — if a customer's plan drops below Scale tier or the Customer is on Capture in the first place - “Error: MCP access unavailable. The Jiminny MCP connector is available on the Scale plan and above. Your account does not currently have an active Scale subscription.” Jiminny-side outage — “Error:Jiminny is temporarily unavailable (status 503). This is not a data or permissions issue — please retry in a few minutes.” No data found - “Error:No calls found matching your criteria. Try adjusting your filters — for example, widening the date range, removing the account filter, or checking the rep name is spelled correctly in Jiminny.” Allow customers to securely control who and what data is accessible externally HIGH Ensure MCP only exposes data user has access to - based on team visibility settings. This means that if a user is not allow to access calls/deals in Jiminny UI then they shouldn’t be able to access those through the MCP as well. Private meetings shouldn’t be exposed via MCP HIGH When a meetings is set to Private then the information about it shouldn’t be exposed through the MCP. Ensure Jiminny data can be combined with other sources (e.g. CRM, docs) in AI workflows HIGH Ensure data is structured to be easily combined with: CRM (accounts, deals) external docs Use consistent identifiers: account IDs deal IDs MCP is available only for Scale tier and above HIGH Customers who are on Capture tier should be able to access any of their data through MCP. This should also cover the scenario when a customer has been on Scale but then downgrades to Capture - their MCP access should stop working. Provide visibility into how external AI tools access Jiminny data HIGH Audit logs: what data was accessed by which external system when identity - who made the request specific queries/filters used failed access attempts (especially cross-visibility-boundary attempts) Admins should be able to access the logs from the org settings.We can start with a csv export before building a specific page for it. example from Atlassian - Provide customers with example prompts to get started quickly HIGH MCP prompts are explicitly defined as prompt templates that clients can discover and call with arguments. See examples in table below. Expose Jiminny as a Connector in Claude medium Competitors like Fathom are listed as Connectors in Claude. This will make it easier for customers to find us and to connect Jiminny Provide customers with example workflows to get started quickly medium A workflow is usually multiple steps, maybe multiple tools, still focused on one outcome. See examples in table below. Allow customers to use predefined Jiminny skills for common workflows medium Anthropic describes Skills as folders that include instructions, scripts, and resources that Claude can load when relevant, and as a way to teach Claude repeatable workflows, preferences, and domain expertise once instead of re-explaining them every time. Skills - a reusable package of behavior that can include prompts, instructions, resources, and sometimes scripts/tools for a broader job. Claude skills - https://resources.anthropic.com/hubfs/The-Complete-Guide-to-Building-Skill-for-Claude.pdf?hsLang=en&utm_source=chatgpt.com See examples in table below. Jiminny UI widget for OpenAI medium The reason to have this is to make certain Jiminny use cases much easier than pure chat. Instead of ChatGPT only replying with text like “Here are the last 5 ACME calls,” it could also show a visual Jiminny card or mini-app inside the chat. That widget could list calls, show a deal summary, let the user filter by rep/date/account, open a transcript section, or save a snippet—while the conversation continues in normal chat alongside it. For Jiminny, the best widget use cases are the ones where users need to browse or compare rather than ask one-off questions. A strong example is deal review: the user asks ChatGPT, “What is the status of the ACME deal?” ChatGPT calls your Jiminny MCP tools, and the widget shows a compact deal view with recent calls, risks, next steps, stakeholders, and links to transcripts/snippets. The chat can still summarize the answer in words, but the widget gives a clearer, scannable interface. Another good Jiminny widget use case is call search and exploration. A text answer can say “I found 12 calls mentioning pricing objections,” but a widget could show a sortable list with date, rep, account, score, and objection count, then let the user click into one call to see the exact excerpt or jump to a transcript section. Allow customers to run long-running analyses asynchronously and retrieve progress/results low Some requests/questions require analysis of Hugh volumes of data. For those, it may be better to: start the job let it run in the background return a status like “in progress” let the client come back for the result later For example - User asks in Claude: “Analyse all calls from this quarter and tell me the top 5 objections by segment.” That might require: searching lots of calls pulling many summaries/transcripts aggregating results Instead of making Claude wait 45+ seconds, Jiminny could: create an analysis job return: job_id = 123, status = running We need this in order to support: large-scale analysis multi-call aggregation across lots of data playlist generation across many calls heavy recap/report generation Creating a snippet through the MCP low Create a shareable snippet from a call recording by specifying a time range. Useful for highlighting key moments — objection handling, pricing discussions, competitive mentions — and sharing them with your team. example request: { \"tool\": \"create_snippet\", \"arguments\": { \"call_id\": \"call_123\", \"start_time\": \"00:18:24\", \"end_time\": \"00:19:10\", \"title\": \"Pricing objection\" } } example response: { \"snippet_id\": \"snip_987\", \"title\": \"Pricing objection\", \"share_url\": \"https://app.jiminny.com/snippets/snip_987\" } Ability to add recordings or snippets to a playlist low Allow customers to create libraries of calls automatically. They can use those for onboarding or other purposes Allow AI tools to read reusable Jiminny resources low fathom Resources are useful for data that should be read consistently rather than recomputed every time. In Jiminny terms, that could be: current deal snapshot account summary weekly rep recap approved talk tracks / objection handling guidance curated playlists or snippet libraries This is useful because an AI can consume these directly as context, instead of repeatedly stitching together many tool calls. Ability to write coaching notes in Jiminny through MCP low What we want to do for prompts/worflows and skills Capability Type User value / job to be done Example Jiminny use case Inputs Steps performed Output Draft follow-up email Prompt Help reps quickly create tailored follow-ups after calls Use the latest customer call to draft an email with recap and next steps Call ID optional tone optional recipient type Retrieve call summary and action items from Jiminny. Pull key points, commitments, and next steps. Apply the chosen tone and structure. Draft the email in a consistent format. Customer-ready follow-up email draft Summarise call Prompt Help users quickly extract the most important points from a conversation Generate a concise summary of one call for internal or external use Call ID optional summary style optional audience Retrieve transcript, metadata, and structured insights. Identify key topics, decisions, risks, and next steps. Format output for the chosen audience. Short or structured call summary with actions and risks Generate deal recap Prompt Help reps and managers get a fast overview of a deal Summarise the current state of a deal based on recent calls and linked CRM context Deal ID or account name optional date range Retrieve calls and meetings linked to the deal. Pull deal metadata and CRM-linked context. Identify recent changes, blockers, risks, and next steps. Summarise into a concise recap. Deal recap with status, blockers, risks, and recommended next steps Prepare weekly recap Prompt Help managers or reps review what changed over a time period Weekly recap of calls, themes, and actions for one rep, team, or account Rep ID team ID or account ID time period Retrieve relevant calls and summaries for the selected time period. Aggregate themes, action items, and changes. Highlight notable risks, opportunities, and follow-ups. Weekly recap with top themes, risks, opportunities, and actions Prepare deal review Workflow Help reps and managers review deal status using multiple sources of context Review a deal before pipeline review or forecast meeting Deal ID optional date range Retrieve all recent calls, emails, and meetings tied to the deal. Pull structured call summaries, score, action items, and key points. Pull linked CRM context such as stage, contacts, and account details. Aggregate open risks, unresolved objections, stakeholder gaps, and next steps. Format into a review-ready structure. Deal review document with current status, risks, stakeholders, blockers, and next steps Weekly team recap Workflow Help managers monitor activity and risk across a group of reps or accounts End-of-week team summary for sales leadership Team ID date range Retrieve calls and structured insights across the team. Group by rep, account, or deal. Identify recurring themes, major risks, strong calls, and missed follow-ups. Highlight calls or deals that need attention. Team-level recap with patterns, key risks, notable wins, and action areas Objection analysis across calls Workflow Help teams identify patterns across multiple conversations Analyse pricing or competitor objections across recent calls Account ID deal ID rep ID keyword/topic date range Search calls matching the topic or keyword. Retrieve summaries, transcripts, and snippets where relevant. Identify recurring objections and how they were handled. Assess whether objections were resolved or remain open. Summarise patterns and examples. Objection analysis with themes, frequency, examples, and suggested follow-up actions Build onboarding playlist Workflow Help enablement teams curate useful learning content faster Build a playlist of strong discovery, demo, or pricing calls for new hires Topic call type rep/team filter optional time period Search for calls matching the selected criteria. Rank or filter calls based on score, topics, or key moments. Identify useful snippets or full recordings. Add selected calls/snippets into a playlist structure. Generate short descriptions for each item. Curated onboarding playlist with selected calls/snippets and descriptions Deal Inspection Skill Skill Give users a consistent, opinionated way to assess a deal Claude reviews a deal using a repeatable Jiminny methodology Deal ID or account name optional review scope Determine whether the request is suitable for a deal inspection. Retrieve relevant calls, summaries, CRM context, stakeholders, and risks. Apply a standard Jiminny review framework to assess deal health. Look for missing next steps, unresolved objections, stakeholder gaps, and warning signs. Present findings in a consistent structure with recommended actions. Structured deal inspection with health assessment, red flags, and recommendations Manager Coaching Skill Skill Help managers review calls consistently and identify coaching moments Analyse a rep’s call and surface strengths, gaps, and examples for coaching Call ID optional rep ID optional coaching focus Retrieve transcript, score, summary, and key moments from the call. Evaluate the conversation against a coaching framework. Identify what went well and where the rep could improve. Suggest moments to clip as snippets. Recommend coaching actions or playlist additions. Coaching review with strengths, gaps, snippet suggestions, and recommended coaching actions CSM / QBR Prep Skill Skill Help CS or AM teams prepare structured customer reviews from conversations Generate an account review or QBR-style summary from recent customer interactions Account ID, optional time period Retrieve all recent calls, emails, and account-linked context. Aggregate themes, requests, blockers, sentiment shifts, and opportunities. Apply a repeatable account review structure. Summarise outcomes, open issues, and suggested next steps. Structured QBR/account review summary with themes, risks, opportunities, and actions Snippet Builder Skill Skill Help users consistently capture and label useful moments from calls Identify useful moments in a call and convert them into reusable snippets Call ID, optional focus area such as pricing, objection, competitor, discovery Retrieve transcript, recording timeline, and call insights. Detect moments matching the requested focus area. Propose snippet start/end times and titles. Tag snippets by type or theme. Optionally save them or add them to a playlist. One or more proposed or saved snippets with title, timing, and tags 💡 Technical details Auth model needs specifying. Are API keys scoped per user, per team, or per Jiminny instance? If a key is generated by an admin, does it inherit their visibility level, or provide org-wide? Are permissions evaluated at query time or frozen at key creation? Needs to be query-time, otherwise permission changes won't propagate. Key lifecycle management is missing. No mention of rotation, expiry, or revocation. A departed employee's active key is a data leak. Need: revocation, optional expiry, alerts on stale keys, and consider whether keys should be tied to service accounts rather than personal users. Rate limiting should be HIGH. A compromised key or misconfigured automation could bulk-export an entire customer's call history. Need per-key rate limits and anomaly detection on unusual access patterns. Open Questions Track unresolved issues or decisions that need to be made. Update as answers become available. Question Answer Date Answered Competitor research Competitor MCP Availability Core Capabilities Advanced Capabilities Positioning Key Strength Key Weakness Gong ✅ Mature MCP List/search calls Get transcripts get Call metadata Deal intelligence Scorecards, analytics CRM context Enterprise data layer Deep data + ecosystem integrations Limited opinionated AI workflows Avoma ✅ Mature MCP list_meetings get_meeting get_transcript key topics Deal fields/Deal level analysis Coaching/Scoring CRM context pushing insights into Notion / Confluence AI-ready meeting intelligence Strongest “outputs” layer Mostly pull-based interactions Fathom ✅ MCP list/search meetings get transcript get summary/action items Team/org context Webhooks (event-based triggers) get_weekly_recap aggregated action items across meetings creating webhooks directly from the MCP server Lightweight meeting data access Includes summaries + actions Limited analytics depth Grain ✅ Basic MCP get meetings download transcripts Notes Deals Scorecards Data access utility Simple + accessible Low sophistication, sometimes browser-based Outreach ⚠️ MCP (workflow-focused) Search sequences Emails Meetings (Kaia) account / prospect / opportunity lookups Workflow automation Multi-system orchestration Revenue workflow engine End-to-end GTM workflows Less depth in conversation data Attention ⚠️ Emerging MCP Meeting data Transcripts CRM-linked context AI insights Sales assistant workflows create snippets AI sales assistant + CRM Strong CRM linkage Less focus on external knowledge layer Planhat - Related content Ask Jiminny Anything on Call level Galya Dimitrova Hubspot app Galya Dimitrova Product Vision & Strategy Galya Dimitrova Automated CRM Filling Simona Georgieva (Deactivated) Competitive analysis Galya Dimitrova AI agent ideas Steliyan Georgiev Comments James Graham 9 Apr A few areas around Security & Compliance that need more depth before this moves beyond draft: Auth model needs specifying. Are API keys scoped per user, per team, or per Jiminny instance? If a key is generated by an admin, does it inherit their visibility level, or provide org-wide? Are permissions evaluated at query time or frozen at key creation? Needs to be query-time, otherwise permission changes won't propagate. Team visibility enforcement should be its own HIGH requirement. The current note under access control (\"ensure MCP only exposes data user has access to\") is doing too much work as a single line. Every MCP tool response (especially search_calls and deal-level aggregations) must be filtered through the same visibility engine as the UI. Semantic search is the riskiest here; it could surface results across team boundaries if not properly scoped. No data minimisation or scoping controls. We're exposing transcripts, CRM fields, contact details with job titles, deal context - significant PII and commercial data leaving the platform. Can customers configure which data types are exposed? Can transcripts be PII-stripped before they leave Jiminny? Given we position GDPR consent as a differentiator, we should be thinking about this. GDPR downstream processing is unaddressed. Piping transcripts to OpenAI/Gemini introduces new data processors. Customers need to acknowledge responsibility for downstream processing during setup. We should also consider whether call participants' recording consent covers onward sharing to third-party AI - it almost certainly doesn't by default. This is one for me to pick up. Key lifecycle management is missing. No mention of rotation, expiry, or revocation. A departed employee's active key is a data leak. Need: revocation, optional expiry, alerts on stale keys, and consider whether keys should be tied to service accounts rather than personal users. Rate limiting should be HIGH. A compromised key or misconfigured automation could bulk-export an entire customer's call history. Need per-key rate limits and anomaly detection on unusual access patterns. Audit logs should go deeper. Current spec (what data, which system, when) is a start. Add: identity behind the key, specific queries/filters used, and failed access attempts (especially cross-visibility-boundary attempts). Enterprise compliance teams will expect this. Downgrade handling. Doc says Scale tier and above, but doesn't say what happens on downgrade. Keys should auto-deactivate. Happy to help draft a dedicated Security & Compliance section if useful. Galya Dimitrova 15 Apr Thanks for the input @James Graham . I made the product related changes in the table and for the rest I left them as a note in the Technical section for the team to look at when they start looking at this. I wonder about your points related to GDPR. Currently multiple customers are using the Customer API/zapier to feed this data to AI and BI tools. They are also manually exporting transcripts and other information from the platform and feeding it to AI tools. 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This meeting has been marked as private by the host and cannot be accessed through the MCP connector. Try requesting a different call or ask the meeting host to change the visibility settings in Jiminny.”","depth":23,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"Downgraded/Capture account — if a customer's plan drops below Scale tier or the Customer is on Capture in the first place - “Error: MCP access unavailable. The Jiminny MCP connector is available on the Scale plan and above. Your account does not currently have an active Scale subscription.”","depth":23,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"Jiminny-side outage — “Error:Jiminny is temporarily unavailable (status 503). This is not a data or permissions issue — please retry in a few minutes.”","depth":23,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"No data found - “Error:No calls found matching your criteria. Try adjusting your filters — for example, widening the date range, removing the account filter, or checking the rep name is spelled correctly in Jiminny.”","depth":23,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"Allow customers to securely control who and what data is accessible externally","depth":23,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"HIGH","depth":23,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"Ensure MCP only exposes data user has access to - based on team visibility settings. This means that if a user is not allow to access calls/deals in Jiminny UI then they shouldn’t be able to access those through the MCP as well.","depth":23,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"Private meetings shouldn’t be exposed via MCP","depth":23,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"HIGH","depth":23,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"When a meetings is set to Private then the information about it shouldn’t be exposed through the MCP.","depth":23,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"Ensure Jiminny data can be combined with other sources (e.g. CRM, docs) in AI workflows","depth":23,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"HIGH","depth":23,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"Ensure data is structured to be easily combined with:","depth":23,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"CRM (accounts, deals)","depth":23,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"external docs","depth":23,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"Use consistent identifiers:","depth":23,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"account IDs","depth":23,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"deal IDs","depth":23,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"MCP is available only for Scale tier and above","depth":23,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"HIGH","depth":23,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"Customers who are on Capture tier should be able to access any of their data through MCP.","depth":23,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"This should also cover the scenario when a customer has been on Scale but then downgrades to Capture - their MCP access should stop working.","depth":23,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"Provide visibility into how external AI tools access Jiminny data","depth":23,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"HIGH","depth":23,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"Audit logs:","depth":23,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"what data was accessed by which external system when","depth":23,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"identity - who made the request","depth":23,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"specific queries/filters used","depth":23,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"failed access attempts (especially cross-visibility-boundary attempts)","depth":23,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"Admins should be able to access the logs from the org settings.We can start with a csv export before building a specific page for it.","depth":23,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"example from Atlassian -","depth":23,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"Provide customers with example prompts to get started quickly","depth":23,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"HIGH","depth":23,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"MCP prompts are explicitly defined as prompt templates that clients can discover and call with arguments.","depth":23,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"See examples in table below.","depth":23,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"Expose Jiminny as a Connector in Claude","depth":23,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"medium","depth":23,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"Competitors like Fathom are listed as Connectors in Claude. This will make it easier for customers to find us and to connect Jiminny","depth":23,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"Provide customers with example workflows to get started quickly","depth":23,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"medium","depth":23,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"A workflow is usually multiple steps, maybe multiple tools, still focused on one outcome.","depth":23,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"See examples in table below.","depth":23,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"Allow customers to use predefined Jiminny skills for common workflows","depth":23,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"medium","depth":23,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"Anthropic describes Skills as folders that include instructions, scripts, and resources that Claude can load when relevant, and as a way to teach Claude repeatable workflows, preferences, and domain expertise once instead of re-explaining them every time. Skills - a reusable package of behavior that can include prompts, instructions, resources, and sometimes scripts/tools for a broader job.","depth":23,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"Claude skills - https://resources.anthropic.com/hubfs/The-Complete-Guide-to-Building-Skill-for-Claude.pdf?hsLang=en&utm_source=chatgpt.com","depth":23,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"See examples in table below.","depth":23,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"Jiminny UI widget for OpenAI","depth":23,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"medium","depth":23,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"The reason to have this is to make certain Jiminny use cases much easier than pure chat.","depth":23,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"Instead of ChatGPT only replying with text like “Here are the last 5 ACME calls,” it could also show a visual Jiminny card or mini-app inside the chat. That widget could list calls, show a deal summary, let the user filter by rep/date/account, open a transcript section, or save a snippet—while the conversation continues in normal chat alongside it.","depth":23,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"For Jiminny, the best widget use cases are the ones where users need to browse or compare rather than ask one-off questions. A strong example is deal review: the user asks ChatGPT, “What is the status of the ACME deal?” ChatGPT calls your Jiminny MCP tools, and the widget shows a compact deal view with recent calls, risks, next steps, stakeholders, and links to transcripts/snippets. The chat can still summarize the answer in words, but the widget gives a clearer, scannable interface.","depth":23,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"Another good Jiminny widget use case is call search and exploration. A text answer can say “I found 12 calls mentioning pricing objections,” but a widget could show a sortable list with date, rep, account, score, and objection count, then let the user click into one call to see the exact excerpt or jump to a transcript section.","depth":23,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"Allow customers to run long-running analyses asynchronously and retrieve progress/results","depth":23,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"low","depth":23,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"Some requests/questions require analysis of Hugh volumes of data. For those, it may be better to:","depth":23,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"start the job","depth":23,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"let it run in the background","depth":23,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"return a status like “in progress”","depth":23,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"let the client come back for the result later","depth":23,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"For example - User asks in Claude:","depth":23,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"“Analyse all calls from this quarter and tell me the top 5 objections by segment.”","depth":23,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"That might require:","depth":23,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"searching lots of calls","depth":23,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"pulling many summaries/transcripts","depth":23,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"aggregating results","depth":23,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"Instead of making Claude wait 45+ seconds, Jiminny could:","depth":23,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"create an analysis job","depth":23,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"return: job_id = 123, status = running","depth":23,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"We need this in order to support:","depth":23,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"large-scale analysis","depth":23,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"multi-call aggregation across lots of data","depth":23,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"playlist generation across many calls","depth":23,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"heavy recap/report generation","depth":23,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"Creating a snippet through the MCP","depth":23,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"low","depth":23,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"Create a shareable snippet from a call recording by specifying a time range. Useful for highlighting key moments — objection handling, pricing discussions, competitive mentions — and sharing them with your team.","depth":23,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"example request:","depth":23,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"{","depth":23,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"\"tool\": \"create_snippet\",","depth":23,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"\"arguments\": {","depth":23,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"\"call_id\": \"call_123\",","depth":23,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"\"start_time\": \"00:18:24\",","depth":23,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"\"end_time\": \"00:19:10\",","depth":23,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"\"title\": \"Pricing objection\"","depth":23,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"}","depth":23,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"}","depth":23,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"example response:","depth":23,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"{","depth":23,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"\"snippet_id\": \"snip_987\",","depth":23,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"\"title\": \"Pricing objection\",","depth":23,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"\"share_url\": \"https://app.jiminny.com/snippets/snip_987\"","depth":23,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"}","depth":23,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"Ability to add recordings or snippets to a playlist","depth":23,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"low","depth":23,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"Allow customers to create libraries of calls automatically. They can use those for onboarding or other purposes","depth":23,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"Allow AI tools to read reusable Jiminny resources","depth":23,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"low","depth":23,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"fathom","depth":23,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"Resources are useful for data that should be read consistently rather than recomputed every time. In Jiminny terms, that could be:","depth":23,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"current deal snapshot","depth":23,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"account summary","depth":23,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"weekly rep recap","depth":23,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"approved talk tracks / objection handling guidance","depth":23,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"curated playlists or snippet libraries","depth":23,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"This is useful because an AI can consume these directly as context, instead of repeatedly stitching together many tool calls.","depth":23,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"Ability to write coaching notes in Jiminny through MCP","depth":23,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"low","depth":23,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"What we want to do for prompts/worflows and skills","depth":23,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"Capability","depth":23,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"Type","depth":23,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"User value / job to be done","depth":23,"help_text":"","role_description":"text","subrole":"AXUnknown"},{"role":"AXStaticText","text":"Example Jiminny use 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Platform Sprint 2 Q2 - Platform Team - Scrum Board Platform Sprint 2 Q2 - Platform Team - Scrum Board - Jira
SevenShores\Hubspot\Exceptions\BadRequest: Client error: `POST [URL_WITH_CREDENTIALS] Graham . I made the product related changes in the table and for the rest I left them as a note in the Technical section for the team to look at when they start looking at this. I wonder about your points related to GDPR. Currently multiple customers are using the Customer API/zapier to feed this data to AI and BI tools. They are also manually exporting transcripts and other information from the platform and feeding it to AI tools. I don’t get how MCP is so much different that all of these and why it will introduce new data processors (which are already being utilised) and would require any changes to the consent provided by participants.
You said
Jiminny MCP Connector
Epic
Link to Epik in Jira
Document status
DRAFT
Objective
Enable customers to connect Jiminny data to external AI tools (Claude, OpenAI, Gemini) so it can be used as part of their broader knowledge base and workflows.
Position Jiminny as a data layer for AI-driven revenue workflows, not just a standalone product.
👤 Target user
Revenue teams using AI tools (Sales, CS, RevOps)
Companies already experimenting with Claude / OpenAI
Mid-market & Enterprise customers with multiple data sources (CRM, docs, CI tools, Support tools etc)
🤕 Pain point or problem
Jiminny data is locked in the platform
AI tools lack access to high-value conversation context
Customers must manually export/copy transcripts
No easy way to combine calls with CRM + docs + other info - using the Jiminny API is not suitable for non technical sales people
Peer pressure as almost all competitors have this
💥 Impact and benefits
For customers
Better AI outputs using real customer conversations
Ability to build automated workflows across tools
For Jiminny
Increased product stickiness (embedded in workflows)
Competitive parity with Gong / Avoma etc.
💡 Solution ideas
Build an AI Knowledge Connector (MCP-based) that:
Exposes Jiminny data (calls, transcripts, metadata) to AI tools
Provides structured insights (summaries, action items, scoring etc.)
Supports deal-level context
Allows integration into customer-owned AI stacks (Claude + Zapier, etc.)
Success metrics
List the key goals and how you will measure success. Include both qualitative and quantitative metrics (e.g., user adoption, retention rate, revenue targets).
Goal
Metric
Increase stickiness by ensuring Jiminny is embedded in the customer’s workflows
% of customers connecting external AI tools
Number of MCP/API calls per customer - and which ones are being used the most
Decrease the manual copying of transcripts
decrease by X %
User interaction and design
Simple setup flow:
Generate API key / connect MCP
Clear instructions for Claude / Zapier setup
Provide:
Example prompts for Claude
Pre-built workflow templates for Zapier
Clear documentation - with use cases
👉 Focus: usable by non-technical users
Detailed Requirements
List the functional and non-functional requirements. Prioritize them (e.g., High, Medium, Low) and add notes for clarification.
Requirement
Importance
Notes
Allow customers to connect Jiminny to their AI tools (e.g. Claude, OpenAI)
HIGH
Provide MCP endpoint so customers can easily integrate Jiminny into their AI stack
Allow customers to access call data through AI tools
HIGH
Expose Jiminny data:
list calls (filter by date, user, account, deal)
get call
get transcript (speaker-separated)
get call metadata
search calls (keyword + semantic)
Support filtering by:
account / contact/ lead / deal
jiminny user
date range
Allow customers to search and query calls using AI tools
HIGH
Support keyword and semantic search across conversations
Provide structured insights so customers can generate better outputs
HIGH
For each call, expose:
Summary
Action items
Key points
Activity type
Notes
Call Score
CRM information
Allow customers to understand deal status across multiple calls/emails
HIGH
For each deal expose:
calls/meetings/emails
Identified risks
contacts related to the deal with their job title
linked account details
all CRM field information that we have in DI + fields used for CRM filling
example - get_deal_summary
request -
{
"tool": "get_deal_summary",
"arguments": {
"deal_name": "ACME"
}
}
responce:
{
"deal_name": "ACME",
"stage": "Negotiation",
"recent_activity": [
"Demo call on 2026-04-01",
"Pricing discussion on 2026-04-03"
],
"risks": [
"Pricing concerns",
"Security review pending"
], "next_steps": [
"Send follow-up to VP Sales",
"Share security documentation"
]
}
Ensure the AI can easily understand the schema of the data coming from Jiminny
HIGH
Models perform much better when tools have:
clear names
rich descriptions
predictable schemas
Provide clear, actionable error states for customers when MCP connections fail
HIGH
Error messages should guide agents toward solutions with specific suggestions and next steps.
Expired or revoked key — “Error: Authentication failed. The API key used to access Jiminny has been revoked or has expired. Please ask your Jiminny admin to generate a new API key in Settings > Organization > General and reconnect the MCP server.”
Rate limit hit — “Error: Rate limit exceeded. Too many requests have been made to the Jiminny MCP server in a short period. Please wait 60 seconds before retrying.”
Permissions mismatch — if a user tries to access data outside their team visibility settings - “Error: Access denied. The requested call (call_id: [X]) is outside your team's visibility settings in Jiminny. Only calls within your permitted scope are accessible.”
Trying to access private meeting - “Error: Access denied. This meeting has been marked as private by the host and cannot be accessed through the MCP connector. Try requesting a different call or ask the meeting host to change the visibility settings in Jiminny.”
Downgraded/Capture account — if a customer's plan drops below Scale tier or the Customer is on Capture in the first place - “Error: MCP access unavailable. The Jiminny MCP connector is available on the Scale plan and above. Your account does not currently have an active Scale subscription.”
Jiminny-side outage — “Error:Jiminny is temporarily unavailable (status 503). This is not a data or permissions issue — please retry in a few minutes.”
No data found - “Error:No calls found matching your criteria. Try adjusting your filters — for example, widening the date range, removing the account filter, or checking the rep name is spelled correctly in Jiminny.”
Allow customers to securely control who and what data is accessible externally
HIGH
Ensure MCP only exposes data user has access to - based on team visibility settings. This means that if a user is not allow to access calls/deals in Jiminny UI then they shouldn’t be able to access those through the MCP as well.
Private meetings shouldn’t be exposed via MCP
HIGH
When a meetings is set to Private then the information about it shouldn’t be exposed through the MCP.
Ensure Jiminny data can be combined with other sources (e.g. CRM, docs) in AI workflows
HIGH
Ensure data is structured to be easily combined with:
CRM (accounts, deals)
external docs
Use consistent identifiers:
account IDs
deal IDs
MCP is available only for Scale tier and above
HIGH
Customers who are on Capture tier should be able to access any of their data through MCP.
This should also cover the scenario when a customer has been on Scale but then downgrades to Capture - their MCP access should stop working.
Provide visibility into how external AI tools access Jiminny data
HIGH
Audit logs:
what data was accessed by which external system when
identity - who made the request
specific queries/filters used
failed access attempts (especially cross-visibility-boundary attempts)
Admins should be able to access the logs from the org settings.We can start with a csv export before building a specific page for it.
example from Atlassian -
Provide customers with example prompts to get started quickly
HIGH
MCP prompts are explicitly defined as prompt templates that clients can discover and call with arguments.
See examples in table below.
Expose Jiminny as a Connector in Claude
medium
Competitors like Fathom are listed as Connectors in Claude. This will make it easier for customers to find us and to connect Jiminny
Provide customers with example workflows to get started quickly
medium
A workflow is usually multiple steps, maybe multiple tools, still focused on one outcome.
See examples in table below.
Allow customers to use predefined Jiminny skills for common workflows
medium
Anthropic describes Skills as folders that include instructions, scripts, and resources that Claude can load when relevant, and as a way to teach Claude repeatable workflows, preferences, and domain expertise once instead of re-explaining them every time. Skills - a reusable package of behavior that can include prompts, instructions, resources, and sometimes scripts/tools for a broader job.
Claude skills - https://resources.anthropic.com/hubfs/The-Complete-Guide-to-Building-Skill-for-Claude.pdf?hsLang=en&utm_source=chatgpt.com
See examples in table below.
Jiminny UI widget for OpenAI
medium
The reason to have this is to make certain Jiminny use cases much easier than pure chat.
Instead of ChatGPT only replying with text like “Here are the last 5 ACME calls,” it could also show a visual Jiminny card or mini-app inside the chat. That widget could list calls, show a deal summary, let the user filter by rep/date/account, open a transcript section, or save a snippet—while the conversation continues in normal chat alongside it.
For Jiminny, the best widget use cases are the ones where users need to browse or compare rather than ask one-off questions. A strong example is deal review: the user asks ChatGPT, “What is the status of the ACME deal?” ChatGPT calls your Jiminny MCP tools, and the widget shows a compact deal view with recent calls, risks, next steps, stakeholders, and links to transcripts/snippets. The chat can still summarize the answer in words, but the widget gives a clearer, scannable interface.
Another good Jiminny widget use case is call search and exploration. A text answer can say “I found 12 calls mentioning pricing objections,” but a widget could show a sortable list with date, rep, account, score, and objection count, then let the user click into one call to see the exact excerpt or jump to a transcript section.
Allow customers to run long-running analyses asynchronously and retrieve progress/results
low
Some requests/questions require analysis of Hugh volumes of data. For those, it may be better to:
start the job
let it run in the background
return a status like “in progress”
let the client come back for the result later
For example - User asks in Claude:
“Analyse all calls from this quarter and tell me the top 5 objections by segment.”
That might require:
searching lots of calls
pulling many summaries/transcripts
aggregating results
Instead of making Claude wait 45+ seconds, Jiminny could:
create an analysis job
return: job_id = 123, status = running
We need this in order to support:
large-scale analysis
multi-call aggregation across lots of data
playlist generation across many calls
heavy recap/report generation
Creating a snippet through the MCP
low
Create a shareable snippet from a call recording by specifying a time range. Useful for highlighting key moments — objection handling, pricing discussions, competitive mentions — and sharing them with your team.
example request:
{
"tool": "create_snippet",
"arguments": {
"call_id": "call_123",
"start_time": "00:18:24",
"end_time": "00:19:10",
"title": "Pricing objection"
}
}
example response:
{
"snippet_id": "snip_987",
"title": "Pricing objection",
"share_url": "https://app.jiminny.com/snippets/snip_987"
}
Ability to add recordings or snippets to a playlist
low
Allow customers to create libraries of calls automatically. They can use those for onboarding or other purposes
Allow AI tools to read reusable Jiminny resources
low
fathom
Resources are useful for data that should be read consistently rather than recomputed every time. In Jiminny terms, that could be:
current deal snapshot
account summary
weekly rep recap
approved talk tracks / objection handling guidance
curated playlists or snippet libraries
This is useful because an AI can consume these directly as context, instead of repeatedly stitching together many tool calls.
Ability to write coaching notes in Jiminny through MCP
low
What we want to do for prompts/worflows and skills
Capability
Type
User value / job to be done
Example Jiminny use case
Inputs
Steps performed
Output
Draft follow-up email
Prompt
Help reps quickly create tailored follow-ups after calls
Use the latest customer call to draft an email with recap and next steps
Call ID
optional tone
optional recipient type
Retrieve call summary and action items from Jiminny.
Pull key points, commitments, and next steps.
Apply the chosen tone and structure.
Draft the email in a consistent format.
Customer-ready follow-up email draft
Summarise call
Prompt
Help users quickly extract the most important points from a conversation
Generate a concise summary of one call for internal or external use
Call ID
optional summary style
optional audience
Retrieve transcript, metadata, and structured insights.
Identify key topics, decisions, risks, and next steps.
Format output for the chosen audience.
Short or structured call summary with actions and risks
Generate deal recap
Prompt
Help reps and managers get a fast overview of a deal
Summarise the current state of a deal based on recent calls and linked CRM context
Deal ID or account name
optional date range
Retrieve calls and meetings linked to the deal.
Pull deal metadata and CRM-linked context.
Identify recent changes, blockers, risks, and next steps.
Summarise into a concise recap.
Deal recap with status, blockers, risks, and recommended next steps
Prepare weekly recap
Prompt
Help managers or reps review what changed over a time period
Weekly recap of calls, themes, and actions for one rep, team, or account
Rep ID
team ID or account ID
time period
Retrieve relevant calls and summaries for the selected time period.
Aggregate themes, action items, and changes.
Highlight notable risks, opportunities, and follow-ups.
Weekly recap with top themes, risks, opportunities, and actions
Prepare deal review
Workflow
Help reps and managers review deal status using multiple sources of context
Review a deal before pipeline review or forecast meeting
Deal ID
optional date range
Retrieve all recent calls, emails, and meetings tied to the deal.
Pull structured call summaries, score, action items, and key points.
Pull linked CRM context such as stage, contacts, and account details.
Aggregate open risks, unresolved objections, stakeholder gaps, and next steps.
Format into a review-ready structure.
Deal review document with current status, risks, stakeholders, blockers, and next steps
Weekly team recap
Workflow
Help managers monitor activity and risk across a group of reps or accounts
End-of-week team summary for sales leadership
Team ID
date range
Retrieve calls and structured insights across the team.
Group by rep, account, or deal.
Identify recurring themes, major risks, strong calls, and missed follow-ups.
Highlight calls or deals that need attention.
Team-level recap with patterns, key risks, notable wins, and action areas
Objection analysis across calls
Workflow
Help teams identify patterns across multiple conversations
Analyse pricing or competitor objections across recent calls
Account ID
deal ID
rep ID
keyword/topic
date range
Search calls matching the topic or keyword.
Retrieve summaries, transcripts, and snippets where relevant.
Identify recurring objections and how they were handled.
Assess whether objections were resolved or remain open.
Summarise patterns and examples.
Objection analysis with themes, frequency, examples, and suggested follow-up actions
Build onboarding playlist
Workflow
Help enablement teams curate useful learning content faster
Build a playlist of strong discovery, demo, or pricing calls for new hires
Topic
call type
rep/team filter
optional time period
Search for calls matching the selected criteria.
Rank or filter calls based on score, topics, or key moments.
Identify useful snippets or full recordings.
Add selected calls/snippets into a playlist structure.
Generate short descriptions for each item.
Curated onboarding playlist with selected calls/snippets and descriptions
Deal Inspection Skill
Skill
Give users a consistent, opinionated way to assess a deal
Claude reviews a deal using a repeatable Jiminny methodology
Deal ID or account name
optional review scope
Determine whether the request is suitable for a deal inspection.
Retrieve relevant calls, summaries, CRM context, stakeholders, and risks.
Apply a standard Jiminny review framework to assess deal health.
Look for missing next steps, unresolved objections, stakeholder gaps, and warning signs.
Present findings in a consistent structure with recommended actions.
Structured deal inspection with health assessment, red flags, and recommendations
Manager Coaching Skill
Skill
Help managers review calls consistently and identify coaching moments
Analyse a rep’s call and surface strengths, gaps, and examples for coaching
Call ID
optional rep ID
optional coaching focus
Retrieve transcript, score, summary, and key moments from the call.
Evaluate the conversation against a coaching framework.
Identify what went well and where the rep could improve.
Suggest moments to clip as snippets.
Recommend coaching actions or playlist additions.
Coaching review with strengths, gaps, snippet suggestions, and recommended coaching actions
CSM / QBR Prep Skill
Skill
Help CS or AM teams prepare structured customer reviews from conversations
Generate an account review or QBR-style summary from recent customer interactions
Account ID, optional time period
Retrieve all recent calls, emails, and account-linked context.
Aggregate themes, requests, blockers, sentiment shifts, and opportunities.
Apply a repeatable account review structure.
Summarise outcomes, open issues, and suggested next steps.
Structured QBR/account review summary with themes, risks, opportunities, and actions
Snippet Builder Skill
Skill
Help users consistently capture and label useful moments from calls
Identify useful moments in a call and convert them into reusable snippets
Call ID, optional focus area such as pricing, objection, competitor, discovery
Retrieve transcript, recording timeline, and call insights.
Detect moments matching the requested focus area.
Propose snippet start/end times and titles.
Tag snippets by type or theme.
Optionally save them or add them to a playlist.
One or more proposed or saved snippets with title, timing, and tags
💡 Technical details
Auth model needs specifying. Are API keys scoped per user, per team, or per Jiminny instance? If a key is generated by an admin, does it inherit their visibility level, or provide org-wide? Are permissions evaluated at query time or frozen at key creation? Needs to be query-time, otherwise permission changes won't propagate.
Key lifecycle management is missing. No mention of rotation, expiry, or revocation. A departed employee's active key is a data leak. Need: revocation, optional expiry, alerts on stale keys, and consider whether keys should be tied to service accounts rather than personal users.
Rate limiting should be HIGH. A compromised key or misconfigured automation could bulk-export an entire customer's call history. Need per-key rate limits and anomaly detection on unusual access patterns.
Open Questions
Track unresolved issues or decisions that need to be made. Update as answers become available.
Question
Answer
Date Answered
Competitor research
Competitor
MCP Availability
Core Capabilities
Advanced Capabilities
Positioning
Key Strength
Key Weakness
Gong
✅ Mature MCP
List/search calls
Get transcripts
get Call metadata
Deal intelligence
Scorecards, analytics
CRM context
Enterprise data layer
Deep data + ecosystem integrations
Limited opinionated AI workflows
Avoma
✅ Mature MCP
list_meetings
get_meeting
get_transcript
key topics
Deal fields/Deal level analysis
Coaching/Scoring
CRM context
pushing insights into Notion / Confluence
AI-ready meeting intelligence
Strongest “outputs” layer
Mostly pull-based interactions
Fathom
✅ MCP
list/search meetings
get transcript
get summary/action items
Team/org context
Webhooks (event-based triggers)
get_weekly_recap
aggregated action items across meetings
creating webhooks directly from the MCP server
Lightweight meeting data access
Includes summaries + actions
Limited analytics depth
Grain
✅ Basic MCP
get meetings
download transcripts
Notes
Deals
Scorecards
Data access utility
Simple + accessible
Low sophistication, sometimes browser-based
Outreach
⚠️ MCP (workflow-focused)
Search sequences
Emails
Meetings (Kaia)
account / prospect / opportunity lookups
Workflow automation
Multi-system orchestration
Revenue workflow engine
End-to-end GTM workflows
Less depth in conversation data
Attention
⚠️ Emerging MCP
Meeting data
Transcripts
CRM-linked context
AI insights
Sales assistant workflows
create snippets
AI sales assistant + CRM
Strong CRM linkage
Less focus on external knowledge layer
Planhat -
Related content
Ask Jiminny Anything on Call level
Galya Dimitrova
Hubspot app
Galya Dimitrova
Product Vision & Strategy
Galya Dimitrova
Automated CRM Filling
Simona Georgieva (Deactivated)
Competitive analysis
Galya Dimitrova
AI agent ideas
Steliyan Georgiev
Comments
James Graham
9 Apr
A few areas around Security & Compliance that need more depth before this moves beyond draft:
Auth model needs specifying. Are API keys scoped per user, per team, or per Jiminny instance? If a key is generated by an admin, does it inherit their visibility level, or provide org-wide? Are permissions evaluated at query time or frozen at key creation? Needs to be query-time, otherwise permission changes won't propagate.
Team visibility enforcement should be its own HIGH requirement. The current note under access control ("ensure MCP only exposes data user has access to") is doing too much work as a single line. Every MCP tool response (especially search_calls and deal-level aggregations) must be filtered through the same visibility engine as the UI. Semantic search is the riskiest here; it could surface results across team boundaries if not properly scoped....
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DXP4800PLUS-B5F8
Inbox (7) - [EMAIL] - Gmail
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(56) Inbox | [EMAIL] | Proton Mail
Welcome back
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Western Digital Red Plus 3.5 6TB 5400rpm 256MB SATA3 (WD60EFPX) от 241,72 € (472,76 лв.) Вътрешен хард диск Western Digital - Pazaruvaj.com
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Today's Deals
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architecture - screenpipe docs
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Claude Code works better when you stop treating it like a machine - [EMAIL] - Gmail
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Screenpipe — Archive
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SQLite Web: archive.db
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Hey @louis030195 Ill check during my - screenpipe.com
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GitHub - screenpipe/screenpipe: Run agents that work for you based on what you do. AI finally knows what you are doing · GitHub
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Gong Pricing in 2026: Costs, Plans & Is It Worth It?
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GLM 5.1 Thinks Strategically, Data-Center Revolt Intensifies, When Helpful LLMs Turn Unhelpful, Humanoid Robots Get to Work - [EMAIL] - Gmail
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3223284272476174312
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-3677481664530842751
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visual_change
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accessibility
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NULL
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DXP4800PLUS-B5F8
Inbox (7) - [EMAIL] - Gmail
(56) DXP4800PLUS-B5F8
Inbox (7) - [EMAIL] - Gmail
(56) Inbox | [EMAIL] | Proton Mail
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Welcome back
Western Digital Red Plus 3.5 6TB 5400rpm 256MB SATA3 (WD60EFPX) от 241,72 € (472,76 лв.) Вътрешен хард диск Western Digital - Pazaruvaj.com
Western Digital Red Plus 3.5 6TB 5400rpm 256MB SATA3 (WD60EFPX) от 241,72 € (472,76 лв.) Вътрешен хард диск Western Digital - Pazaruvaj.com
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Today's Deals
architecture - screenpipe docs
architecture - screenpipe docs
Claude Code works better when you stop treating it like a machine - [EMAIL] - Gmail
Claude Code works better when you stop treating it like a machine - [EMAIL] - Gmail
Screenpipe — Archive
Screenpipe — Archive
SQLite Web: archive.db
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SQLite Web: db.sqlite
SQLite Web: db.sqlite
Claude Platform
Claude Platform
Hey @louis030195 Ill check during my - screenpipe.com
Hey @louis030195 Ill check during my - screenpipe.com
GitHub - screenpipe/screenpipe: Run agents that work for you based on what you do. AI finally knows what you are doing · GitHub
GitHub - screenpipe/screenpipe: Run agents that work for you based on what you do. AI finally knows what you are doing · GitHub
Gong Pricing in 2026: Costs, Plans & Is It Worth It?
Gong Pricing in 2026: Costs, Plans & Is It Worth It?
GLM 5.1 Thinks Strategically, Data-Center Revolt Intensifies, When Helpful LLMs Turn Unhelpful, Humanoid Robots Get to Work - [EMAIL] - Gmail
GLM 5.1 Thinks Strategically, Data-Center Revolt Intensifies, When Helpful LLMs Turn Unhelpful, Humanoid Robots Get to Work - [EMAIL] - Gmail
Gitea Official Website
Gitea Official Website
lakylak/screenpipe - screenpipe - Gitea: Git with a cup of tea
lakylak/screenpipe - screenpipe - Gitea: Git with a cup of tea
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Product page for netPower Lite 8P
NEW
netPower Lite 8P
$199.00
*
SFP/SFP+
PoE
Outdoors
IP 54
Low-cost. Tough. And always ON! Compact PoE switch with built-in UPS and smart battery charger – because your CCTV cameras and access points deserve true off-the-grid resilience.
Product page for CRS804 DDQ
NEW
CRS804 DDQ
$1,295.00
*
400G
10G
ARM64
Quad-core CPU
ROS v7
A compact 1U 400G switch built for AI clusters, storage fabrics, and high-speed aggregation, featuring four 400G QSFP56-DD ports, dual 10 Gigabit Ethernet, and RouterOS v7. With hot-swap power supplies, robust cooling, and low power consumption, it delivers ultra-high bandwidth, wire-speed performance, and future-proof scalability at an accessible price point.
Product page for CRS304-4XG-IN
CRS304-4XG-IN
$199.00
*
10G
PoE
ARM64
ROS v7
Compact, powerful, and ready to simplify your 10 Gigabit network setups with 4x10G Ethernet ports ready to use out-of-the-box. No extra modules needed!
Product page for CRS305-1G-4S+IN
CRS305-1G-4S+IN
$149.00
*
SFP/SFP+
PoE
ARM
Five-port desktop switch with one Gigabit Ethernet port and four SFP+ 10Gbps ports
Product page for CRS312-4C+8XG-RM
CRS312-4C+8XG-RM
$699.00
*
10G
Combo ports
ROS v7
Switch of the future: the first MikroTik product with 10G RJ45 Ethernet ports and SFP+
Product page for CRS320-8P-8B-4S+RM
CRS320-8P-8B-4S+RM
$489.00
*
SFP/SFP+
PoE
ARM
ROS v7
The first MikroTik high-power PoE++ switch – for easy and cost-effective powering of industry standard 802.3af/at/bt devices. Forget about countless power cables – create a cleaner space with PoE++!
Product page for CRS317-1G-16S+RM
CRS317-1G-16S+RM
$499.00
*
SFP/SFP+
ARM
Smart Switch, 1 x Gigabit LAN, 16 x SFP+ cages, Dual Core 800MHz CPU, 1GB RAM, 1U rackmount passive cooling case, Dual Power Supplies
Product page for CRS309-1G-8S+IN
CRS309-1G-8S+IN
$269.00
*
SFP/SFP+
PoE
ARM
Desktop switch with one Gigabit Ethernet port and eight SFP+ 10Gbps ports
Product page for CRS518-16XS-2XQ-RM
CRS518-16XS-2XQ-RM
$1,595.00
*
100G
ROS v7
A 100 Gigabit switch for enterprise networks and data centers. Hot-swappable parts and insane port density with 1.2 Tbps switching capacity!
Product page for CRS310-1G-5S-4S+IN
CRS310-1G-5S-4S+IN
$199.00
*
SFP/SFP+
PoE
ARM
ROS v7
10 Gigabit fibre connectivity way over a 100 meters – for small offices or ISPs. Hardware offloaded VLAN-filtering and even some L3 routing on a budget!
Product page for CRS310-8G+2S+IN
CRS310-8G+2S+IN
$219.00
*
SFP/SFP+
2.5G
ARM
ROS v7
Take advantage of the blazing fast 2.5/10 Gigabit combo and upgrade your workspace! This switch can utilize the full potential of RouterOS v7: run VLANs, Jumbo frames, link aggregation, ACL rules, and so much more!
Product page for netPower 16P
netPower 16P
$279.00
*
SFP/SFP+
PoE
ARM
Outdoors
IP 54
An outdoor 18 port switch with 16 Gigabit PoE-out ports and 2 SFP+. Power all your access points anywhere!
Product page for netPower 15FR
netPower 15FR
$169.00
*
SFP/SFP+
PoE
ARM
Outdoors
IP 54
An outdoor 18 port switch with 15 reverse PoE ports and SFP. Cut costs, not speed – choose GPEN over GPON!
Product page for netFiber 9
netFiber 9
$249.00
*
SFP/SFP+
PoE
ARM
Outdoors
IP 54
ROS v7
A remarkable outdoor switch for setting up an optical 10G network that can even perform some light routing. The spiritual successor to the beloved FiberBox. Gigabit Ethernet, SFP/SFP+, PoE.
Product page for CRS326-24G-2S+IN
CRS326-24G-2S+IN
$199.00
*
SFP/SFP+
PoE
ARM...
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DXP4800PLUS-B5F8
Inbox (7) - [EMAIL] - Gmail
(56) DXP4800PLUS-B5F8
Inbox (7) - [EMAIL] - Gmail
(56) Inbox | [EMAIL] | Proton Mail
Welcome back
Welcome back
Western Digital Red Plus 3.5 6TB 5400rpm 256MB SATA3 (WD60EFPX) от 241,72 € (472,76 лв.) Вътрешен хард диск Western Digital - Pazaruvaj.com
Western Digital Red Plus 3.5 6TB 5400rpm 256MB SATA3 (WD60EFPX) от 241,72 € (472,76 лв.) Вътрешен хард диск Western Digital - Pazaruvaj.com
Today's Deals
Today's Deals
architecture - screenpipe docs
architecture - screenpipe docs
Claude Code works better when you stop treating it like a machine - [EMAIL] - Gmail
Claude Code works better when you stop treating it like a machine - [EMAIL] - Gmail
Screenpipe — Archive
Screenpipe — Archive
SQLite Web: archive.db
SQLite Web: archive.db
SQLite Web: db.sqlite
SQLite Web: db.sqlite
Claude Platform
Claude Platform
Hey @louis030195 Ill check during my - screenpipe.com
Hey @louis030195 Ill check during my - screenpipe.com
GitHub - screenpipe/screenpipe: Run agents that work for you based on what you do. AI finally knows what you are doing · GitHub
GitHub - screenpipe/screenpipe: Run agents that work for you based on what you do. AI finally knows what you are doing · GitHub
Gong Pricing in 2026: Costs, Plans & Is It Worth It?
Gong Pricing in 2026: Costs, Plans & Is It Worth It?
GLM 5.1 Thinks Strategically, Data-Center Revolt Intensifies, When Helpful LLMs Turn Unhelpful, Humanoid Robots Get to Work - [EMAIL] - Gmail
GLM 5.1 Thinks Strategically, Data-Center Revolt Intensifies, When Helpful LLMs Turn Unhelpful, Humanoid Robots Get to Work - [EMAIL] - Gmail
Gitea Official Website
Gitea Official Website
lakylak/screenpipe - screenpipe - Gitea: Git with a cup of tea
lakylak/screenpipe - screenpipe - Gitea: Git with a cup of tea
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MikroTik · Switches
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Product page for netPower Lite 8P
NEW
netPower Lite 8P
$199.00
*
SFP/SFP+
PoE
Outdoors
IP 54
Low-cost. Tough. And always ON! Compact PoE switch with built-in UPS and smart battery charger – because your CCTV cameras and access points deserve true off-the-grid resilience.
Product page for CRS804 DDQ
NEW
CRS804 DDQ
$1,295.00
*
400G
10G
ARM64
Quad-core CPU
ROS v7
A compact 1U 400G switch built for AI clusters, storage fabrics, and high-speed aggregation, featuring four 400G QSFP56-DD ports, dual 10 Gigabit Ethernet, and RouterOS v7. With hot-swap power supplies, robust cooling, and low power consumption, it delivers ultra-high bandwidth, wire-speed performance, and future-proof scalability at an accessible price point.
Product page for CRS304-4XG-IN
CRS304-4XG-IN
$199.00
*
10G
PoE
ARM64
ROS v7
Compact, powerful, and ready to simplify your 10 Gigabit network setups with 4x10G Ethernet ports ready to use out-of-the-box. No extra modules needed!
Product page for CRS305-1G-4S+IN
CRS305-1G-4S+IN
$149.00
*
SFP/SFP+
PoE
ARM
Five-port desktop switch with one Gigabit Ethernet port and four SFP+ 10Gbps ports
Product page for CRS312-4C+8XG-RM
CRS312-4C+8XG-RM
$699.00
*
10G
Combo ports
ROS v7
Switch of the future: the first MikroTik product with 10G RJ45 Ethernet ports and SFP+
Product page for CRS320-8P-8B-4S+RM
CRS320-8P-8B-4S+RM
$489.00
*
SFP/SFP+
PoE
ARM
ROS v7
The first MikroTik high-power PoE++ switch – for easy and cost-effective powering of industry standard 802.3af/at/bt devices. Forget about countless power cables – create a cleaner space with PoE++!
Product page for CRS317-1G-16S+RM
CRS317-1G-16S+RM
$499.00
*
SFP/SFP+
ARM
Smart Switch, 1 x Gigabit LAN, 16 x SFP+ cages, Dual Core 800MHz CPU, 1GB RAM, 1U rackmount passive cooling case, Dual Power Supplies
Product page for CRS309-1G-8S+IN
CRS309-1G-8S+IN
$269.00
*
SFP/SFP+
PoE
ARM
Desktop switch with one Gigabit Ethernet port and eight SFP+ 10Gbps ports
Product page for CRS518-16XS-2XQ-RM
CRS518-16XS-2XQ-RM
$1,595.00
*
100G
ROS v7
A 100 Gigabit switch for enterprise networks and data centers. Hot-swappable parts and insane port density with 1.2 Tbps switching capacity!
Product page for CRS310-1G-5S-4S+IN
CRS310-1G-5S-4S+IN
$199.00
*
SFP/SFP+
PoE
ARM
ROS v7
10 Gigabit fibre connectivity way over a 100 meters – for small offices or ISPs. Hardware offloaded VLAN-filtering and even some L3 routing on a budget!
Product page for CRS310-8G+2S+IN
CRS310-8G+2S+IN
$219.00
*
SFP/SFP+
2.5G
ARM
ROS v7
Take advantage of the blazing fast 2.5/10 Gigabit combo and upgrade your workspace! This switch can utilize the full potential of RouterOS v7: run VLANs, Jumbo frames, link aggregation, ACL rules, and so much more!
Product page for netPower 16P
netPower 16P
$279.00
*
SFP/SFP+
PoE
ARM
Outdoors
IP 54
An outdoor 18 port switch with 16 Gigabit PoE-out ports and 2 SFP+. Power all your access points anywhere!
Product page for netPower 15FR
netPower 15FR
$169.00
*
SFP/SFP+
PoE
ARM
Outdoors
IP 54
An outdoor 18 port switch with 15 reverse PoE ports and SFP. Cut costs, not speed – choose GPEN over GPON!
Product page for netFiber 9
netFiber 9
$249.00
*
SFP/SFP+
PoE
ARM
Outdoors
IP 54
ROS v7
A remarkable outdoor switch for setting up an optical 10G network that can even perform some light routing. The spiritual successor to the beloved FiberBox. Gigabit Ethernet, SFP/SFP+, PoE.
Product page for CRS326-24G-2S+IN
CRS326-24G-2S+IN
$199.00
*
SFP/SFP+
PoE
ARM
24 Gigabit ports, 2 SFP+ cages and a desktop case – server room power for your home!
Product page for CRS326-24G-2S+RM
CRS326-24G-2S+RM
$209.00
*
SFP/SFP+
PoE
ARM
24 Gigabit port switch with 2 x SFP+ cages in 1U rackmount case, Dual boot (RouterOS or SwitchOS)
Product page for CRS326-24S+2Q+RM
CRS326-24S+2Q+RM
$599.00
*
SFP/SFP+
40G
ROS v7
One of our faster switches for the most demanding setups.
Product page for CRS326-4C+20G+2Q+RM
CRS326-4C+20G+2Q+RM
$999.00
*
40G
2.5G
Combo ports
ROS v7...
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1768209930431276201
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-4253942588431369343
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visual_change
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accessibility
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NULL
|
DXP4800PLUS-B5F8
Inbox (7) - [EMAIL] - Gmail
(56) DXP4800PLUS-B5F8
Inbox (7) - [EMAIL] - Gmail
(56) Inbox | [EMAIL] | Proton Mail
Welcome back
Welcome back
Western Digital Red Plus 3.5 6TB 5400rpm 256MB SATA3 (WD60EFPX) от 241,72 € (472,76 лв.) Вътрешен хард диск Western Digital - Pazaruvaj.com
Western Digital Red Plus 3.5 6TB 5400rpm 256MB SATA3 (WD60EFPX) от 241,72 € (472,76 лв.) Вътрешен хард диск Western Digital - Pazaruvaj.com
Today's Deals
Today's Deals
architecture - screenpipe docs
architecture - screenpipe docs
Claude Code works better when you stop treating it like a machine - [EMAIL] - Gmail
Claude Code works better when you stop treating it like a machine - [EMAIL] - Gmail
Screenpipe — Archive
Screenpipe — Archive
SQLite Web: archive.db
SQLite Web: archive.db
SQLite Web: db.sqlite
SQLite Web: db.sqlite
Claude Platform
Claude Platform
Hey @louis030195 Ill check during my - screenpipe.com
Hey @louis030195 Ill check during my - screenpipe.com
GitHub - screenpipe/screenpipe: Run agents that work for you based on what you do. AI finally knows what you are doing · GitHub
GitHub - screenpipe/screenpipe: Run agents that work for you based on what you do. AI finally knows what you are doing · GitHub
Gong Pricing in 2026: Costs, Plans & Is It Worth It?
Gong Pricing in 2026: Costs, Plans & Is It Worth It?
GLM 5.1 Thinks Strategically, Data-Center Revolt Intensifies, When Helpful LLMs Turn Unhelpful, Humanoid Robots Get to Work - [EMAIL] - Gmail
GLM 5.1 Thinks Strategically, Data-Center Revolt Intensifies, When Helpful LLMs Turn Unhelpful, Humanoid Robots Get to Work - [EMAIL] - Gmail
Gitea Official Website
Gitea Official Website
lakylak/screenpipe - screenpipe - Gitea: Git with a cup of tea
lakylak/screenpipe - screenpipe - Gitea: Git with a cup of tea
New Tab
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Product page for netPower Lite 8P
NEW
netPower Lite 8P
$199.00
*
SFP/SFP+
PoE
Outdoors
IP 54
Low-cost. Tough. And always ON! Compact PoE switch with built-in UPS and smart battery charger – because your CCTV cameras and access points deserve true off-the-grid resilience.
Product page for CRS804 DDQ
NEW
CRS804 DDQ
$1,295.00
*
400G
10G
ARM64
Quad-core CPU
ROS v7
A compact 1U 400G switch built for AI clusters, storage fabrics, and high-speed aggregation, featuring four 400G QSFP56-DD ports, dual 10 Gigabit Ethernet, and RouterOS v7. With hot-swap power supplies, robust cooling, and low power consumption, it delivers ultra-high bandwidth, wire-speed performance, and future-proof scalability at an accessible price point.
Product page for CRS304-4XG-IN
CRS304-4XG-IN
$199.00
*
10G
PoE
ARM64
ROS v7
Compact, powerful, and ready to simplify your 10 Gigabit network setups with 4x10G Ethernet ports ready to use out-of-the-box. No extra modules needed!
Product page for CRS305-1G-4S+IN
CRS305-1G-4S+IN
$149.00
*
SFP/SFP+
PoE
ARM
Five-port desktop switch with one Gigabit Ethernet port and four SFP+ 10Gbps ports
Product page for CRS312-4C+8XG-RM
CRS312-4C+8XG-RM
$699.00
*
10G
Combo ports
ROS v7
Switch of the future: the first MikroTik product with 10G RJ45 Ethernet ports and SFP+
Product page for CRS320-8P-8B-4S+RM
CRS320-8P-8B-4S+RM
$489.00
*
SFP/SFP+
PoE
ARM
ROS v7
The first MikroTik high-power PoE++ switch – for easy and cost-effective powering of industry standard 802.3af/at/bt devices. Forget about countless power cables – create a cleaner space with PoE++!
Product page for CRS317-1G-16S+RM
CRS317-1G-16S+RM
$499.00
*
SFP/SFP+
ARM
Smart Switch, 1 x Gigabit LAN, 16 x SFP+ cages, Dual Core 800MHz CPU, 1GB RAM, 1U rackmount passive cooling case, Dual Power Supplies
Product page for CRS309-1G-8S+IN
CRS309-1G-8S+IN
$269.00
*
SFP/SFP+
PoE
ARM
Desktop switch with one Gigabit Ethernet port and eight SFP+ 10Gbps ports
Product page for CRS518-16XS-2XQ-RM
CRS518-16XS-2XQ-RM
$1,595.00
*
100G
ROS v7
A 100 Gigabit switch for enterprise networks and data centers. Hot-swappable parts and insane port density with 1.2 Tbps switching capacity!
Product page for CRS310-1G-5S-4S+IN
CRS310-1G-5S-4S+IN
$199.00
*
SFP/SFP+
PoE
ARM
ROS v7
10 Gigabit fibre connectivity way over a 100 meters – for small offices or ISPs. Hardware offloaded VLAN-filtering and even some L3 routing on a budget!
Product page for CRS310-8G+2S+IN
CRS310-8G+2S+IN
$219.00
*
SFP/SFP+
2.5G
ARM
ROS v7
Take advantage of the blazing fast 2.5/10 Gigabit combo and upgrade your workspace! This switch can utilize the full potential of RouterOS v7: run VLANs, Jumbo frames, link aggregation, ACL rules, and so much more!
Product page for netPower 16P
netPower 16P
$279.00
*
SFP/SFP+
PoE
ARM
Outdoors
IP 54
An outdoor 18 port switch with 16 Gigabit PoE-out ports and 2 SFP+. Power all your access points anywhere!
Product page for netPower 15FR
netPower 15FR
$169.00
*
SFP/SFP+
PoE
ARM
Outdoors
IP 54
An outdoor 18 port switch with 15 reverse PoE ports and SFP. Cut costs, not speed – choose GPEN over GPON!
Product page for netFiber 9
netFiber 9
$249.00
*
SFP/SFP+
PoE
ARM
Outdoors
IP 54
ROS v7
A remarkable outdoor switch for setting up an optical 10G network that can even perform some light routing. The spiritual successor to the beloved FiberBox. Gigabit Ethernet, SFP/SFP+, PoE.
Product page for CRS326-24G-2S+IN
CRS326-24G-2S+IN
$199.00
*
SFP/SFP+
PoE
ARM
24 Gigabit ports, 2 SFP+ cages and a desktop case – server room power for your home!
Product page for CRS326-24G-2S+RM
CRS326-24G-2S+RM
$209.00
*
SFP/SFP+
PoE
ARM
24 Gigabit port switch with 2 x SFP+ cages in 1U rackmount case, Dual boot (RouterOS or SwitchOS)
Product page for CRS326-24S+2Q+RM
CRS326-24S+2Q+RM
$599.00
*
SFP/SFP+
40G
ROS v7
One of our faster switches for the most demanding setups.
Product page for CRS326-4C+20G+2Q+RM
CRS326-4C+20G+2Q+RM
$999.00
*
40G
2.5G
Combo ports
ROS v7...
|
NULL
|
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80867
|
2140
|
16
|
2026-04-25T15:08:21.537314+00:00
|
/Users/lukas/.screenpipe/data/data/2026-04-25/1777 /Users/lukas/.screenpipe/data/data/2026-04-25/1777129701537_m2.jpg...
|
Firefox
|
MikroTik · Switches — Personal
|
True
|
mikrotik.com/products/group/switches
|
monitor_2
|
NULL
|
NULL
|
NULL
|
NULL
|
DXP4800PLUS-B5F8
Inbox (7) - [EMAIL] - Gmail
(56) DXP4800PLUS-B5F8
Inbox (7) - [EMAIL] - Gmail
(56) Inbox | [EMAIL] | Proton Mail
Welcome back
Welcome back
Western Digital Red Plus 3.5 6TB 5400rpm 256MB SATA3 (WD60EFPX) от 241,72 € (472,76 лв.) Вътрешен хард диск Western Digital - Pazaruvaj.com
Western Digital Red Plus 3.5 6TB 5400rpm 256MB SATA3 (WD60EFPX) от 241,72 € (472,76 лв.) Вътрешен хард диск Western Digital - Pazaruvaj.com
Today's Deals
Today's Deals
architecture - screenpipe docs
architecture - screenpipe docs
Claude Code works better when you stop treating it like a machine - [EMAIL] - Gmail
Claude Code works better when you stop treating it like a machine - [EMAIL] - Gmail
Screenpipe — Archive
Screenpipe — Archive
SQLite Web: archive.db
SQLite Web: archive.db
SQLite Web: db.sqlite
SQLite Web: db.sqlite
Claude Platform
Claude Platform
Hey @louis030195 Ill check during my - screenpipe.com
Hey @louis030195 Ill check during my - screenpipe.com
GitHub - screenpipe/screenpipe: Run agents that work for you based on what you do. AI finally knows what you are doing · GitHub
GitHub - screenpipe/screenpipe: Run agents that work for you based on what you do. AI finally knows what you are doing · GitHub
Gong Pricing in 2026: Costs, Plans & Is It Worth It?
Gong Pricing in 2026: Costs, Plans & Is It Worth It?
GLM 5.1 Thinks Strategically, Data-Center Revolt Intensifies, When Helpful LLMs Turn Unhelpful, Humanoid Robots Get to Work - [EMAIL] - Gmail
GLM 5.1 Thinks Strategically, Data-Center Revolt Intensifies, When Helpful LLMs Turn Unhelpful, Humanoid Robots Get to Work - [EMAIL] - Gmail
Gitea Official Website
Gitea Official Website
lakylak/screenpipe - screenpipe - Gitea: Git with a cup of tea
lakylak/screenpipe - screenpipe - Gitea: Git with a cup of tea
New Tab
New Tab
MikroTik · Switches
MikroTik · Switches
Close tab
New Tab
Customize sidebar
Open Le Chat Mistral (⌃X)
Open history (⇧⌘H)
Open bookmarks (⌘B)
Bitwarden
Skip to main content
Skip to main content
Go to home page
HOME
HOME
HARDWARE
HARDWARE
SWITCHES
SWITCHES
Status
Status
Wired Interfaces
Wired Interfaces
Options Range
Options Range
Features
Features
Operating System
Operating System
Architecture
Architecture
Product page for netPower Lite 8P
NEW
netPower Lite 8P
$199.00
*
SFP/SFP+
PoE
Outdoors
IP 54
Low-cost. Tough. And always ON! Compact PoE switch with built-in UPS and smart battery charger – because your CCTV cameras and access points deserve true off-the-grid resilience.
Product page for CRS804 DDQ
NEW
CRS804 DDQ
$1,295.00
*
400G
10G
ARM64
Quad-core CPU
ROS v7
A compact 1U 400G switch built for AI clusters, storage fabrics, and high-speed aggregation, featuring four 400G QSFP56-DD ports, dual 10 Gigabit Ethernet, and RouterOS v7. With hot-swap power supplies, robust cooling, and low power consumption, it delivers ultra-high bandwidth, wire-speed performance, and future-proof scalability at an accessible price point.
Product page for CRS304-4XG-IN
CRS304-4XG-IN
$199.00
*
10G
PoE
ARM64
ROS v7
Compact, powerful, and ready to simplify your 10 Gigabit network setups with 4x10G Ethernet ports ready to use out-of-the-box. No extra modules needed!
Product page for CRS305-1G-4S+IN
CRS305-1G-4S+IN
$149.00
*
SFP/SFP+
PoE
ARM
Five-port desktop switch with one Gigabit Ethernet port and four SFP+ 10Gbps ports
Product page for CRS312-4C+8XG-RM
CRS312-4C+8XG-RM
$699.00
*
10G
Combo ports
ROS v7
Switch of the future: the first MikroTik product with 10G RJ45 Ethernet ports and SFP+
Product page for CRS320-8P-8B-4S+RM
CRS320-8P-8B-4S+RM
$489.00
*
SFP/SFP+
PoE
ARM
ROS v7
The first MikroTik high-power PoE++ switch – for easy and cost-effective powering of industry standard 802.3af/at/bt devices. Forget about countless power cables – create a cleaner space with PoE++!
Product page for CRS317-1G-16S+RM
CRS317-1G-16S+RM
$499.00
*
SFP/SFP+
ARM
Smart Switch, 1 x Gigabit LAN, 16 x SFP+ cages, Dual Core 800MHz CPU, 1GB RAM, 1U rackmount passive cooling case, Dual Power Supplies
Product page for CRS309-1G-8S+IN
CRS309-1G-8S+IN
$269.00
*
SFP/SFP+
PoE
ARM
Desktop switch with one Gigabit Ethernet port and eight SFP+ 10Gbps ports
Product page for CRS518-16XS-2XQ-RM
CRS518-16XS-2XQ-RM
$1,595.00
*
100G
ROS v7
A 100 Gigabit switch for enterprise networks and data centers. Hot-swappable parts and insane port density with 1.2 Tbps switching capacity!
Product page for CRS310-1G-5S-4S+IN
CRS310-1G-5S-4S+IN
$199.00
*
SFP/SFP+
PoE
ARM
ROS v7
10 Gigabit fibre connectivity way over a 100 meters – for small offices or ISPs. Hardware offloaded VLAN-filtering and even some L3 routing on a budget!
Product page for CRS310-8G+2S+IN
CRS310-8G+2S+IN
$219.00
*
SFP/SFP+
2.5G
ARM
ROS v7
Take advantage of the blazing fast 2.5/10 Gigabit combo and upgrade your workspace! This switch can utilize the full potential of RouterOS v7: run VLANs, Jumbo frames, link aggregation, ACL rules, and so much more!
Product page for netPower 16P
netPower 16P
$279.00
*
SFP/SFP+
PoE
ARM
Outdoors
IP 54
An outdoor 18 port switch with 16 Gigabit PoE-out ports and 2 SFP+. Power all your access points anywhere!
Product page for netPower 15FR
netPower 15FR
$169.00
*
SFP/SFP+
PoE
ARM
Outdoors
IP 54
An outdoor 18 port switch with 15 reverse PoE ports and SFP. Cut costs, not speed – choose GPEN over GPON!
Product page for netFiber 9
netFiber 9
$249.00
*
SFP/SFP+
PoE
ARM
Outdoors
IP 54
ROS v7
A remarkable outdoor switch for setting up an optical 10G network that can even perform some light routing. The spiritual successor to the beloved FiberBox. Gigabit Ethernet, SFP/SFP+, PoE.
Product page for CRS326-24G-2S+IN
CRS326-24G-2S+IN
$199.00
*
SFP/SFP+
PoE
ARM
24 Gigabit ports, 2 SFP+ cages and a desktop case – server room power for your home!
Product page for CRS326-24G-2S+RM
CRS326-24G-2S+RM
$209.00
*
SFP/SFP+
PoE
ARM...
|
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visual_change
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accessibility
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NULL
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DXP4800PLUS-B5F8
Inbox (7) - [EMAIL] - Gmail
(56) DXP4800PLUS-B5F8
Inbox (7) - [EMAIL] - Gmail
(56) Inbox | [EMAIL] | Proton Mail
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Western Digital Red Plus 3.5 6TB 5400rpm 256MB SATA3 (WD60EFPX) от 241,72 € (472,76 лв.) Вътрешен хард диск Western Digital - Pazaruvaj.com
Western Digital Red Plus 3.5 6TB 5400rpm 256MB SATA3 (WD60EFPX) от 241,72 € (472,76 лв.) Вътрешен хард диск Western Digital - Pazaruvaj.com
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architecture - screenpipe docs
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Claude Code works better when you stop treating it like a machine - [EMAIL] - Gmail
Claude Code works better when you stop treating it like a machine - [EMAIL] - Gmail
Screenpipe — Archive
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SQLite Web: archive.db
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Claude Platform
Claude Platform
Hey @louis030195 Ill check during my - screenpipe.com
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GitHub - screenpipe/screenpipe: Run agents that work for you based on what you do. AI finally knows what you are doing · GitHub
GitHub - screenpipe/screenpipe: Run agents that work for you based on what you do. AI finally knows what you are doing · GitHub
Gong Pricing in 2026: Costs, Plans & Is It Worth It?
Gong Pricing in 2026: Costs, Plans & Is It Worth It?
GLM 5.1 Thinks Strategically, Data-Center Revolt Intensifies, When Helpful LLMs Turn Unhelpful, Humanoid Robots Get to Work - [EMAIL] - Gmail
GLM 5.1 Thinks Strategically, Data-Center Revolt Intensifies, When Helpful LLMs Turn Unhelpful, Humanoid Robots Get to Work - [EMAIL] - Gmail
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lakylak/screenpipe - screenpipe - Gitea: Git with a cup of tea
lakylak/screenpipe - screenpipe - Gitea: Git with a cup of tea
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Product page for netPower Lite 8P
NEW
netPower Lite 8P
$199.00
*
SFP/SFP+
PoE
Outdoors
IP 54
Low-cost. Tough. And always ON! Compact PoE switch with built-in UPS and smart battery charger – because your CCTV cameras and access points deserve true off-the-grid resilience.
Product page for CRS804 DDQ
NEW
CRS804 DDQ
$1,295.00
*
400G
10G
ARM64
Quad-core CPU
ROS v7
A compact 1U 400G switch built for AI clusters, storage fabrics, and high-speed aggregation, featuring four 400G QSFP56-DD ports, dual 10 Gigabit Ethernet, and RouterOS v7. With hot-swap power supplies, robust cooling, and low power consumption, it delivers ultra-high bandwidth, wire-speed performance, and future-proof scalability at an accessible price point.
Product page for CRS304-4XG-IN
CRS304-4XG-IN
$199.00
*
10G
PoE
ARM64
ROS v7
Compact, powerful, and ready to simplify your 10 Gigabit network setups with 4x10G Ethernet ports ready to use out-of-the-box. No extra modules needed!
Product page for CRS305-1G-4S+IN
CRS305-1G-4S+IN
$149.00
*
SFP/SFP+
PoE
ARM
Five-port desktop switch with one Gigabit Ethernet port and four SFP+ 10Gbps ports
Product page for CRS312-4C+8XG-RM
CRS312-4C+8XG-RM
$699.00
*
10G
Combo ports
ROS v7
Switch of the future: the first MikroTik product with 10G RJ45 Ethernet ports and SFP+
Product page for CRS320-8P-8B-4S+RM
CRS320-8P-8B-4S+RM
$489.00
*
SFP/SFP+
PoE
ARM
ROS v7
The first MikroTik high-power PoE++ switch – for easy and cost-effective powering of industry standard 802.3af/at/bt devices. Forget about countless power cables – create a cleaner space with PoE++!
Product page for CRS317-1G-16S+RM
CRS317-1G-16S+RM
$499.00
*
SFP/SFP+
ARM
Smart Switch, 1 x Gigabit LAN, 16 x SFP+ cages, Dual Core 800MHz CPU, 1GB RAM, 1U rackmount passive cooling case, Dual Power Supplies
Product page for CRS309-1G-8S+IN
CRS309-1G-8S+IN
$269.00
*
SFP/SFP+
PoE
ARM
Desktop switch with one Gigabit Ethernet port and eight SFP+ 10Gbps ports
Product page for CRS518-16XS-2XQ-RM
CRS518-16XS-2XQ-RM
$1,595.00
*
100G
ROS v7
A 100 Gigabit switch for enterprise networks and data centers. Hot-swappable parts and insane port density with 1.2 Tbps switching capacity!
Product page for CRS310-1G-5S-4S+IN
CRS310-1G-5S-4S+IN
$199.00
*
SFP/SFP+
PoE
ARM
ROS v7
10 Gigabit fibre connectivity way over a 100 meters – for small offices or ISPs. Hardware offloaded VLAN-filtering and even some L3 routing on a budget!
Product page for CRS310-8G+2S+IN
CRS310-8G+2S+IN
$219.00
*
SFP/SFP+
2.5G
ARM
ROS v7
Take advantage of the blazing fast 2.5/10 Gigabit combo and upgrade your workspace! This switch can utilize the full potential of RouterOS v7: run VLANs, Jumbo frames, link aggregation, ACL rules, and so much more!
Product page for netPower 16P
netPower 16P
$279.00
*
SFP/SFP+
PoE
ARM
Outdoors
IP 54
An outdoor 18 port switch with 16 Gigabit PoE-out ports and 2 SFP+. Power all your access points anywhere!
Product page for netPower 15FR
netPower 15FR
$169.00
*
SFP/SFP+
PoE
ARM
Outdoors
IP 54
An outdoor 18 port switch with 15 reverse PoE ports and SFP. Cut costs, not speed – choose GPEN over GPON!
Product page for netFiber 9
netFiber 9
$249.00
*
SFP/SFP+
PoE
ARM
Outdoors
IP 54
ROS v7
A remarkable outdoor switch for setting up an optical 10G network that can even perform some light routing. The spiritual successor to the beloved FiberBox. Gigabit Ethernet, SFP/SFP+, PoE.
Product page for CRS326-24G-2S+IN
CRS326-24G-2S+IN
$199.00
*
SFP/SFP+
PoE
ARM
24 Gigabit ports, 2 SFP+ cages and a desktop case – server room power for your home!
Product page for CRS326-24G-2S+RM
CRS326-24G-2S+RM
$209.00
*
SFP/SFP+
PoE
ARM...
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Product page for CRS304-4XG-IN
DXP4800PLUS-B5F8
In Product page for CRS304-4XG-IN
DXP4800PLUS-B5F8
Inbox (7) - [EMAIL] - Gmail
(56) Inbox | [EMAIL] | Proton Mail
Welcome back
Welcome back
Western Digital Red Plus 3.5 6TB 5400rpm 256MB SATA3 (WD60EFPX) от 241,72 € (472,76 лв.) Вътрешен хард диск Western Digital - Pazaruvaj.com
Western Digital Red Plus 3.5 6TB 5400rpm 256MB SATA3 (WD60EFPX) от 241,72 € (472,76 лв.) Вътрешен хард диск Western Digital - Pazaruvaj.com
Today's Deals
Today's Deals
architecture - screenpipe docs
architecture - screenpipe docs
Claude Code works better when you stop treating it like a machine - [EMAIL] - Gmail
Claude Code works better when you stop treating it like a machine - [EMAIL] - Gmail
Screenpipe — Archive
Screenpipe — Archive
SQLite Web: archive.db
SQLite Web: archive.db
SQLite Web: db.sqlite
SQLite Web: db.sqlite
Claude Platform
Claude Platform
Hey @louis030195 Ill check during my - screenpipe.com
Hey @louis030195 Ill check during my - screenpipe.com
GitHub - screenpipe/screenpipe: Run agents that work for you based on what you do. AI finally knows what you are doing · GitHub
GitHub - screenpipe/screenpipe: Run agents that work for you based on what you do. AI finally knows what you are doing · GitHub
Gong Pricing in 2026: Costs, Plans & Is It Worth It?
Gong Pricing in 2026: Costs, Plans & Is It Worth It?
GLM 5.1 Thinks Strategically, Data-Center Revolt Intensifies, When Helpful LLMs Turn Unhelpful, Humanoid Robots Get to Work - [EMAIL] - Gmail
GLM 5.1 Thinks Strategically, Data-Center Revolt Intensifies, When Helpful LLMs Turn Unhelpful, Humanoid Robots Get to Work - [EMAIL] - Gmail
Gitea Official Website
Gitea Official Website
lakylak/screenpipe - screenpipe - Gitea: Git with a cup of tea
lakylak/screenpipe - screenpipe - Gitea: Git with a cup of tea
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Product page for netPower Lite 8P
NEW
netPower Lite 8P
$199.00
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SFP/SFP+
PoE
Outdoors
IP 54
Low-cost. Tough. And always ON! Compact PoE switch with built-in UPS and smart battery charger – because your CCTV cameras and access points deserve true off-the-grid resilience.
Product page for CRS804 DDQ
NEW
CRS804 DDQ
$1,295.00
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400G
10G
ARM64
Quad-core CPU
ROS v7
A compact 1U 400G switch built for AI clusters, storage fabrics, and high-speed aggregation, featuring four 400G QSFP56-DD ports, dual 10 Gigabit Ethernet, and RouterOS v7. With hot-swap power supplies, robust cooling, and low power consumption, it delivers ultra-high bandwidth, wire-speed performance, and future-proof scalability at an accessible price point.
Product page for CRS304-4XG-IN
CRS304-4XG-IN
$199.00
*
10G
PoE
ARM64
ROS v7
Compact, powerful, and ready to simplify your 10 Gigabit network setups with 4x10G Ethernet ports ready to use out-of-the-box. No extra modules needed!
Product page for CRS305-1G-4S+IN
CRS305-1G-4S+IN
$149.00
*
SFP/SFP+
PoE
ARM
Five-port desktop switch with one Gigabit Ethernet port and four SFP+ 10Gbps ports
Product page for CRS312-4C+8XG-RM
CRS312-4C+8XG-RM
$699.00
*
10G
Combo ports
ROS v7
Switch of the future: the first MikroTik product with 10G RJ45 Ethernet ports and SFP+
Product page for CRS320-8P-8B-4S+RM
CRS320-8P-8B-4S+RM
$489.00
*
SFP/SFP+
PoE
ARM
ROS v7
The first MikroTik high-power PoE++ switch – for easy and cost-effective powering of industry standard 802.3af/at/bt devices. Forget about countless power cables – create a cleaner space with PoE++!
Product page for CRS317-1G-16S+RM
CRS317-1G-16S+RM
$499.00
*
SFP/SFP+
ARM
Smart Switch, 1 x Gigabit LAN, 16 x SFP+ cages, Dual Core 800MHz CPU, 1GB RAM, 1U rackmount passive cooling case, Dual Power Supplies
Product page for CRS309-1G-8S+IN
CRS309-1G-8S+IN
$269.00
*
SFP/SFP+
PoE
ARM
Desktop switch with one Gigabit Ethernet port and eight SFP+ 10Gbps ports
Product page for CRS518-16XS-2XQ-RM
CRS518-16XS-2XQ-RM
$1,595.00
*
100G
ROS v7
A 100 Gigabit switch for enterprise networks and data centers. Hot-swappable parts and insane port density with 1.2 Tbps switching capacity!
Product page for CRS310-1G-5S-4S+IN
CRS310-1G-5S-4S+IN
$199.00
*
SFP/SFP+
PoE
ARM
ROS v7
10 Gigabit fibre connectivity way over a 100 meters – for small offices or ISPs. Hardware offloaded VLAN-filtering and even some L3 routing on a budget!
Product page for CRS310-8G+2S+IN
CRS310-8G+2S+IN
$219.00
*
SFP/SFP+
2.5G
ARM
ROS v7
Take advantage of the blazing fast 2.5/10 Gigabit combo and upgrade your workspace! This switch can utilize the full potential of RouterOS v7: run VLANs, Jumbo frames, link aggregation, ACL rules, and so much more!
Product page for netPower 16P
netPower 16P
$279.00
*
SFP/SFP+
PoE
ARM
Outdoors
IP 54
An outdoor 18 port switch with 16 Gigabit PoE-out ports and 2 SFP+. Power all your access points anywhere!
Product page for netPower 15FR
netPower 15FR
$169.00
*
SFP/SFP+
PoE
ARM
Outdoors
IP 54
An outdoor 18 port switch with 15 reverse PoE ports and SFP. Cut costs, not speed – choose GPEN over GPON!
Product page for netFiber 9
netFiber 9
$249.00
*
SFP/SFP+
PoE
ARM
Outdoors
IP 54
ROS v7
A remarkable outdoor switch for setting up an optical 10G network that can even perform some light routing. The spiritual successor to the beloved FiberBox. Gigabit Ethernet, SFP/SFP+, PoE.
Product page for CRS326-24G-2S+IN
CRS326-24G-2S+IN
$199.00
*
SFP/SFP+
PoE
ARM
24 Gigabit ports, 2 SFP+ cages and a desktop case – server room power for your home!
Product page for CRS326-24G-2S+RM
CRS326-24G-2S+RM
$209.00
*
SFP/SFP+
PoE
ARM
24 Gigabit port switch with 2 x SFP+ cages in 1U rackmount case, Dual boot (RouterOS or SwitchOS)
Product page for CRS326-24S+2Q+RM
CRS326-24S+2Q+RM
$599.00
*
SFP/SFP+
40G
ROS v7
One of our faster switches for the most demanding setups.
Product page for CRS326-4C+20G+2Q+RM
CRS326-4C+20G+2Q+RM
$999.00
*
40G
2.5G...
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Product page for CRS304-4XG-IN
DXP4800PLUS-B5F8
In Product page for CRS304-4XG-IN
DXP4800PLUS-B5F8
Inbox (7) - [EMAIL] - Gmail
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Welcome back
Welcome back
Western Digital Red Plus 3.5 6TB 5400rpm 256MB SATA3 (WD60EFPX) от 241,72 € (472,76 лв.) Вътрешен хард диск Western Digital - Pazaruvaj.com
Western Digital Red Plus 3.5 6TB 5400rpm 256MB SATA3 (WD60EFPX) от 241,72 € (472,76 лв.) Вътрешен хард диск Western Digital - Pazaruvaj.com
Today's Deals
Today's Deals
architecture - screenpipe docs
architecture - screenpipe docs
Claude Code works better when you stop treating it like a machine - [EMAIL] - Gmail
Claude Code works better when you stop treating it like a machine - [EMAIL] - Gmail
Screenpipe — Archive
Screenpipe — Archive
SQLite Web: archive.db
SQLite Web: archive.db
SQLite Web: db.sqlite
SQLite Web: db.sqlite
Claude Platform
Claude Platform
Hey @louis030195 Ill check during my - screenpipe.com
Hey @louis030195 Ill check during my - screenpipe.com
GitHub - screenpipe/screenpipe: Run agents that work for you based on what you do. AI finally knows what you are doing · GitHub
GitHub - screenpipe/screenpipe: Run agents that work for you based on what you do. AI finally knows what you are doing · GitHub
Gong Pricing in 2026: Costs, Plans & Is It Worth It?
Gong Pricing in 2026: Costs, Plans & Is It Worth It?
GLM 5.1 Thinks Strategically, Data-Center Revolt Intensifies, When Helpful LLMs Turn Unhelpful, Humanoid Robots Get to Work - [EMAIL] - Gmail
GLM 5.1 Thinks Strategically, Data-Center Revolt Intensifies, When Helpful LLMs Turn Unhelpful, Humanoid Robots Get to Work - [EMAIL] - Gmail
Gitea Official Website
Gitea Official Website
lakylak/screenpipe - screenpipe - Gitea: Git with a cup of tea
lakylak/screenpipe - screenpipe - Gitea: Git with a cup of tea
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Product page for netPower Lite 8P
NEW
netPower Lite 8P
$199.00
*
SFP/SFP+
PoE
Outdoors
IP 54
Low-cost. Tough. And always ON! Compact PoE switch with built-in UPS and smart battery charger – because your CCTV cameras and access points deserve true off-the-grid resilience.
Product page for CRS804 DDQ
NEW
CRS804 DDQ
$1,295.00
*
400G
10G
ARM64
Quad-core CPU
ROS v7
A compact 1U 400G switch built for AI clusters, storage fabrics, and high-speed aggregation, featuring four 400G QSFP56-DD ports, dual 10 Gigabit Ethernet, and RouterOS v7. With hot-swap power supplies, robust cooling, and low power consumption, it delivers ultra-high bandwidth, wire-speed performance, and future-proof scalability at an accessible price point.
Product page for CRS304-4XG-IN
CRS304-4XG-IN
$199.00
*
10G
PoE
ARM64
ROS v7
Compact, powerful, and ready to simplify your 10 Gigabit network setups with 4x10G Ethernet ports ready to use out-of-the-box. No extra modules needed!
Product page for CRS305-1G-4S+IN
CRS305-1G-4S+IN
$149.00
*
SFP/SFP+
PoE
ARM
Five-port desktop switch with one Gigabit Ethernet port and four SFP+ 10Gbps ports
Product page for CRS312-4C+8XG-RM
CRS312-4C+8XG-RM
$699.00
*
10G
Combo ports
ROS v7
Switch of the future: the first MikroTik product with 10G RJ45 Ethernet ports and SFP+
Product page for CRS320-8P-8B-4S+RM
CRS320-8P-8B-4S+RM
$489.00
*
SFP/SFP+
PoE
ARM
ROS v7
The first MikroTik high-power PoE++ switch – for easy and cost-effective powering of industry standard 802.3af/at/bt devices. Forget about countless power cables – create a cleaner space with PoE++!
Product page for CRS317-1G-16S+RM
CRS317-1G-16S+RM
$499.00
*
SFP/SFP+
ARM
Smart Switch, 1 x Gigabit LAN, 16 x SFP+ cages, Dual Core 800MHz CPU, 1GB RAM, 1U rackmount passive cooling case, Dual Power Supplies
Product page for CRS309-1G-8S+IN
CRS309-1G-8S+IN
$269.00
*
SFP/SFP+
PoE
ARM
Desktop switch with one Gigabit Ethernet port and eight SFP+ 10Gbps ports
Product page for CRS518-16XS-2XQ-RM
CRS518-16XS-2XQ-RM
$1,595.00
*
100G
ROS v7
A 100 Gigabit switch for enterprise networks and data centers. Hot-swappable parts and insane port density with 1.2 Tbps switching capacity!
Product page for CRS310-1G-5S-4S+IN
CRS310-1G-5S-4S+IN
$199.00
*
SFP/SFP+
PoE
ARM
ROS v7
10 Gigabit fibre connectivity way over a 100 meters – for small offices or ISPs. Hardware offloaded VLAN-filtering and even some L3 routing on a budget!
Product page for CRS310-8G+2S+IN
CRS310-8G+2S+IN
$219.00
*
SFP/SFP+
2.5G
ARM
ROS v7
Take advantage of the blazing fast 2.5/10 Gigabit combo and upgrade your workspace! This switch can utilize the full potential of RouterOS v7: run VLANs, Jumbo frames, link aggregation, ACL rules, and so much more!
Product page for netPower 16P
netPower 16P
$279.00
*
SFP/SFP+
PoE
ARM
Outdoors
IP 54
An outdoor 18 port switch with 16 Gigabit PoE-out ports and 2 SFP+. Power all your access points anywhere!
Product page for netPower 15FR
netPower 15FR
$169.00
*
SFP/SFP+
PoE
ARM
Outdoors
IP 54
An outdoor 18 port switch with 15 reverse PoE ports and SFP. Cut costs, not speed – choose GPEN over GPON!
Product page for netFiber 9
netFiber 9
$249.00
*
SFP/SFP+
PoE
ARM
Outdoors
IP 54
ROS v7
A remarkable outdoor switch for setting up an optical 10G network that can even perform some light routing. The spiritual successor to the beloved FiberBox. Gigabit Ethernet, SFP/SFP+, PoE.
Product page for CRS326-24G-2S+IN
CRS326-24G-2S+IN
$199.00
*
SFP/SFP+
PoE
ARM
24 Gigabit ports, 2 SFP+ cages and a desktop case – server room power for your home!
Product page for CRS326-24G-2S+RM
CRS326-24G-2S+RM
$209.00
*
SFP/SFP+
PoE
ARM
24 Gigabit port switch with 2 x SFP+ cages in 1U rackmount case, Dual boot (RouterOS or SwitchOS)
Product page for CRS326-24S+2Q+RM
CRS326-24S+2Q+RM
$599.00
*
SFP/SFP+
40G
ROS v7
One of our faster switches for the most demanding setups.
Product page for CRS326-4C+20G+2Q+RM
CRS326-4C+20G+2Q+RM
$999.00
*
40G
2.5G...
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NULL
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80870
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2140
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19
|
2026-04-25T15:08:30.645721+00:00
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/Users/lukas/.screenpipe/data/data/2026-04-25/1777 /Users/lukas/.screenpipe/data/data/2026-04-25/1777129710645_m2.jpg...
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Firefox
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MikroTik · Switches — Personal
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True
|
mikrotik.com/products/group/switches
|
monitor_2
|
NULL
|
NULL
|
NULL
|
NULL
|
DXP4800PLUS-B5F8
Inbox (7) - [EMAIL] - Gmail
(56) DXP4800PLUS-B5F8
Inbox (7) - [EMAIL] - Gmail
(56) Inbox | [EMAIL] | Proton Mail
Welcome back
Welcome back
Western Digital Red Plus 3.5 6TB 5400rpm 256MB SATA3 (WD60EFPX) от 241,72 € (472,76 лв.) Вътрешен хард диск Western Digital - Pazaruvaj.com
Western Digital Red Plus 3.5 6TB 5400rpm 256MB SATA3 (WD60EFPX) от 241,72 € (472,76 лв.) Вътрешен хард диск Western Digital - Pazaruvaj.com
Today's Deals
Today's Deals
architecture - screenpipe docs
architecture - screenpipe docs
Claude Code works better when you stop treating it like a machine - [EMAIL] - Gmail
Claude Code works better when you stop treating it like a machine - [EMAIL] - Gmail
Screenpipe — Archive
Screenpipe — Archive
SQLite Web: archive.db
SQLite Web: archive.db
SQLite Web: db.sqlite
SQLite Web: db.sqlite
Claude Platform
Claude Platform
Hey @louis030195 Ill check during my - screenpipe.com
Hey @louis030195 Ill check during my - screenpipe.com
GitHub - screenpipe/screenpipe: Run agents that work for you based on what you do. AI finally knows what you are doing · GitHub
GitHub - screenpipe/screenpipe: Run agents that work for you based on what you do. AI finally knows what you are doing · GitHub
Gong Pricing in 2026: Costs, Plans & Is It Worth It?
Gong Pricing in 2026: Costs, Plans & Is It Worth It?
GLM 5.1 Thinks Strategically, Data-Center Revolt Intensifies, When Helpful LLMs Turn Unhelpful, Humanoid Robots Get to Work - [EMAIL] - Gmail
GLM 5.1 Thinks Strategically, Data-Center Revolt Intensifies, When Helpful LLMs Turn Unhelpful, Humanoid Robots Get to Work - [EMAIL] - Gmail
Gitea Official Website
Gitea Official Website
lakylak/screenpipe - screenpipe - Gitea: Git with a cup of tea
lakylak/screenpipe - screenpipe - Gitea: Git with a cup of tea
New Tab
New Tab
MikroTik · Switches
MikroTik · Switches
Close tab
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Open Le Chat Mistral (⌃X)
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Product page for netPower Lite 8P
NEW
netPower Lite 8P
$199.00
*
SFP/SFP+
PoE
Outdoors
IP 54
Low-cost. Tough. And always ON! Compact PoE switch with built-in UPS and smart battery charger – because your CCTV cameras and access points deserve true off-the-grid resilience.
Product page for CRS804 DDQ
NEW
CRS804 DDQ
$1,295.00
*
400G
10G
ARM64
Quad-core CPU
ROS v7
A compact 1U 400G switch built for AI clusters, storage fabrics, and high-speed aggregation, featuring four 400G QSFP56-DD ports, dual 10 Gigabit Ethernet, and RouterOS v7. With hot-swap power supplies, robust cooling, and low power consumption, it delivers ultra-high bandwidth, wire-speed performance, and future-proof scalability at an accessible price point.
Product page for CRS304-4XG-IN
CRS304-4XG-IN
$199.00
*
10G
PoE
ARM64
ROS v7
Compact, powerful, and ready to simplify your 10 Gigabit network setups with 4x10G Ethernet ports ready to use out-of-the-box. No extra modules needed!
Product page for CRS305-1G-4S+IN
CRS305-1G-4S+IN
$149.00
*
SFP/SFP+
PoE
ARM
Five-port desktop switch with one Gigabit Ethernet port and four SFP+ 10Gbps ports
Product page for CRS312-4C+8XG-RM
CRS312-4C+8XG-RM
$699.00
*
10G
Combo ports
ROS v7
Switch of the future: the first MikroTik product with 10G RJ45 Ethernet ports and SFP+
Product page for CRS320-8P-8B-4S+RM
CRS320-8P-8B-4S+RM
$489.00
*
SFP/SFP+
PoE
ARM
ROS v7
The first MikroTik high-power PoE++ switch – for easy and cost-effective powering of industry standard 802.3af/at/bt devices. Forget about countless power cables – create a cleaner space with PoE++!
Product page for CRS317-1G-16S+RM
CRS317-1G-16S+RM
$499.00
*
SFP/SFP+
ARM
Smart Switch, 1 x Gigabit LAN, 16 x SFP+ cages, Dual Core 800MHz CPU, 1GB RAM, 1U rackmount passive cooling case, Dual Power Supplies
Product page for CRS309-1G-8S+IN
CRS309-1G-8S+IN
$269.00
*
SFP/SFP+
PoE
ARM
Desktop switch with one Gigabit Ethernet port and eight SFP+ 10Gbps ports
Product page for CRS518-16XS-2XQ-RM
CRS518-16XS-2XQ-RM
$1,595.00
*
100G
ROS v7
A 100 Gigabit switch for enterprise networks and data centers. Hot-swappable parts and insane port density with 1.2 Tbps switching capacity!
Product page for CRS310-1G-5S-4S+IN
CRS310-1G-5S-4S+IN
$199.00
*
SFP/SFP+
PoE
ARM
ROS v7
10 Gigabit fibre connectivity way over a 100 meters – for small offices or ISPs. Hardware offloaded VLAN-filtering and even some L3 routing on a budget!
Product page for CRS310-8G+2S+IN
CRS310-8G+2S+IN
$219.00
*
SFP/SFP+
2.5G
ARM
ROS v7
Take advantage of the blazing fast 2.5/10 Gigabit combo and upgrade your workspace! This switch can utilize the full potential of RouterOS v7: run VLANs, Jumbo frames, link aggregation, ACL rules, and so much more!
Product page for netPower 16P
netPower 16P
$279.00
*
SFP/SFP+
PoE
ARM
Outdoors
IP 54
An outdoor 18 port switch with 16 Gigabit PoE-out ports and 2 SFP+. Power all your access points anywhere!
Product page for netPower 15FR
netPower 15FR
$169.00
*
SFP/SFP+
PoE
ARM
Outdoors
IP 54
An outdoor 18 port switch with 15 reverse PoE ports and SFP. Cut costs, not speed – choose GPEN over GPON!
Product page for netFiber 9
netFiber 9
$249.00
*
SFP/SFP+
PoE
ARM
Outdoors
IP 54
ROS v7
A remarkable outdoor switch for setting up an optical 10G network that can even perform some light routing. The spiritual successor to the beloved FiberBox. Gigabit Ethernet, SFP/SFP+, PoE.
Product page for CRS326-24G-2S+IN
CRS326-24G-2S+IN
$199.00
*
SFP/SFP+
PoE
ARM
24 Gigabit ports, 2 SFP+ cages and a desktop case – server room power for your home!
Product page for CRS326-24G-2S+RM
CRS326-24G-2S+RM
$209.00
*
SFP/SFP+
PoE...
|
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2234021505289962171
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visual_change
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accessibility
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NULL
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DXP4800PLUS-B5F8
Inbox (7) - [EMAIL] - Gmail
(56) DXP4800PLUS-B5F8
Inbox (7) - [EMAIL] - Gmail
(56) Inbox | [EMAIL] | Proton Mail
Welcome back
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Western Digital Red Plus 3.5 6TB 5400rpm 256MB SATA3 (WD60EFPX) от 241,72 € (472,76 лв.) Вътрешен хард диск Western Digital - Pazaruvaj.com
Western Digital Red Plus 3.5 6TB 5400rpm 256MB SATA3 (WD60EFPX) от 241,72 € (472,76 лв.) Вътрешен хард диск Western Digital - Pazaruvaj.com
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architecture - screenpipe docs
architecture - screenpipe docs
Claude Code works better when you stop treating it like a machine - [EMAIL] - Gmail
Claude Code works better when you stop treating it like a machine - [EMAIL] - Gmail
Screenpipe — Archive
Screenpipe — Archive
SQLite Web: archive.db
SQLite Web: archive.db
SQLite Web: db.sqlite
SQLite Web: db.sqlite
Claude Platform
Claude Platform
Hey @louis030195 Ill check during my - screenpipe.com
Hey @louis030195 Ill check during my - screenpipe.com
GitHub - screenpipe/screenpipe: Run agents that work for you based on what you do. AI finally knows what you are doing · GitHub
GitHub - screenpipe/screenpipe: Run agents that work for you based on what you do. AI finally knows what you are doing · GitHub
Gong Pricing in 2026: Costs, Plans & Is It Worth It?
Gong Pricing in 2026: Costs, Plans & Is It Worth It?
GLM 5.1 Thinks Strategically, Data-Center Revolt Intensifies, When Helpful LLMs Turn Unhelpful, Humanoid Robots Get to Work - [EMAIL] - Gmail
GLM 5.1 Thinks Strategically, Data-Center Revolt Intensifies, When Helpful LLMs Turn Unhelpful, Humanoid Robots Get to Work - [EMAIL] - Gmail
Gitea Official Website
Gitea Official Website
lakylak/screenpipe - screenpipe - Gitea: Git with a cup of tea
lakylak/screenpipe - screenpipe - Gitea: Git with a cup of tea
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*
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Low-cost. Tough. And always ON! Compact PoE switch with built-in UPS and smart battery charger – because your CCTV cameras and access points deserve true off-the-grid resilience.
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CRS804 DDQ
$1,295.00
*
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ROS v7
A compact 1U 400G switch built for AI clusters, storage fabrics, and high-speed aggregation, featuring four 400G QSFP56-DD ports, dual 10 Gigabit Ethernet, and RouterOS v7. With hot-swap power supplies, robust cooling, and low power consumption, it delivers ultra-high bandwidth, wire-speed performance, and future-proof scalability at an accessible price point.
Product page for CRS304-4XG-IN
CRS304-4XG-IN
$199.00
*
10G
PoE
ARM64
ROS v7
Compact, powerful, and ready to simplify your 10 Gigabit network setups with 4x10G Ethernet ports ready to use out-of-the-box. No extra modules needed!
Product page for CRS305-1G-4S+IN
CRS305-1G-4S+IN
$149.00
*
SFP/SFP+
PoE
ARM
Five-port desktop switch with one Gigabit Ethernet port and four SFP+ 10Gbps ports
Product page for CRS312-4C+8XG-RM
CRS312-4C+8XG-RM
$699.00
*
10G
Combo ports
ROS v7
Switch of the future: the first MikroTik product with 10G RJ45 Ethernet ports and SFP+
Product page for CRS320-8P-8B-4S+RM
CRS320-8P-8B-4S+RM
$489.00
*
SFP/SFP+
PoE
ARM
ROS v7
The first MikroTik high-power PoE++ switch – for easy and cost-effective powering of industry standard 802.3af/at/bt devices. Forget about countless power cables – create a cleaner space with PoE++!
Product page for CRS317-1G-16S+RM
CRS317-1G-16S+RM
$499.00
*
SFP/SFP+
ARM
Smart Switch, 1 x Gigabit LAN, 16 x SFP+ cages, Dual Core 800MHz CPU, 1GB RAM, 1U rackmount passive cooling case, Dual Power Supplies
Product page for CRS309-1G-8S+IN
CRS309-1G-8S+IN
$269.00
*
SFP/SFP+
PoE
ARM
Desktop switch with one Gigabit Ethernet port and eight SFP+ 10Gbps ports
Product page for CRS518-16XS-2XQ-RM
CRS518-16XS-2XQ-RM
$1,595.00
*
100G
ROS v7
A 100 Gigabit switch for enterprise networks and data centers. Hot-swappable parts and insane port density with 1.2 Tbps switching capacity!
Product page for CRS310-1G-5S-4S+IN
CRS310-1G-5S-4S+IN
$199.00
*
SFP/SFP+
PoE
ARM
ROS v7
10 Gigabit fibre connectivity way over a 100 meters – for small offices or ISPs. Hardware offloaded VLAN-filtering and even some L3 routing on a budget!
Product page for CRS310-8G+2S+IN
CRS310-8G+2S+IN
$219.00
*
SFP/SFP+
2.5G
ARM
ROS v7
Take advantage of the blazing fast 2.5/10 Gigabit combo and upgrade your workspace! This switch can utilize the full potential of RouterOS v7: run VLANs, Jumbo frames, link aggregation, ACL rules, and so much more!
Product page for netPower 16P
netPower 16P
$279.00
*
SFP/SFP+
PoE
ARM
Outdoors
IP 54
An outdoor 18 port switch with 16 Gigabit PoE-out ports and 2 SFP+. Power all your access points anywhere!
Product page for netPower 15FR
netPower 15FR
$169.00
*
SFP/SFP+
PoE
ARM
Outdoors
IP 54
An outdoor 18 port switch with 15 reverse PoE ports and SFP. Cut costs, not speed – choose GPEN over GPON!
Product page for netFiber 9
netFiber 9
$249.00
*
SFP/SFP+
PoE
ARM
Outdoors
IP 54
ROS v7
A remarkable outdoor switch for setting up an optical 10G network that can even perform some light routing. The spiritual successor to the beloved FiberBox. Gigabit Ethernet, SFP/SFP+, PoE.
Product page for CRS326-24G-2S+IN
CRS326-24G-2S+IN
$199.00
*
SFP/SFP+
PoE
ARM
24 Gigabit ports, 2 SFP+ cages and a desktop case – server room power for your home!
Product page for CRS326-24G-2S+RM
CRS326-24G-2S+RM
$209.00
*
SFP/SFP+
PoE...
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MikroTik · Switches — Personal
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mikrotik.com/products/group/switches
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Product page for CRS304-4XG-IN
DXP4800PLUS-B5F8
In Product page for CRS304-4XG-IN
DXP4800PLUS-B5F8
Inbox (7) - [EMAIL] - Gmail
(56) Inbox | [EMAIL] | Proton Mail
Welcome back
Welcome back
Western Digital Red Plus 3.5 6TB 5400rpm 256MB SATA3 (WD60EFPX) от 241,72 € (472,76 лв.) Вътрешен хард диск Western Digital - Pazaruvaj.com
Western Digital Red Plus 3.5 6TB 5400rpm 256MB SATA3 (WD60EFPX) от 241,72 € (472,76 лв.) Вътрешен хард диск Western Digital - Pazaruvaj.com
Today's Deals
Today's Deals
architecture - screenpipe docs
architecture - screenpipe docs
Claude Code works better when you stop treating it like a machine - [EMAIL] - Gmail
Claude Code works better when you stop treating it like a machine - [EMAIL] - Gmail
Screenpipe — Archive
Screenpipe — Archive
SQLite Web: archive.db
SQLite Web: archive.db
SQLite Web: db.sqlite
SQLite Web: db.sqlite
Claude Platform
Claude Platform
Hey @louis030195 Ill check during my - screenpipe.com
Hey @louis030195 Ill check during my - screenpipe.com
GitHub - screenpipe/screenpipe: Run agents that work for you based on what you do. AI finally knows what you are doing · GitHub
GitHub - screenpipe/screenpipe: Run agents that work for you based on what you do. AI finally knows what you are doing · GitHub
Gong Pricing in 2026: Costs, Plans & Is It Worth It?
Gong Pricing in 2026: Costs, Plans & Is It Worth It?
GLM 5.1 Thinks Strategically, Data-Center Revolt Intensifies, When Helpful LLMs Turn Unhelpful, Humanoid Robots Get to Work - [EMAIL] - Gmail
GLM 5.1 Thinks Strategically, Data-Center Revolt Intensifies, When Helpful LLMs Turn Unhelpful, Humanoid Robots Get to Work - [EMAIL] - Gmail
Gitea Official Website
Gitea Official Website
lakylak/screenpipe - screenpipe - Gitea: Git with a cup of tea
lakylak/screenpipe - screenpipe - Gitea: Git with a cup of tea
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NEW
netPower Lite 8P
$199.00
*
SFP/SFP+
PoE
Outdoors
IP 54
Low-cost. Tough. And always ON! Compact PoE switch with built-in UPS and smart battery charger – because your CCTV cameras and access points deserve true off-the-grid resilience.
Product page for CRS804 DDQ
NEW
CRS804 DDQ
$1,295.00
*
400G
10G
ARM64
Quad-core CPU
ROS v7
A compact 1U 400G switch built for AI clusters, storage fabrics, and high-speed aggregation, featuring four 400G QSFP56-DD ports, dual 10 Gigabit Ethernet, and RouterOS v7. With hot-swap power supplies, robust cooling, and low power consumption, it delivers ultra-high bandwidth, wire-speed performance, and future-proof scalability at an accessible price point.
Product page for CRS304-4XG-IN
CRS304-4XG-IN
$199.00
*
10G
PoE
ARM64
ROS v7
Compact, powerful, and ready to simplify your 10 Gigabit network setups with 4x10G Ethernet ports ready to use out-of-the-box. No extra modules needed!
Product page for CRS305-1G-4S+IN
CRS305-1G-4S+IN
$149.00
*
SFP/SFP+
PoE
ARM
Five-port desktop switch with one Gigabit Ethernet port and four SFP+ 10Gbps ports
Product page for CRS312-4C+8XG-RM
CRS312-4C+8XG-RM
$699.00
*
10G
Combo ports
ROS v7
Switch of the future: the first MikroTik product with 10G RJ45 Ethernet ports and SFP+
Product page for CRS320-8P-8B-4S+RM
CRS320-8P-8B-4S+RM
$489.00
*
SFP/SFP+
PoE
ARM
ROS v7
The first MikroTik high-power PoE++ switch – for easy and cost-effective powering of industry standard 802.3af/at/bt devices. Forget about countless power cables – create a cleaner space with PoE++!
Product page for CRS317-1G-16S+RM
CRS317-1G-16S+RM
$499.00
*
SFP/SFP+
ARM
Smart Switch, 1 x Gigabit LAN, 16 x SFP+ cages, Dual Core 800MHz CPU, 1GB RAM, 1U rackmount passive cooling case, Dual Power Supplies
Product page for CRS309-1G-8S+IN
CRS309-1G-8S+IN
$269.00
*
SFP/SFP+
PoE
ARM
Desktop switch with one Gigabit Ethernet port and eight SFP+ 10Gbps ports
Product page for CRS518-16XS-2XQ-RM
CRS518-16XS-2XQ-RM
$1,595.00
*
100G
ROS v7
A 100 Gigabit switch for enterprise networks and data centers. Hot-swappable parts and insane port density with 1.2 Tbps switching capacity!
Product page for CRS310-1G-5S-4S+IN
CRS310-1G-5S-4S+IN
$199.00
*
SFP/SFP+
PoE
ARM
ROS v7
10 Gigabit fibre connectivity way over a 100 meters – for small offices or ISPs. Hardware offloaded VLAN-filtering and even some L3 routing on a budget!
Product page for CRS310-8G+2S+IN
CRS310-8G+2S+IN
$219.00
*
SFP/SFP+
2.5G
ARM
ROS v7
Take advantage of the blazing fast 2.5/10 Gigabit combo and upgrade your workspace! This switch can utilize the full potential of RouterOS v7: run VLANs, Jumbo frames, link aggregation, ACL rules, and so much more!
Product page for netPower 16P
netPower 16P
$279.00
*
SFP/SFP+
PoE
ARM
Outdoors
IP 54
An outdoor 18 port switch with 16 Gigabit PoE-out ports and 2 SFP+. Power all your access points anywhere!
Product page for netPower 15FR
netPower 15FR
$169.00
*
SFP/SFP+
PoE
ARM
Outdoors
IP 54
An outdoor 18 port switch with 15 reverse PoE ports and SFP. Cut costs, not speed – choose GPEN over GPON!
Product page for netFiber 9
netFiber 9
$249.00
*
SFP/SFP+
PoE
ARM
Outdoors
IP 54
ROS v7
A remarkable outdoor switch for setting up an optical 10G network that can even perform some light routing. The spiritual successor to the beloved FiberBox. Gigabit Ethernet, SFP/SFP+, PoE.
Product page for CRS326-24G-2S+IN
CRS326-24G-2S+IN
$199.00
*...
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Product page for CRS304-4XG-IN
DXP4800PLUS-B5F8
In Product page for CRS304-4XG-IN
DXP4800PLUS-B5F8
Inbox (7) - [EMAIL] - Gmail
(56) Inbox | [EMAIL] | Proton Mail
Welcome back
Welcome back
Western Digital Red Plus 3.5 6TB 5400rpm 256MB SATA3 (WD60EFPX) от 241,72 € (472,76 лв.) Вътрешен хард диск Western Digital - Pazaruvaj.com
Western Digital Red Plus 3.5 6TB 5400rpm 256MB SATA3 (WD60EFPX) от 241,72 € (472,76 лв.) Вътрешен хард диск Western Digital - Pazaruvaj.com
Today's Deals
Today's Deals
architecture - screenpipe docs
architecture - screenpipe docs
Claude Code works better when you stop treating it like a machine - [EMAIL] - Gmail
Claude Code works better when you stop treating it like a machine - [EMAIL] - Gmail
Screenpipe — Archive
Screenpipe — Archive
SQLite Web: archive.db
SQLite Web: archive.db
SQLite Web: db.sqlite
SQLite Web: db.sqlite
Claude Platform
Claude Platform
Hey @louis030195 Ill check during my - screenpipe.com
Hey @louis030195 Ill check during my - screenpipe.com
GitHub - screenpipe/screenpipe: Run agents that work for you based on what you do. AI finally knows what you are doing · GitHub
GitHub - screenpipe/screenpipe: Run agents that work for you based on what you do. AI finally knows what you are doing · GitHub
Gong Pricing in 2026: Costs, Plans & Is It Worth It?
Gong Pricing in 2026: Costs, Plans & Is It Worth It?
GLM 5.1 Thinks Strategically, Data-Center Revolt Intensifies, When Helpful LLMs Turn Unhelpful, Humanoid Robots Get to Work - [EMAIL] - Gmail
GLM 5.1 Thinks Strategically, Data-Center Revolt Intensifies, When Helpful LLMs Turn Unhelpful, Humanoid Robots Get to Work - [EMAIL] - Gmail
Gitea Official Website
Gitea Official Website
lakylak/screenpipe - screenpipe - Gitea: Git with a cup of tea
lakylak/screenpipe - screenpipe - Gitea: Git with a cup of tea
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Product page for netPower Lite 8P
NEW
netPower Lite 8P
$199.00
*
SFP/SFP+
PoE
Outdoors
IP 54
Low-cost. Tough. And always ON! Compact PoE switch with built-in UPS and smart battery charger – because your CCTV cameras and access points deserve true off-the-grid resilience.
Product page for CRS804 DDQ
NEW
CRS804 DDQ
$1,295.00
*
400G
10G
ARM64
Quad-core CPU
ROS v7
A compact 1U 400G switch built for AI clusters, storage fabrics, and high-speed aggregation, featuring four 400G QSFP56-DD ports, dual 10 Gigabit Ethernet, and RouterOS v7. With hot-swap power supplies, robust cooling, and low power consumption, it delivers ultra-high bandwidth, wire-speed performance, and future-proof scalability at an accessible price point.
Product page for CRS304-4XG-IN
CRS304-4XG-IN
$199.00
*
10G
PoE
ARM64
ROS v7
Compact, powerful, and ready to simplify your 10 Gigabit network setups with 4x10G Ethernet ports ready to use out-of-the-box. No extra modules needed!
Product page for CRS305-1G-4S+IN
CRS305-1G-4S+IN
$149.00
*
SFP/SFP+
PoE
ARM
Five-port desktop switch with one Gigabit Ethernet port and four SFP+ 10Gbps ports
Product page for CRS312-4C+8XG-RM
CRS312-4C+8XG-RM
$699.00
*
10G
Combo ports
ROS v7
Switch of the future: the first MikroTik product with 10G RJ45 Ethernet ports and SFP+
Product page for CRS320-8P-8B-4S+RM
CRS320-8P-8B-4S+RM
$489.00
*
SFP/SFP+
PoE
ARM
ROS v7
The first MikroTik high-power PoE++ switch – for easy and cost-effective powering of industry standard 802.3af/at/bt devices. Forget about countless power cables – create a cleaner space with PoE++!
Product page for CRS317-1G-16S+RM
CRS317-1G-16S+RM
$499.00
*
SFP/SFP+
ARM
Smart Switch, 1 x Gigabit LAN, 16 x SFP+ cages, Dual Core 800MHz CPU, 1GB RAM, 1U rackmount passive cooling case, Dual Power Supplies
Product page for CRS309-1G-8S+IN
CRS309-1G-8S+IN
$269.00
*
SFP/SFP+
PoE
ARM
Desktop switch with one Gigabit Ethernet port and eight SFP+ 10Gbps ports
Product page for CRS518-16XS-2XQ-RM
CRS518-16XS-2XQ-RM
$1,595.00
*
100G
ROS v7
A 100 Gigabit switch for enterprise networks and data centers. Hot-swappable parts and insane port density with 1.2 Tbps switching capacity!
Product page for CRS310-1G-5S-4S+IN
CRS310-1G-5S-4S+IN
$199.00
*
SFP/SFP+
PoE
ARM
ROS v7
10 Gigabit fibre connectivity way over a 100 meters – for small offices or ISPs. Hardware offloaded VLAN-filtering and even some L3 routing on a budget!
Product page for CRS310-8G+2S+IN
CRS310-8G+2S+IN
$219.00
*
SFP/SFP+
2.5G
ARM
ROS v7
Take advantage of the blazing fast 2.5/10 Gigabit combo and upgrade your workspace! This switch can utilize the full potential of RouterOS v7: run VLANs, Jumbo frames, link aggregation, ACL rules, and so much more!
Product page for netPower 16P
netPower 16P
$279.00
*
SFP/SFP+
PoE
ARM
Outdoors
IP 54
An outdoor 18 port switch with 16 Gigabit PoE-out ports and 2 SFP+. Power all your access points anywhere!
Product page for netPower 15FR
netPower 15FR
$169.00
*
SFP/SFP+
PoE
ARM
Outdoors
IP 54
An outdoor 18 port switch with 15 reverse PoE ports and SFP. Cut costs, not speed – choose GPEN over GPON!
Product page for netFiber 9
netFiber 9
$249.00
*
SFP/SFP+
PoE
ARM
Outdoors
IP 54
ROS v7
A remarkable outdoor switch for setting up an optical 10G network that can even perform some light routing. The spiritual successor to the beloved FiberBox. Gigabit Ethernet, SFP/SFP+, PoE.
Product page for CRS326-24G-2S+IN
CRS326-24G-2S+IN
$199.00
*...
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/Users/lukas/.screenpipe/data/data/2026-04-25/1777 /Users/lukas/.screenpipe/data/data/2026-04-25/1777129731836_m2.jpg...
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MikroTik · Switches — Personal
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mikrotik.com/products/group/switches
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monitor_2
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DXP4800PLUS-B5F8
Inbox (7) - [EMAIL] - Gmail
(56) DXP4800PLUS-B5F8
Inbox (7) - [EMAIL] - Gmail
(56) Inbox | [EMAIL] | Proton Mail
Welcome back
Welcome back
Western Digital Red Plus 3.5 6TB 5400rpm 256MB SATA3 (WD60EFPX) от 241,72 € (472,76 лв.) Вътрешен хард диск Western Digital - Pazaruvaj.com
Western Digital Red Plus 3.5 6TB 5400rpm 256MB SATA3 (WD60EFPX) от 241,72 € (472,76 лв.) Вътрешен хард диск Western Digital - Pazaruvaj.com
Today's Deals
Today's Deals
architecture - screenpipe docs
architecture - screenpipe docs
Claude Code works better when you stop treating it like a machine - [EMAIL] - Gmail
Claude Code works better when you stop treating it like a machine - [EMAIL] - Gmail
Screenpipe — Archive
Screenpipe — Archive
SQLite Web: archive.db
SQLite Web: archive.db
SQLite Web: db.sqlite
SQLite Web: db.sqlite
Claude Platform
Claude Platform
Hey @louis030195 Ill check during my - screenpipe.com
Hey @louis030195 Ill check during my - screenpipe.com
GitHub - screenpipe/screenpipe: Run agents that work for you based on what you do. AI finally knows what you are doing · GitHub
GitHub - screenpipe/screenpipe: Run agents that work for you based on what you do. AI finally knows what you are doing · GitHub
Gong Pricing in 2026: Costs, Plans & Is It Worth It?
Gong Pricing in 2026: Costs, Plans & Is It Worth It?
GLM 5.1 Thinks Strategically, Data-Center Revolt Intensifies, When Helpful LLMs Turn Unhelpful, Humanoid Robots Get to Work - [EMAIL] - Gmail
GLM 5.1 Thinks Strategically, Data-Center Revolt Intensifies, When Helpful LLMs Turn Unhelpful, Humanoid Robots Get to Work - [EMAIL] - Gmail
Gitea Official Website
Gitea Official Website
lakylak/screenpipe - screenpipe - Gitea: Git with a cup of tea
lakylak/screenpipe - screenpipe - Gitea: Git with a cup of tea
New Tab
New Tab
MikroTik · Switches
MikroTik · Switches
Close tab
New Tab
Customize sidebar
Open Le Chat Mistral (⌃X)
Open history (⇧⌘H)
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Skip to main content
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Go to home page
HOME
HOME
HARDWARE
HARDWARE
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Operating System
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Architecture
Product page for netPower Lite 8P
NEW
netPower Lite 8P
$199.00
*
SFP/SFP+
PoE
Outdoors
IP 54
Low-cost. Tough. And always ON! Compact PoE switch with built-in UPS and smart battery charger – because your CCTV cameras and access points deserve true off-the-grid resilience.
Product page for CRS804 DDQ
NEW
CRS804 DDQ
$1,295.00
*
400G
10G
ARM64
Quad-core CPU
ROS v7
A compact 1U 400G switch built for AI clusters, storage fabrics, and high-speed aggregation, featuring four 400G QSFP56-DD ports, dual 10 Gigabit Ethernet, and RouterOS v7. With hot-swap power supplies, robust cooling, and low power consumption, it delivers ultra-high bandwidth, wire-speed performance, and future-proof scalability at an accessible price point.
Product page for CRS304-4XG-IN
CRS304-4XG-IN
$199.00
*
10G
PoE
ARM64
ROS v7
Compact, powerful, and ready to simplify your 10 Gigabit network setups with 4x10G Ethernet ports ready to use out-of-the-box. No extra modules needed!
Product page for CRS305-1G-4S+IN
CRS305-1G-4S+IN
$149.00
*
SFP/SFP+
PoE
ARM
Five-port desktop switch with one Gigabit Ethernet port and four SFP+ 10Gbps ports
Product page for CRS312-4C+8XG-RM
CRS312-4C+8XG-RM
$699.00
*
10G
Combo ports
ROS v7
Switch of the future: the first MikroTik product with 10G RJ45 Ethernet ports and SFP+
Product page for CRS320-8P-8B-4S+RM
CRS320-8P-8B-4S+RM
$489.00
*
SFP/SFP+
PoE
ARM
ROS v7
The first MikroTik high-power PoE++ switch – for easy and cost-effective powering of industry standard 802.3af/at/bt devices. Forget about countless power cables – create a cleaner space with PoE++!
Product page for CRS317-1G-16S+RM
CRS317-1G-16S+RM
$499.00
*
SFP/SFP+
ARM
Smart Switch, 1 x Gigabit LAN, 16 x SFP+ cages, Dual Core 800MHz CPU, 1GB RAM, 1U rackmount passive cooling case, Dual Power Supplies
Product page for CRS309-1G-8S+IN
CRS309-1G-8S+IN
$269.00
*
SFP/SFP+
PoE
ARM
Desktop switch with one Gigabit Ethernet port and eight SFP+ 10Gbps ports
Product page for CRS518-16XS-2XQ-RM
CRS518-16XS-2XQ-RM
$1,595.00
*
100G
ROS v7
A 100 Gigabit switch for enterprise networks and data centers. Hot-swappable parts and insane port density with 1.2 Tbps switching capacity!
Product page for CRS310-1G-5S-4S+IN
CRS310-1G-5S-4S+IN
$199.00
*
SFP/SFP+
PoE
ARM
ROS v7
10 Gigabit fibre connectivity way over a 100 meters – for small offices or ISPs. Hardware offloaded VLAN-filtering and even some L3 routing on a budget!
Product page for CRS310-8G+2S+IN
CRS310-8G+2S+IN
$219.00
*
SFP/SFP+
2.5G
ARM
ROS v7
Take advantage of the blazing fast 2.5/10 Gigabit combo and upgrade your workspace! This switch can utilize the full potential of RouterOS v7: run VLANs, Jumbo frames, link aggregation, ACL rules, and so much more!
Product page for netPower 16P
netPower 16P
$279.00
*
SFP/SFP+
PoE
ARM
Outdoors
IP 54
An outdoor 18 port switch with 16 Gigabit PoE-out ports and 2 SFP+. Power all your access points anywhere!
Product page for netPower 15FR
netPower 15FR
$169.00
*
SFP/SFP+
PoE
ARM
Outdoors
IP 54
An outdoor 18 port switch with 15 reverse PoE ports and SFP. Cut costs, not speed – choose GPEN over GPON!
Product page for netFiber 9
netFiber 9
$249.00
*
SFP/SFP+
PoE
ARM
Outdoors
IP 54
ROS v7
A remarkable outdoor switch for setting up an optical 10G network that can even perform some light routing. The spiritual successor to the beloved FiberBox. Gigabit Ethernet, SFP/SFP+, PoE.
Product page for CRS326-24G-2S+IN
CRS326-24G-2S+IN
$199.00
*
SFP/SFP+
PoE
ARM
24 Gigabit ports, 2 SFP+ cages and a desktop case – server room power for your home!
Product page for CRS326-24G-2S+RM
CRS326-24G-2S+RM
$209.00
*
SFP/SFP+
PoE
ARM
24 Gigabit port switch with 2 x SFP+ cages in 1U rackmount case, Dual boot (RouterOS or SwitchOS)
Product page for CRS326-24S+2Q+RM
CRS326-24S+2Q+RM
$599.00
*
SFP/SFP+
40G
ROS v7
One of our faster switches for the most demanding setups.
Product page for CRS326-4C+20G+2Q+RM
CRS326-4C+20G+2Q+RM
$999.00
*
40G
2.5G
Combo ports
ROS v7
Our top-of-the-line switch with incredible 2.5 Gigabit port density, combo ports, and even a pair of 40 Gbps QSFP+ cages. Enterprise-level gamechanger… for the price of a smartphone!...
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DXP4800PLUS-B5F8
Inbox (7) - [EMAIL] - Gmail
(56) DXP4800PLUS-B5F8
Inbox (7) - [EMAIL] - Gmail
(56) Inbox | [EMAIL] | Proton Mail
Welcome back
Welcome back
Western Digital Red Plus 3.5 6TB 5400rpm 256MB SATA3 (WD60EFPX) от 241,72 € (472,76 лв.) Вътрешен хард диск Western Digital - Pazaruvaj.com
Western Digital Red Plus 3.5 6TB 5400rpm 256MB SATA3 (WD60EFPX) от 241,72 € (472,76 лв.) Вътрешен хард диск Western Digital - Pazaruvaj.com
Today's Deals
Today's Deals
architecture - screenpipe docs
architecture - screenpipe docs
Claude Code works better when you stop treating it like a machine - [EMAIL] - Gmail
Claude Code works better when you stop treating it like a machine - [EMAIL] - Gmail
Screenpipe — Archive
Screenpipe — Archive
SQLite Web: archive.db
SQLite Web: archive.db
SQLite Web: db.sqlite
SQLite Web: db.sqlite
Claude Platform
Claude Platform
Hey @louis030195 Ill check during my - screenpipe.com
Hey @louis030195 Ill check during my - screenpipe.com
GitHub - screenpipe/screenpipe: Run agents that work for you based on what you do. AI finally knows what you are doing · GitHub
GitHub - screenpipe/screenpipe: Run agents that work for you based on what you do. AI finally knows what you are doing · GitHub
Gong Pricing in 2026: Costs, Plans & Is It Worth It?
Gong Pricing in 2026: Costs, Plans & Is It Worth It?
GLM 5.1 Thinks Strategically, Data-Center Revolt Intensifies, When Helpful LLMs Turn Unhelpful, Humanoid Robots Get to Work - [EMAIL] - Gmail
GLM 5.1 Thinks Strategically, Data-Center Revolt Intensifies, When Helpful LLMs Turn Unhelpful, Humanoid Robots Get to Work - [EMAIL] - Gmail
Gitea Official Website
Gitea Official Website
lakylak/screenpipe - screenpipe - Gitea: Git with a cup of tea
lakylak/screenpipe - screenpipe - Gitea: Git with a cup of tea
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Product page for netPower Lite 8P
NEW
netPower Lite 8P
$199.00
*
SFP/SFP+
PoE
Outdoors
IP 54
Low-cost. Tough. And always ON! Compact PoE switch with built-in UPS and smart battery charger – because your CCTV cameras and access points deserve true off-the-grid resilience.
Product page for CRS804 DDQ
NEW
CRS804 DDQ
$1,295.00
*
400G
10G
ARM64
Quad-core CPU
ROS v7
A compact 1U 400G switch built for AI clusters, storage fabrics, and high-speed aggregation, featuring four 400G QSFP56-DD ports, dual 10 Gigabit Ethernet, and RouterOS v7. With hot-swap power supplies, robust cooling, and low power consumption, it delivers ultra-high bandwidth, wire-speed performance, and future-proof scalability at an accessible price point.
Product page for CRS304-4XG-IN
CRS304-4XG-IN
$199.00
*
10G
PoE
ARM64
ROS v7
Compact, powerful, and ready to simplify your 10 Gigabit network setups with 4x10G Ethernet ports ready to use out-of-the-box. No extra modules needed!
Product page for CRS305-1G-4S+IN
CRS305-1G-4S+IN
$149.00
*
SFP/SFP+
PoE
ARM
Five-port desktop switch with one Gigabit Ethernet port and four SFP+ 10Gbps ports
Product page for CRS312-4C+8XG-RM
CRS312-4C+8XG-RM
$699.00
*
10G
Combo ports
ROS v7
Switch of the future: the first MikroTik product with 10G RJ45 Ethernet ports and SFP+
Product page for CRS320-8P-8B-4S+RM
CRS320-8P-8B-4S+RM
$489.00
*
SFP/SFP+
PoE
ARM
ROS v7
The first MikroTik high-power PoE++ switch – for easy and cost-effective powering of industry standard 802.3af/at/bt devices. Forget about countless power cables – create a cleaner space with PoE++!
Product page for CRS317-1G-16S+RM
CRS317-1G-16S+RM
$499.00
*
SFP/SFP+
ARM
Smart Switch, 1 x Gigabit LAN, 16 x SFP+ cages, Dual Core 800MHz CPU, 1GB RAM, 1U rackmount passive cooling case, Dual Power Supplies
Product page for CRS309-1G-8S+IN
CRS309-1G-8S+IN
$269.00
*
SFP/SFP+
PoE
ARM
Desktop switch with one Gigabit Ethernet port and eight SFP+ 10Gbps ports
Product page for CRS518-16XS-2XQ-RM
CRS518-16XS-2XQ-RM
$1,595.00
*
100G
ROS v7
A 100 Gigabit switch for enterprise networks and data centers. Hot-swappable parts and insane port density with 1.2 Tbps switching capacity!
Product page for CRS310-1G-5S-4S+IN
CRS310-1G-5S-4S+IN
$199.00
*
SFP/SFP+
PoE
ARM
ROS v7
10 Gigabit fibre connectivity way over a 100 meters – for small offices or ISPs. Hardware offloaded VLAN-filtering and even some L3 routing on a budget!
Product page for CRS310-8G+2S+IN
CRS310-8G+2S+IN
$219.00
*
SFP/SFP+
2.5G
ARM
ROS v7
Take advantage of the blazing fast 2.5/10 Gigabit combo and upgrade your workspace! This switch can utilize the full potential of RouterOS v7: run VLANs, Jumbo frames, link aggregation, ACL rules, and so much more!
Product page for netPower 16P
netPower 16P
$279.00
*
SFP/SFP+
PoE
ARM
Outdoors
IP 54
An outdoor 18 port switch with 16 Gigabit PoE-out ports and 2 SFP+. Power all your access points anywhere!
Product page for netPower 15FR
netPower 15FR
$169.00
*
SFP/SFP+
PoE
ARM
Outdoors
IP 54
An outdoor 18 port switch with 15 reverse PoE ports and SFP. Cut costs, not speed – choose GPEN over GPON!
Product page for netFiber 9
netFiber 9
$249.00
*
SFP/SFP+
PoE
ARM
Outdoors
IP 54
ROS v7
A remarkable outdoor switch for setting up an optical 10G network that can even perform some light routing. The spiritual successor to the beloved FiberBox. Gigabit Ethernet, SFP/SFP+, PoE.
Product page for CRS326-24G-2S+IN
CRS326-24G-2S+IN
$199.00
*
SFP/SFP+
PoE
ARM
24 Gigabit ports, 2 SFP+ cages and a desktop case – server room power for your home!
Product page for CRS326-24G-2S+RM
CRS326-24G-2S+RM
$209.00
*
SFP/SFP+
PoE
ARM
24 Gigabit port switch with 2 x SFP+ cages in 1U rackmount case, Dual boot (RouterOS or SwitchOS)
Product page for CRS326-24S+2Q+RM
CRS326-24S+2Q+RM
$599.00
*
SFP/SFP+
40G
ROS v7
One of our faster switches for the most demanding setups.
Product page for CRS326-4C+20G+2Q+RM
CRS326-4C+20G+2Q+RM
$999.00
*
40G
2.5G
Combo ports
ROS v7
Our top-of-the-line switch with incredible 2.5 Gigabit port density, combo ports, and even a pair of 40 Gbps QSFP+ cages. Enterprise-level gamechanger… for the price of a smartphone!...
|
80870
|
|
80873
|
2140
|
21
|
2026-04-25T15:09:00.906327+00:00
|
/Users/lukas/.screenpipe/data/data/2026-04-25/1777 /Users/lukas/.screenpipe/data/data/2026-04-25/1777129740906_m2.jpg...
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Firefox
|
MikroTik · Switches — Personal
|
True
|
mikrotik.com/products/group/switches
|
monitor_2
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NULL
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NULL
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NULL
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NULL
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Product page for CRS304-4XG-IN
DXP4800PLUS-B5F8
In Product page for CRS304-4XG-IN
DXP4800PLUS-B5F8
Inbox (7) - [EMAIL] - Gmail
(56) Inbox | [EMAIL] | Proton Mail
Welcome back
Welcome back
Western Digital Red Plus 3.5 6TB 5400rpm 256MB SATA3 (WD60EFPX) от 241,72 € (472,76 лв.) Вътрешен хард диск Western Digital - Pazaruvaj.com
Western Digital Red Plus 3.5 6TB 5400rpm 256MB SATA3 (WD60EFPX) от 241,72 € (472,76 лв.) Вътрешен хард диск Western Digital - Pazaruvaj.com
Today's Deals
Today's Deals
architecture - screenpipe docs
architecture - screenpipe docs
Claude Code works better when you stop treating it like a machine - [EMAIL] - Gmail
Claude Code works better when you stop treating it like a machine - [EMAIL] - Gmail
Screenpipe — Archive
Screenpipe — Archive
SQLite Web: archive.db
SQLite Web: archive.db
SQLite Web: db.sqlite
SQLite Web: db.sqlite
Claude Platform
Claude Platform
Hey @louis030195 Ill check during my - screenpipe.com
Hey @louis030195 Ill check during my - screenpipe.com
GitHub - screenpipe/screenpipe: Run agents that work for you based on what you do. AI finally knows what you are doing · GitHub
GitHub - screenpipe/screenpipe: Run agents that work for you based on what you do. AI finally knows what you are doing · GitHub
Gong Pricing in 2026: Costs, Plans & Is It Worth It?
Gong Pricing in 2026: Costs, Plans & Is It Worth It?
GLM 5.1 Thinks Strategically, Data-Center Revolt Intensifies, When Helpful LLMs Turn Unhelpful, Humanoid Robots Get to Work - [EMAIL] - Gmail
GLM 5.1 Thinks Strategically, Data-Center Revolt Intensifies, When Helpful LLMs Turn Unhelpful, Humanoid Robots Get to Work - [EMAIL] - Gmail
Gitea Official Website
Gitea Official Website
lakylak/screenpipe - screenpipe - Gitea: Git with a cup of tea
lakylak/screenpipe - screenpipe - Gitea: Git with a cup of tea
New Tab
New Tab
MikroTik · Switches
MikroTik · Switches
Close tab
New Tab
Customize sidebar
Open Le Chat Mistral (⌃X)
Open history (⇧⌘H)
Open bookmarks (⌘B)
Bitwarden
Skip to main content
Skip to main content
Go to home page
HOME
HOME
HARDWARE
HARDWARE
SWITCHES
SWITCHES
Status
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Wired Interfaces
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Features
Features
Operating System
Operating System
Architecture
Architecture
Product page for netPower Lite 8P
NEW
netPower Lite 8P
$199.00
*
SFP/SFP+
PoE
Outdoors
IP 54
Low-cost. Tough. And always ON! Compact PoE switch with built-in UPS and smart battery charger – because your CCTV cameras and access points deserve true off-the-grid resilience.
Product page for CRS804 DDQ
NEW
CRS804 DDQ
$1,295.00
*
400G
10G
ARM64
Quad-core CPU
ROS v7
A compact 1U 400G switch built for AI clusters, storage fabrics, and high-speed aggregation, featuring four 400G QSFP56-DD ports, dual 10 Gigabit Ethernet, and RouterOS v7. With hot-swap power supplies, robust cooling, and low power consumption, it delivers ultra-high bandwidth, wire-speed performance, and future-proof scalability at an accessible price point.
Product page for CRS304-4XG-IN
CRS304-4XG-IN
$199.00
*
10G
PoE
ARM64
ROS v7
Compact, powerful, and ready to simplify your 10 Gigabit network setups with 4x10G Ethernet ports ready to use out-of-the-box. No extra modules needed!
Product page for CRS305-1G-4S+IN
CRS305-1G-4S+IN
$149.00
*
SFP/SFP+
PoE
ARM
Five-port desktop switch with one Gigabit Ethernet port and four SFP+ 10Gbps ports
Product page for CRS312-4C+8XG-RM
CRS312-4C+8XG-RM
$699.00
*
10G
Combo ports
ROS v7
Switch of the future: the first MikroTik product with 10G RJ45 Ethernet ports and SFP+
Product page for CRS320-8P-8B-4S+RM
CRS320-8P-8B-4S+RM
$489.00
*
SFP/SFP+
PoE
ARM
ROS v7
The first MikroTik high-power PoE++ switch – for easy and cost-effective powering of industry standard 802.3af/at/bt devices. Forget about countless power cables – create a cleaner space with PoE++!
Product page for CRS317-1G-16S+RM
CRS317-1G-16S+RM
$499.00
*
SFP/SFP+
ARM
Smart Switch, 1 x Gigabit LAN, 16 x SFP+ cages, Dual Core 800MHz CPU, 1GB RAM, 1U rackmount passive cooling case, Dual Power Supplies
Product page for CRS309-1G-8S+IN
CRS309-1G-8S+IN
$269.00
*
SFP/SFP+
PoE
ARM
Desktop switch with one Gigabit Ethernet port and eight SFP+ 10Gbps ports
Product page for CRS518-16XS-2XQ-RM
CRS518-16XS-2XQ-RM
$1,595.00
*
100G
ROS v7
A 100 Gigabit switch for enterprise networks and data centers. Hot-swappable parts and insane port density with 1.2 Tbps switching capacity!
Product page for CRS310-1G-5S-4S+IN
CRS310-1G-5S-4S+IN
$199.00
*
SFP/SFP+
PoE
ARM
ROS v7
10 Gigabit fibre connectivity way over a 100 meters – for small offices or ISPs. Hardware offloaded VLAN-filtering and even some L3 routing on a budget!
Product page for CRS310-8G+2S+IN
CRS310-8G+2S+IN
$219.00
*
SFP/SFP+
2.5G
ARM
ROS v7
Take advantage of the blazing fast 2.5/10 Gigabit combo and upgrade your workspace! This switch can utilize the full potential of RouterOS v7: run VLANs, Jumbo frames, link aggregation, ACL rules, and so much more!
Product page for netPower 16P
netPower 16P
$279.00
*
SFP/SFP+
PoE
ARM
Outdoors
IP 54
An outdoor 18 port switch with 16 Gigabit PoE-out ports and 2 SFP+. Power all your access points anywhere!
Product page for netPower 15FR
netPower 15FR
$169.00
*
SFP/SFP+
PoE
ARM
Outdoors
IP 54
An outdoor 18 port switch with 15 reverse PoE ports and SFP. Cut costs, not speed – choose GPEN over GPON!
Product page for netFiber 9
netFiber 9
$249.00
*
SFP/SFP+
PoE
ARM
Outdoors
IP 54
ROS v7
A remarkable outdoor switch for setting up an optical 10G network that can even perform some light routing. The spiritual successor to the beloved FiberBox. Gigabit Ethernet, SFP/SFP+, PoE.
Product page for CRS326-24G-2S+IN
CRS326-24G-2S+IN
$199.00
*
SFP/SFP+
PoE
ARM
24 Gigabit ports, 2 SFP+ cages and a desktop case – server room power for your home!
Product page for CRS326-24G-2S+RM
CRS326-24G-2S+RM
$209.00
*
SFP/SFP+
PoE
ARM
24 Gigabit port switch with 2 x SFP+ cages in 1U rackmount case, Dual boot (RouterOS or SwitchOS)
Product page for CRS326-24S+2Q+RM
CRS326-24S+2Q+RM
$599.00
*
SFP/SFP+
40G
ROS v7
One of our faster switches for the most demanding setups.
Product page for CRS326-4C+20G+2Q+RM
CRS326-4C+20G+2Q+RM
$999.00
*
40G
2.5G...
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Product page for CRS304-4XG-IN
DXP4800PLUS-B5F8
In Product page for CRS304-4XG-IN
DXP4800PLUS-B5F8
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Western Digital Red Plus 3.5 6TB 5400rpm 256MB SATA3 (WD60EFPX) от 241,72 € (472,76 лв.) Вътрешен хард диск Western Digital - Pazaruvaj.com
Western Digital Red Plus 3.5 6TB 5400rpm 256MB SATA3 (WD60EFPX) от 241,72 € (472,76 лв.) Вътрешен хард диск Western Digital - Pazaruvaj.com
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architecture - screenpipe docs
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Claude Code works better when you stop treating it like a machine - [EMAIL] - Gmail
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SQLite Web: archive.db
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Claude Platform
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Hey @louis030195 Ill check during my - screenpipe.com
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GitHub - screenpipe/screenpipe: Run agents that work for you based on what you do. AI finally knows what you are doing · GitHub
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Gong Pricing in 2026: Costs, Plans & Is It Worth It?
Gong Pricing in 2026: Costs, Plans & Is It Worth It?
GLM 5.1 Thinks Strategically, Data-Center Revolt Intensifies, When Helpful LLMs Turn Unhelpful, Humanoid Robots Get to Work - [EMAIL] - Gmail
GLM 5.1 Thinks Strategically, Data-Center Revolt Intensifies, When Helpful LLMs Turn Unhelpful, Humanoid Robots Get to Work - [EMAIL] - Gmail
Gitea Official Website
Gitea Official Website
lakylak/screenpipe - screenpipe - Gitea: Git with a cup of tea
lakylak/screenpipe - screenpipe - Gitea: Git with a cup of tea
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netPower Lite 8P
$199.00
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SFP/SFP+
PoE
Outdoors
IP 54
Low-cost. Tough. And always ON! Compact PoE switch with built-in UPS and smart battery charger – because your CCTV cameras and access points deserve true off-the-grid resilience.
Product page for CRS804 DDQ
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CRS804 DDQ
$1,295.00
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400G
10G
ARM64
Quad-core CPU
ROS v7
A compact 1U 400G switch built for AI clusters, storage fabrics, and high-speed aggregation, featuring four 400G QSFP56-DD ports, dual 10 Gigabit Ethernet, and RouterOS v7. With hot-swap power supplies, robust cooling, and low power consumption, it delivers ultra-high bandwidth, wire-speed performance, and future-proof scalability at an accessible price point.
Product page for CRS304-4XG-IN
CRS304-4XG-IN
$199.00
*
10G
PoE
ARM64
ROS v7
Compact, powerful, and ready to simplify your 10 Gigabit network setups with 4x10G Ethernet ports ready to use out-of-the-box. No extra modules needed!
Product page for CRS305-1G-4S+IN
CRS305-1G-4S+IN
$149.00
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SFP/SFP+
PoE
ARM
Five-port desktop switch with one Gigabit Ethernet port and four SFP+ 10Gbps ports
Product page for CRS312-4C+8XG-RM
CRS312-4C+8XG-RM
$699.00
*
10G
Combo ports
ROS v7
Switch of the future: the first MikroTik product with 10G RJ45 Ethernet ports and SFP+
Product page for CRS320-8P-8B-4S+RM
CRS320-8P-8B-4S+RM
$489.00
*
SFP/SFP+
PoE
ARM
ROS v7
The first MikroTik high-power PoE++ switch – for easy and cost-effective powering of industry standard 802.3af/at/bt devices. Forget about countless power cables – create a cleaner space with PoE++!
Product page for CRS317-1G-16S+RM
CRS317-1G-16S+RM
$499.00
*
SFP/SFP+
ARM
Smart Switch, 1 x Gigabit LAN, 16 x SFP+ cages, Dual Core 800MHz CPU, 1GB RAM, 1U rackmount passive cooling case, Dual Power Supplies
Product page for CRS309-1G-8S+IN
CRS309-1G-8S+IN
$269.00
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SFP/SFP+
PoE
ARM
Desktop switch with one Gigabit Ethernet port and eight SFP+ 10Gbps ports
Product page for CRS518-16XS-2XQ-RM
CRS518-16XS-2XQ-RM
$1,595.00
*
100G
ROS v7
A 100 Gigabit switch for enterprise networks and data centers. Hot-swappable parts and insane port density with 1.2 Tbps switching capacity!
Product page for CRS310-1G-5S-4S+IN
CRS310-1G-5S-4S+IN
$199.00
*
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PoE
ARM
ROS v7
10 Gigabit fibre connectivity way over a 100 meters – for small offices or ISPs. Hardware offloaded VLAN-filtering and even some L3 routing on a budget!
Product page for CRS310-8G+2S+IN
CRS310-8G+2S+IN
$219.00
*
SFP/SFP+
2.5G
ARM
ROS v7
Take advantage of the blazing fast 2.5/10 Gigabit combo and upgrade your workspace! This switch can utilize the full potential of RouterOS v7: run VLANs, Jumbo frames, link aggregation, ACL rules, and so much more!
Product page for netPower 16P
netPower 16P
$279.00
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PoE
ARM
Outdoors
IP 54
An outdoor 18 port switch with 16 Gigabit PoE-out ports and 2 SFP+. Power all your access points anywhere!
Product page for netPower 15FR
netPower 15FR
$169.00
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PoE
ARM
Outdoors
IP 54
An outdoor 18 port switch with 15 reverse PoE ports and SFP. Cut costs, not speed – choose GPEN over GPON!
Product page for netFiber 9
netFiber 9
$249.00
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PoE
ARM
Outdoors
IP 54
ROS v7
A remarkable outdoor switch for setting up an optical 10G network that can even perform some light routing. The spiritual successor to the beloved FiberBox. Gigabit Ethernet, SFP/SFP+, PoE.
Product page for CRS326-24G-2S+IN
CRS326-24G-2S+IN
$199.00
*
SFP/SFP+
PoE
ARM
24 Gigabit ports, 2 SFP+ cages and a desktop case – server room power for your home!
Product page for CRS326-24G-2S+RM
CRS326-24G-2S+RM
$209.00
*
SFP/SFP+
PoE
ARM
24 Gigabit port switch with 2 x SFP+ cages in 1U rackmount case, Dual boot (RouterOS or SwitchOS)
Product page for CRS326-24S+2Q+RM
CRS326-24S+2Q+RM
$599.00
*
SFP/SFP+
40G
ROS v7
One of our faster switches for the most demanding setups.
Product page for CRS326-4C+20G+2Q+RM
CRS326-4C+20G+2Q+RM
$999.00
*
40G
2.5G...
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DXP4800PLUS-B5F8
Inbox (7) - [EMAIL] - Gmail
(56) DXP4800PLUS-B5F8
Inbox (7) - [EMAIL] - Gmail
(56) Inbox | [EMAIL] | Proton Mail
Welcome back
Welcome back
Western Digital Red Plus 3.5 6TB 5400rpm 256MB SATA3 (WD60EFPX) от 241,72 € (472,76 лв.) Вътрешен хард диск Western Digital - Pazaruvaj.com
Western Digital Red Plus 3.5 6TB 5400rpm 256MB SATA3 (WD60EFPX) от 241,72 € (472,76 лв.) Вътрешен хард диск Western Digital - Pazaruvaj.com
Today's Deals
Today's Deals
architecture - screenpipe docs
architecture - screenpipe docs
Claude Code works better when you stop treating it like a machine - [EMAIL] - Gmail
Claude Code works better when you stop treating it like a machine - [EMAIL] - Gmail
Screenpipe — Archive
Screenpipe — Archive
SQLite Web: archive.db
SQLite Web: archive.db
SQLite Web: db.sqlite
SQLite Web: db.sqlite
Claude Platform
Claude Platform
Hey @louis030195 Ill check during my - screenpipe.com
Hey @louis030195 Ill check during my - screenpipe.com
GitHub - screenpipe/screenpipe: Run agents that work for you based on what you do. AI finally knows what you are doing · GitHub
GitHub - screenpipe/screenpipe: Run agents that work for you based on what you do. AI finally knows what you are doing · GitHub
Gong Pricing in 2026: Costs, Plans & Is It Worth It?
Gong Pricing in 2026: Costs, Plans & Is It Worth It?
GLM 5.1 Thinks Strategically, Data-Center Revolt Intensifies, When Helpful LLMs Turn Unhelpful, Humanoid Robots Get to Work - [EMAIL] - Gmail
GLM 5.1 Thinks Strategically, Data-Center Revolt Intensifies, When Helpful LLMs Turn Unhelpful, Humanoid Robots Get to Work - [EMAIL] - Gmail
Gitea Official Website
Gitea Official Website
lakylak/screenpipe - screenpipe - Gitea: Git with a cup of tea
lakylak/screenpipe - screenpipe - Gitea: Git with a cup of tea
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NEW
netPower Lite 8P
$199.00
*
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Outdoors
IP 54
Low-cost. Tough. And always ON! Compact PoE switch with built-in UPS and smart battery charger – because your CCTV cameras and access points deserve true off-the-grid resilience.
Product page for CRS804 DDQ
NEW
CRS804 DDQ
$1,295.00
*
400G
10G
ARM64
Quad-core CPU
ROS v7
A compact 1U 400G switch built for AI clusters, storage fabrics, and high-speed aggregation, featuring four 400G QSFP56-DD ports, dual 10 Gigabit Ethernet, and RouterOS v7. With hot-swap power supplies, robust cooling, and low power consumption, it delivers ultra-high bandwidth, wire-speed performance, and future-proof scalability at an accessible price point.
Product page for CRS304-4XG-IN
CRS304-4XG-IN
$199.00
*
10G
PoE
ARM64
ROS v7
Compact, powerful, and ready to simplify your 10 Gigabit network setups with 4x10G Ethernet ports ready to use out-of-the-box. No extra modules needed!
Product page for CRS305-1G-4S+IN
CRS305-1G-4S+IN
$149.00
*
SFP/SFP+
PoE
ARM
Five-port desktop switch with one Gigabit Ethernet port and four SFP+ 10Gbps ports
Product page for CRS312-4C+8XG-RM
CRS312-4C+8XG-RM
$699.00
*
10G
Combo ports
ROS v7
Switch of the future: the first MikroTik product with 10G RJ45 Ethernet ports and SFP+
Product page for CRS320-8P-8B-4S+RM
CRS320-8P-8B-4S+RM...
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DXP4800PLUS-B5F8
Inbox (7) - [EMAIL] - Gmail
(56) DXP4800PLUS-B5F8
Inbox (7) - [EMAIL] - Gmail
(56) Inbox | [EMAIL] | Proton Mail
Welcome back
Welcome back
Western Digital Red Plus 3.5 6TB 5400rpm 256MB SATA3 (WD60EFPX) от 241,72 € (472,76 лв.) Вътрешен хард диск Western Digital - Pazaruvaj.com
Western Digital Red Plus 3.5 6TB 5400rpm 256MB SATA3 (WD60EFPX) от 241,72 € (472,76 лв.) Вътрешен хард диск Western Digital - Pazaruvaj.com
Today's Deals
Today's Deals
architecture - screenpipe docs
architecture - screenpipe docs
Claude Code works better when you stop treating it like a machine - [EMAIL] - Gmail
Claude Code works better when you stop treating it like a machine - [EMAIL] - Gmail
Screenpipe — Archive
Screenpipe — Archive
SQLite Web: archive.db
SQLite Web: archive.db
SQLite Web: db.sqlite
SQLite Web: db.sqlite
Claude Platform
Claude Platform
Hey @louis030195 Ill check during my - screenpipe.com
Hey @louis030195 Ill check during my - screenpipe.com
GitHub - screenpipe/screenpipe: Run agents that work for you based on what you do. AI finally knows what you are doing · GitHub
GitHub - screenpipe/screenpipe: Run agents that work for you based on what you do. AI finally knows what you are doing · GitHub
Gong Pricing in 2026: Costs, Plans & Is It Worth It?
Gong Pricing in 2026: Costs, Plans & Is It Worth It?
GLM 5.1 Thinks Strategically, Data-Center Revolt Intensifies, When Helpful LLMs Turn Unhelpful, Humanoid Robots Get to Work - [EMAIL] - Gmail
GLM 5.1 Thinks Strategically, Data-Center Revolt Intensifies, When Helpful LLMs Turn Unhelpful, Humanoid Robots Get to Work - [EMAIL] - Gmail
Gitea Official Website
Gitea Official Website
lakylak/screenpipe - screenpipe - Gitea: Git with a cup of tea
lakylak/screenpipe - screenpipe - Gitea: Git with a cup of tea
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Product page for netPower Lite 8P
NEW
netPower Lite 8P
$199.00
*
SFP/SFP+
PoE
Outdoors
IP 54
Low-cost. Tough. And always ON! Compact PoE switch with built-in UPS and smart battery charger – because your CCTV cameras and access points deserve true off-the-grid resilience.
Product page for CRS804 DDQ
NEW
CRS804 DDQ
$1,295.00
*
400G
10G
ARM64
Quad-core CPU
ROS v7
A compact 1U 400G switch built for AI clusters, storage fabrics, and high-speed aggregation, featuring four 400G QSFP56-DD ports, dual 10 Gigabit Ethernet, and RouterOS v7. With hot-swap power supplies, robust cooling, and low power consumption, it delivers ultra-high bandwidth, wire-speed performance, and future-proof scalability at an accessible price point.
Product page for CRS304-4XG-IN
CRS304-4XG-IN
$199.00
*
10G
PoE
ARM64
ROS v7
Compact, powerful, and ready to simplify your 10 Gigabit network setups with 4x10G Ethernet ports ready to use out-of-the-box. No extra modules needed!
Product page for CRS305-1G-4S+IN
CRS305-1G-4S+IN
$149.00
*
SFP/SFP+
PoE
ARM
Five-port desktop switch with one Gigabit Ethernet port and four SFP+ 10Gbps ports
Product page for CRS312-4C+8XG-RM
CRS312-4C+8XG-RM
$699.00
*
10G
Combo ports
ROS v7
Switch of the future: the first MikroTik product with 10G RJ45 Ethernet ports and SFP+
Product page for CRS320-8P-8B-4S+RM
CRS320-8P-8B-4S+RM...
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80875
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2140
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22
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2026-04-25T15:09:02.578466+00:00
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Firefox
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MikroTik · Switches — Personal
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True
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mikrotik.com/products/group/switches
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monitor_2
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NULL
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NULL
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NULL
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NULL
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DXP4800PLUS-B5F8
Inbox (7) - [EMAIL] - Gmail
(56) DXP4800PLUS-B5F8
Inbox (7) - [EMAIL] - Gmail
(56) Inbox | [EMAIL] | Proton Mail
Welcome back
Welcome back
Western Digital Red Plus 3.5 6TB 5400rpm 256MB SATA3 (WD60EFPX) от 241,72 € (472,76 лв.) Вътрешен хард диск Western Digital - Pazaruvaj.com
Western Digital Red Plus 3.5 6TB 5400rpm 256MB SATA3 (WD60EFPX) от 241,72 € (472,76 лв.) Вътрешен хард диск Western Digital - Pazaruvaj.com
Today's Deals
Today's Deals
architecture - screenpipe docs
architecture - screenpipe docs
Claude Code works better when you stop treating it like a machine - [EMAIL] - Gmail
Claude Code works better when you stop treating it like a machine - [EMAIL] - Gmail
Screenpipe — Archive
Screenpipe — Archive
SQLite Web: archive.db
SQLite Web: archive.db
SQLite Web: db.sqlite
SQLite Web: db.sqlite
Claude Platform
Claude Platform
Hey @louis030195 Ill check during my - screenpipe.com
Hey @louis030195 Ill check during my - screenpipe.com
GitHub - screenpipe/screenpipe: Run agents that work for you based on what you do. AI finally knows what you are doing · GitHub
GitHub - screenpipe/screenpipe: Run agents that work for you based on what you do. AI finally knows what you are doing · GitHub
Gong Pricing in 2026: Costs, Plans & Is It Worth It?
Gong Pricing in 2026: Costs, Plans & Is It Worth It?
GLM 5.1 Thinks Strategically, Data-Center Revolt Intensifies, When Helpful LLMs Turn Unhelpful, Humanoid Robots Get to Work - [EMAIL] - Gmail
GLM 5.1 Thinks Strategically, Data-Center Revolt Intensifies, When Helpful LLMs Turn Unhelpful, Humanoid Robots Get to Work - [EMAIL] - Gmail
Gitea Official Website
Gitea Official Website
lakylak/screenpipe - screenpipe - Gitea: Git with a cup of tea
lakylak/screenpipe - screenpipe - Gitea: Git with a cup of tea
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MikroTik · Switches
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Close tab
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Go to home page
HOME
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HARDWARE
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Status
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Operating System
Architecture
Architecture
Product page for netPower Lite 8P
NEW
netPower Lite 8P
$199.00
*
SFP/SFP+
PoE
Outdoors
IP 54
Low-cost. Tough. And always ON! Compact PoE switch with built-in UPS and smart battery charger – because your CCTV cameras and access points deserve true off-the-grid resilience.
Product page for CRS804 DDQ
NEW
CRS804 DDQ
$1,295.00
*
400G
10G
ARM64
Quad-core CPU
ROS v7
A compact 1U 400G switch built for AI clusters, storage fabrics, and high-speed aggregation, featuring four 400G QSFP56-DD ports, dual 10 Gigabit Ethernet, and RouterOS v7. With hot-swap power supplies, robust cooling, and low power consumption, it delivers ultra-high bandwidth, wire-speed performance, and future-proof scalability at an accessible price point.
Product page for CRS304-4XG-IN
CRS304-4XG-IN
$199.00
*
10G
PoE
ARM64
ROS v7
Compact, powerful, and ready to simplify your 10 Gigabit network setups with 4x10G Ethernet ports ready to use out-of-the-box. No extra modules needed!
Product page for CRS305-1G-4S+IN
CRS305-1G-4S+IN
$149.00
*
SFP/SFP+
PoE
ARM
Five-port desktop switch with one Gigabit Ethernet port and four SFP+ 10Gbps ports
Product page for CRS312-4C+8XG-RM
CRS312-4C+8XG-RM
$699.00
*
10G
Combo ports
ROS v7
Switch of the future: the first MikroTik product with 10G RJ45 Ethernet ports and SFP+
Product page for CRS320-8P-8B-4S+RM
CRS320-8P-8B-4S+RM
$489.00
*
SFP/SFP+
PoE
ARM
ROS v7
The first MikroTik high-power PoE++ switch – for easy and cost-effective powering of industry standard 802.3af/at/bt devices. Forget about countless power cables – create a cleaner space with PoE++!
Product page for CRS317-1G-16S+RM
CRS317-1G-16S+RM
$499.00
*
SFP/SFP+
ARM
Smart Switch, 1 x Gigabit LAN, 16 x SFP+ cages, Dual Core 800MHz CPU, 1GB RAM, 1U rackmount passive cooling case, Dual Power Supplies
Product page for CRS309-1G-8S+IN
CRS309-1G-8S+IN
$269.00
*
SFP/SFP+
PoE
ARM
Desktop switch with one Gigabit Ethernet port and eight SFP+ 10Gbps ports
Product page for CRS518-16XS-2XQ-RM
CRS518-16XS-2XQ-RM
$1,595.00
*
100G
ROS v7
A 100 Gigabit switch for enterprise networks and data centers. Hot-swappable parts and insane port density with 1.2 Tbps switching capacity!
Product page for CRS310-1G-5S-4S+IN
CRS310-1G-5S-4S+IN
$199.00
*
SFP/SFP+
PoE
ARM
ROS v7
10 Gigabit fibre connectivity way over a 100 meters – for small offices or ISPs. Hardware offloaded VLAN-filtering and even some L3 routing on a budget!
Product page for CRS310-8G+2S+IN
CRS310-8G+2S+IN
$219.00
*
SFP/SFP+
2.5G
ARM
ROS v7
Take advantage of the blazing fast 2.5/10 Gigabit combo and upgrade your workspace! This switch can utilize the full potential of RouterOS v7: run VLANs, Jumbo frames, link aggregation, ACL rules, and so much more!
Product page for netPower 16P
netPower 16P
$279.00
*
SFP/SFP+
PoE
ARM
Outdoors
IP 54
An outdoor 18 port switch with 16 Gigabit PoE-out ports and 2 SFP+. Power all your access points anywhere!...
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5977766471226844178
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click
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accessibility
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NULL
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DXP4800PLUS-B5F8
Inbox (7) - [EMAIL] - Gmail
(56) DXP4800PLUS-B5F8
Inbox (7) - [EMAIL] - Gmail
(56) Inbox | [EMAIL] | Proton Mail
Welcome back
Welcome back
Western Digital Red Plus 3.5 6TB 5400rpm 256MB SATA3 (WD60EFPX) от 241,72 € (472,76 лв.) Вътрешен хард диск Western Digital - Pazaruvaj.com
Western Digital Red Plus 3.5 6TB 5400rpm 256MB SATA3 (WD60EFPX) от 241,72 € (472,76 лв.) Вътрешен хард диск Western Digital - Pazaruvaj.com
Today's Deals
Today's Deals
architecture - screenpipe docs
architecture - screenpipe docs
Claude Code works better when you stop treating it like a machine - [EMAIL] - Gmail
Claude Code works better when you stop treating it like a machine - [EMAIL] - Gmail
Screenpipe — Archive
Screenpipe — Archive
SQLite Web: archive.db
SQLite Web: archive.db
SQLite Web: db.sqlite
SQLite Web: db.sqlite
Claude Platform
Claude Platform
Hey @louis030195 Ill check during my - screenpipe.com
Hey @louis030195 Ill check during my - screenpipe.com
GitHub - screenpipe/screenpipe: Run agents that work for you based on what you do. AI finally knows what you are doing · GitHub
GitHub - screenpipe/screenpipe: Run agents that work for you based on what you do. AI finally knows what you are doing · GitHub
Gong Pricing in 2026: Costs, Plans & Is It Worth It?
Gong Pricing in 2026: Costs, Plans & Is It Worth It?
GLM 5.1 Thinks Strategically, Data-Center Revolt Intensifies, When Helpful LLMs Turn Unhelpful, Humanoid Robots Get to Work - [EMAIL] - Gmail
GLM 5.1 Thinks Strategically, Data-Center Revolt Intensifies, When Helpful LLMs Turn Unhelpful, Humanoid Robots Get to Work - [EMAIL] - Gmail
Gitea Official Website
Gitea Official Website
lakylak/screenpipe - screenpipe - Gitea: Git with a cup of tea
lakylak/screenpipe - screenpipe - Gitea: Git with a cup of tea
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Product page for netPower Lite 8P
NEW
netPower Lite 8P
$199.00
*
SFP/SFP+
PoE
Outdoors
IP 54
Low-cost. Tough. And always ON! Compact PoE switch with built-in UPS and smart battery charger – because your CCTV cameras and access points deserve true off-the-grid resilience.
Product page for CRS804 DDQ
NEW
CRS804 DDQ
$1,295.00
*
400G
10G
ARM64
Quad-core CPU
ROS v7
A compact 1U 400G switch built for AI clusters, storage fabrics, and high-speed aggregation, featuring four 400G QSFP56-DD ports, dual 10 Gigabit Ethernet, and RouterOS v7. With hot-swap power supplies, robust cooling, and low power consumption, it delivers ultra-high bandwidth, wire-speed performance, and future-proof scalability at an accessible price point.
Product page for CRS304-4XG-IN
CRS304-4XG-IN
$199.00
*
10G
PoE
ARM64
ROS v7
Compact, powerful, and ready to simplify your 10 Gigabit network setups with 4x10G Ethernet ports ready to use out-of-the-box. No extra modules needed!
Product page for CRS305-1G-4S+IN
CRS305-1G-4S+IN
$149.00
*
SFP/SFP+
PoE
ARM
Five-port desktop switch with one Gigabit Ethernet port and four SFP+ 10Gbps ports
Product page for CRS312-4C+8XG-RM
CRS312-4C+8XG-RM
$699.00
*
10G
Combo ports
ROS v7
Switch of the future: the first MikroTik product with 10G RJ45 Ethernet ports and SFP+
Product page for CRS320-8P-8B-4S+RM
CRS320-8P-8B-4S+RM
$489.00
*
SFP/SFP+
PoE
ARM
ROS v7
The first MikroTik high-power PoE++ switch – for easy and cost-effective powering of industry standard 802.3af/at/bt devices. Forget about countless power cables – create a cleaner space with PoE++!
Product page for CRS317-1G-16S+RM
CRS317-1G-16S+RM
$499.00
*
SFP/SFP+
ARM
Smart Switch, 1 x Gigabit LAN, 16 x SFP+ cages, Dual Core 800MHz CPU, 1GB RAM, 1U rackmount passive cooling case, Dual Power Supplies
Product page for CRS309-1G-8S+IN
CRS309-1G-8S+IN
$269.00
*
SFP/SFP+
PoE
ARM
Desktop switch with one Gigabit Ethernet port and eight SFP+ 10Gbps ports
Product page for CRS518-16XS-2XQ-RM
CRS518-16XS-2XQ-RM
$1,595.00
*
100G
ROS v7
A 100 Gigabit switch for enterprise networks and data centers. Hot-swappable parts and insane port density with 1.2 Tbps switching capacity!
Product page for CRS310-1G-5S-4S+IN
CRS310-1G-5S-4S+IN
$199.00
*
SFP/SFP+
PoE
ARM
ROS v7
10 Gigabit fibre connectivity way over a 100 meters – for small offices or ISPs. Hardware offloaded VLAN-filtering and even some L3 routing on a budget!
Product page for CRS310-8G+2S+IN
CRS310-8G+2S+IN
$219.00
*
SFP/SFP+
2.5G
ARM
ROS v7
Take advantage of the blazing fast 2.5/10 Gigabit combo and upgrade your workspace! This switch can utilize the full potential of RouterOS v7: run VLANs, Jumbo frames, link aggregation, ACL rules, and so much more!
Product page for netPower 16P
netPower 16P
$279.00
*
SFP/SFP+
PoE
ARM
Outdoors
IP 54
An outdoor 18 port switch with 16 Gigabit PoE-out ports and 2 SFP+. Power all your access points anywhere!...
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80924
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NULL
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0
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2026-04-25T15:27:00.899230+00:00
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/Users/lukas/.screenpipe/data/data/2026-04-25/1777 /Users/lukas/.screenpipe/data/data/2026-04-25/1777130820899_m2.jpg...
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Firefox
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MikroTik · Switches — Personal
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True
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mikrotik.com/products/group/switches
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monitor_2
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NULL
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NULL
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NULL
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NULL
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DXP4800PLUS-B5F8
Inbox (7) - [EMAIL] - Gmail
(56) DXP4800PLUS-B5F8
Inbox (7) - [EMAIL] - Gmail
(56) Inbox | [EMAIL] | Proton Mail
Welcome back
Welcome back
Western Digital Red Plus 3.5 6TB 5400rpm 256MB SATA3 (WD60EFPX) от 241,72 € (472,76 лв.) Вътрешен хард диск Western Digital - Pazaruvaj.com
Western Digital Red Plus 3.5 6TB 5400rpm 256MB SATA3 (WD60EFPX) от 241,72 € (472,76 лв.) Вътрешен хард диск Western Digital - Pazaruvaj.com
Today's Deals
Today's Deals
architecture - screenpipe docs
architecture - screenpipe docs
Claude Code works better when you stop treating it like a machine - [EMAIL] - Gmail
Claude Code works better when you stop treating it like a machine - [EMAIL] - Gmail
Screenpipe — Archive
Screenpipe — Archive
SQLite Web: archive.db
SQLite Web: archive.db
SQLite Web: db.sqlite
SQLite Web: db.sqlite
Claude Platform
Claude Platform
Hey @louis030195 Ill check during my - screenpipe.com
Hey @louis030195 Ill check during my - screenpipe.com
GitHub - screenpipe/screenpipe: Run agents that work for you based on what you do. AI finally knows what you are doing · GitHub
GitHub - screenpipe/screenpipe: Run agents that work for you based on what you do. AI finally knows what you are doing · GitHub
Gong Pricing in 2026: Costs, Plans & Is It Worth It?
Gong Pricing in 2026: Costs, Plans & Is It Worth It?
GLM 5.1 Thinks Strategically, Data-Center Revolt Intensifies, When Helpful LLMs Turn Unhelpful, Humanoid Robots Get to Work - [EMAIL] - Gmail
GLM 5.1 Thinks Strategically, Data-Center Revolt Intensifies, When Helpful LLMs Turn Unhelpful, Humanoid Robots Get to Work - [EMAIL] - Gmail
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Low-cost. Tough. And always ON! Compact PoE switch with built-in UPS and smart battery charger – because your CCTV cameras and access points deserve true off-the-grid resilience.
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A compact 1U 400G switch built for AI clusters, storage fabrics, and high-speed aggregation, featuring four 400G QSFP56-DD ports, dual 10 Gigabit Ethernet, and RouterOS v7. With hot-swap power supplies, robust cooling, and low power consumption, it delivers ultra-high bandwidth, wire-speed performance, and future-proof scalability at an accessible price point.
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Compact, powerful, and ready to simplify your 10 Gigabit network setups with 4x10G Ethernet ports ready to use out-of-the-box. No extra modules needed!
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Five-port desktop switch with one Gigabit Ethernet port and four SFP+ 10Gbps ports
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CRS312-4C+8XG-RM
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Switch of the future: the first MikroTik product with 10G RJ45 Ethernet ports and SFP+
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The first MikroTik high-power PoE++ switch – for easy and cost-effective powering of industry standard 802.3af/at/bt devices. Forget about countless power cables – create a cleaner space with PoE++!
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CRS317-1G-16S+RM
$499.00
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Smart Switch, 1 x Gigabit LAN, 16 x SFP+ cages, Dual Core 800MHz CPU, 1GB RAM, 1U rackmount passive cooling case, Dual Power Supplies
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CRS309-1G-8S+IN
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Desktop switch with one Gigabit Ethernet port and eight SFP+ 10Gbps ports
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A 100 Gigabit switch for enterprise networks and data centers. Hot-swappable parts and insane port density with 1.2 Tbps switching capacity!
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10 Gigabit fibre connectivity way over a 100 meters – for small offices or ISPs. Hardware offloaded VLAN-filtering and even some L3 routing on a budget!
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An outdoor 18 port switch with 15 reverse PoE ports and SFP. Cut costs, not speed – choose GPEN over GPON!
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ROS v7
A remarkable outdoor switch for setting up an optical 10G network that can even perform some light routing. The spiritual successor to the beloved FiberBox. Gigabit Ethernet, SFP/SFP+, PoE.
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CRS326-24G-2S+IN
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24 Gigabit ports, 2 SFP+ cages and a desktop case – server room power for your home!
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CRS326-24G-2S+RM
$209.00
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24 Gigabit port switch with 2 x SFP+ cages in 1U rackmount case, Dual boot (RouterOS or SwitchOS)
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CRS326-24S+2Q+RM
$599.00
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SFP/SFP+...
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DXP4800PLUS-B5F8
Inbox (7) - [EMAIL] - Gmail
(56) DXP4800PLUS-B5F8
Inbox (7) - [EMAIL] - Gmail
(56) Inbox | [EMAIL] | Proton Mail
Welcome back
Welcome back
Western Digital Red Plus 3.5 6TB 5400rpm 256MB SATA3 (WD60EFPX) от 241,72 € (472,76 лв.) Вътрешен хард диск Western Digital - Pazaruvaj.com
Western Digital Red Plus 3.5 6TB 5400rpm 256MB SATA3 (WD60EFPX) от 241,72 € (472,76 лв.) Вътрешен хард диск Western Digital - Pazaruvaj.com
Today's Deals
Today's Deals
architecture - screenpipe docs
architecture - screenpipe docs
Claude Code works better when you stop treating it like a machine - [EMAIL] - Gmail
Claude Code works better when you stop treating it like a machine - [EMAIL] - Gmail
Screenpipe — Archive
Screenpipe — Archive
SQLite Web: archive.db
SQLite Web: archive.db
SQLite Web: db.sqlite
SQLite Web: db.sqlite
Claude Platform
Claude Platform
Hey @louis030195 Ill check during my - screenpipe.com
Hey @louis030195 Ill check during my - screenpipe.com
GitHub - screenpipe/screenpipe: Run agents that work for you based on what you do. AI finally knows what you are doing · GitHub
GitHub - screenpipe/screenpipe: Run agents that work for you based on what you do. AI finally knows what you are doing · GitHub
Gong Pricing in 2026: Costs, Plans & Is It Worth It?
Gong Pricing in 2026: Costs, Plans & Is It Worth It?
GLM 5.1 Thinks Strategically, Data-Center Revolt Intensifies, When Helpful LLMs Turn Unhelpful, Humanoid Robots Get to Work - [EMAIL] - Gmail
GLM 5.1 Thinks Strategically, Data-Center Revolt Intensifies, When Helpful LLMs Turn Unhelpful, Humanoid Robots Get to Work - [EMAIL] - Gmail
Gitea Official Website
Gitea Official Website
lakylak/screenpipe - screenpipe - Gitea: Git with a cup of tea
lakylak/screenpipe - screenpipe - Gitea: Git with a cup of tea
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Product page for netPower Lite 8P
NEW
netPower Lite 8P
$199.00
*
SFP/SFP+
PoE
Outdoors
IP 54
Low-cost. Tough. And always ON! Compact PoE switch with built-in UPS and smart battery charger – because your CCTV cameras and access points deserve true off-the-grid resilience.
Product page for CRS804 DDQ
NEW
CRS804 DDQ
$1,295.00
*
400G
10G
ARM64
Quad-core CPU
ROS v7
A compact 1U 400G switch built for AI clusters, storage fabrics, and high-speed aggregation, featuring four 400G QSFP56-DD ports, dual 10 Gigabit Ethernet, and RouterOS v7. With hot-swap power supplies, robust cooling, and low power consumption, it delivers ultra-high bandwidth, wire-speed performance, and future-proof scalability at an accessible price point.
Product page for CRS304-4XG-IN
CRS304-4XG-IN
$199.00
*
10G
PoE
ARM64
ROS v7
Compact, powerful, and ready to simplify your 10 Gigabit network setups with 4x10G Ethernet ports ready to use out-of-the-box. No extra modules needed!
Product page for CRS305-1G-4S+IN
CRS305-1G-4S+IN
$149.00
*
SFP/SFP+
PoE
ARM
Five-port desktop switch with one Gigabit Ethernet port and four SFP+ 10Gbps ports
Product page for CRS312-4C+8XG-RM
CRS312-4C+8XG-RM
$699.00
*
10G
Combo ports
ROS v7
Switch of the future: the first MikroTik product with 10G RJ45 Ethernet ports and SFP+
Product page for CRS320-8P-8B-4S+RM
CRS320-8P-8B-4S+RM
$489.00
*
SFP/SFP+
PoE
ARM
ROS v7
The first MikroTik high-power PoE++ switch – for easy and cost-effective powering of industry standard 802.3af/at/bt devices. Forget about countless power cables – create a cleaner space with PoE++!
Product page for CRS317-1G-16S+RM
CRS317-1G-16S+RM
$499.00
*
SFP/SFP+
ARM
Smart Switch, 1 x Gigabit LAN, 16 x SFP+ cages, Dual Core 800MHz CPU, 1GB RAM, 1U rackmount passive cooling case, Dual Power Supplies
Product page for CRS309-1G-8S+IN
CRS309-1G-8S+IN
$269.00
*
SFP/SFP+
PoE
ARM
Desktop switch with one Gigabit Ethernet port and eight SFP+ 10Gbps ports
Product page for CRS518-16XS-2XQ-RM
CRS518-16XS-2XQ-RM
$1,595.00
*
100G
ROS v7
A 100 Gigabit switch for enterprise networks and data centers. Hot-swappable parts and insane port density with 1.2 Tbps switching capacity!
Product page for CRS310-1G-5S-4S+IN
CRS310-1G-5S-4S+IN
$199.00
*
SFP/SFP+
PoE
ARM
ROS v7
10 Gigabit fibre connectivity way over a 100 meters – for small offices or ISPs. Hardware offloaded VLAN-filtering and even some L3 routing on a budget!
Product page for CRS310-8G+2S+IN
CRS310-8G+2S+IN
$219.00
*
SFP/SFP+
2.5G
ARM
ROS v7
Take advantage of the blazing fast 2.5/10 Gigabit combo and upgrade your workspace! This switch can utilize the full potential of RouterOS v7: run VLANs, Jumbo frames, link aggregation, ACL rules, and so much more!
Product page for netPower 16P
netPower 16P
$279.00
*
SFP/SFP+
PoE
ARM
Outdoors
IP 54
An outdoor 18 port switch with 16 Gigabit PoE-out ports and 2 SFP+. Power all your access points anywhere!
Product page for netPower 15FR
netPower 15FR
$169.00
*
SFP/SFP+
PoE
ARM
Outdoors
IP 54
An outdoor 18 port switch with 15 reverse PoE ports and SFP. Cut costs, not speed – choose GPEN over GPON!
Product page for netFiber 9
netFiber 9
$249.00
*
SFP/SFP+
PoE
ARM
Outdoors
IP 54
ROS v7
A remarkable outdoor switch for setting up an optical 10G network that can even perform some light routing. The spiritual successor to the beloved FiberBox. Gigabit Ethernet, SFP/SFP+, PoE.
Product page for CRS326-24G-2S+IN
CRS326-24G-2S+IN
$199.00
*
SFP/SFP+
PoE
ARM
24 Gigabit ports, 2 SFP+ cages and a desktop case – server room power for your home!
Product page for CRS326-24G-2S+RM
CRS326-24G-2S+RM
$209.00
*
SFP/SFP+
PoE
ARM
24 Gigabit port switch with 2 x SFP+ cages in 1U rackmount case, Dual boot (RouterOS or SwitchOS)
Product page for CRS326-24S+2Q+RM
CRS326-24S+2Q+RM
$599.00
*
SFP/SFP+...
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80925
|
2149
|
0
|
2026-04-25T15:36:10.203746+00:00
|
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Firefox
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MikroTik · Switches — Personal
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True
|
mikrotik.com/products/group/switches
|
monitor_2
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NULL
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NULL
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Product page for CRS804 DDQ
DXP4800PLUS-B5F8
Inbox Product page for CRS804 DDQ
DXP4800PLUS-B5F8
Inbox (7) - [EMAIL] - Gmail
(56) Inbox | [EMAIL] | Proton Mail
Welcome back
Welcome back
Western Digital Red Plus 3.5 6TB 5400rpm 256MB SATA3 (WD60EFPX) от 241,72 € (472,76 лв.) Вътрешен хард диск Western Digital - Pazaruvaj.com
Western Digital Red Plus 3.5 6TB 5400rpm 256MB SATA3 (WD60EFPX) от 241,72 € (472,76 лв.) Вътрешен хард диск Western Digital - Pazaruvaj.com
Today's Deals
Today's Deals
architecture - screenpipe docs
architecture - screenpipe docs
Claude Code works better when you stop treating it like a machine - [EMAIL] - Gmail
Claude Code works better when you stop treating it like a machine - [EMAIL] - Gmail
Screenpipe — Archive
Screenpipe — Archive
SQLite Web: archive.db
SQLite Web: archive.db
SQLite Web: db.sqlite
SQLite Web: db.sqlite
Claude Platform
Claude Platform
Hey @louis030195 Ill check during my - screenpipe.com
Hey @louis030195 Ill check during my - screenpipe.com
GitHub - screenpipe/screenpipe: Run agents that work for you based on what you do. AI finally knows what you are doing · GitHub
GitHub - screenpipe/screenpipe: Run agents that work for you based on what you do. AI finally knows what you are doing · GitHub
Gong Pricing in 2026: Costs, Plans & Is It Worth It?
Gong Pricing in 2026: Costs, Plans & Is It Worth It?
GLM 5.1 Thinks Strategically, Data-Center Revolt Intensifies, When Helpful LLMs Turn Unhelpful, Humanoid Robots Get to Work - [EMAIL] - Gmail
GLM 5.1 Thinks Strategically, Data-Center Revolt Intensifies, When Helpful LLMs Turn Unhelpful, Humanoid Robots Get to Work - [EMAIL] - Gmail
Gitea Official Website
Gitea Official Website
lakylak/screenpipe - screenpipe - Gitea: Git with a cup of tea
lakylak/screenpipe - screenpipe - Gitea: Git with a cup of tea
New Tab
New Tab
MikroTik · Switches
MikroTik · Switches
Close tab
New Tab
Customize sidebar
Open Le Chat Mistral (⌃X)
Open history (⇧⌘H)
Open bookmarks (⌘B)
Bitwarden
Skip to main content
Skip to main content
Go to home page
HOME
HOME
HARDWARE
HARDWARE
SWITCHES
SWITCHES
Status
Status
Wired Interfaces
Wired Interfaces
Options Range
Options Range
Features
Features
Operating System
Operating System
Architecture
Architecture
Product page for netPower Lite 8P
NEW
netPower Lite 8P
$199.00
*
SFP/SFP+
PoE
Outdoors
IP 54
Low-cost. Tough. And always ON! Compact PoE switch with built-in UPS and smart battery charger – because your CCTV cameras and access points deserve true off-the-grid resilience.
Product page for CRS804 DDQ
NEW
CRS804 DDQ
$1,295.00
*
400G
10G
ARM64
Quad-core CPU
ROS v7
A compact 1U 400G switch built for AI clusters, storage fabrics, and high-speed aggregation, featuring four 400G QSFP56-DD ports, dual 10 Gigabit Ethernet, and RouterOS v7. With hot-swap power supplies, robust cooling, and low power consumption, it delivers ultra-high bandwidth, wire-speed performance, and future-proof scalability at an accessible price point.
Product page for CRS304-4XG-IN
CRS304-4XG-IN
$199.00
*
10G
PoE
ARM64
ROS v7
Compact, powerful, and ready to simplify your 10 Gigabit network setups with 4x10G Ethernet ports ready to use out-of-the-box. No extra modules needed!
Product page for CRS305-1G-4S+IN
CRS305-1G-4S+IN
$149.00
*
SFP/SFP+
PoE
ARM
Five-port desktop switch with one Gigabit Ethernet port and four SFP+ 10Gbps ports
Product page for CRS312-4C+8XG-RM
CRS312-4C+8XG-RM
$699.00
*
10G
Combo ports
ROS v7
Switch of the future: the first MikroTik product with 10G RJ45 Ethernet ports and SFP+
Product page for CRS320-8P-8B-4S+RM
CRS320-8P-8B-4S+RM
$489.00
*
SFP/SFP+
PoE
ARM
ROS v7
The first MikroTik high-power PoE++ switch – for easy and cost-effective powering of industry standard 802.3af/at/bt devices. Forget about countless power cables – create a cleaner space with PoE++!
Product page for CRS317-1G-16S+RM
CRS317-1G-16S+RM
$499.00
*
SFP/SFP+
ARM
Smart Switch, 1 x Gigabit LAN, 16 x SFP+ cages, Dual Core 800MHz CPU, 1GB RAM, 1U rackmount passive cooling case, Dual Power Supplies
Product page for CRS309-1G-8S+IN
CRS309-1G-8S+IN
$269.00
*
SFP/SFP+
PoE
ARM
Desktop switch with one Gigabit Ethernet port and eight SFP+ 10Gbps ports
Product page for CRS518-16XS-2XQ-RM
CRS518-16XS-2XQ-RM
$1,595.00
*
100G
ROS v7
A 100 Gigabit switch for enterprise networks and data centers. Hot-swappable parts and insane port density with 1.2 Tbps switching capacity!
Product page for CRS310-1G-5S-4S+IN
CRS310-1G-5S-4S+IN
$199.00
*
SFP/SFP+
PoE
ARM
ROS v7
10 Gigabit fibre connectivity way over a 100 meters – for small offices or ISPs. Hardware offloaded VLAN-filtering and even some L3 routing on a budget!
Product page for CRS310-8G+2S+IN
CRS310-8G+2S+IN
$219.00
*
SFP/SFP+
2.5G
ARM
ROS v7
Take advantage of the blazing fast 2.5/10 Gigabit combo and upgrade your workspace! This switch can utilize the full potential of RouterOS v7: run VLANs, Jumbo frames, link aggregation, ACL rules, and so much more!
Product page for netPower 16P
netPower 16P
$279.00
*
SFP/SFP+
PoE
ARM
Outdoors
IP 54
An outdoor 18 port switch with 16 Gigabit PoE-out ports and 2 SFP+. Power all your access points anywhere!
Product page for netPower 15FR
netPower 15FR
$169.00
*
SFP/SFP+
PoE
ARM
Outdoors
IP 54
An outdoor 18 port switch with 15 reverse PoE ports and SFP. Cut costs, not speed – choose GPEN over GPON!
Product page for netFiber 9
netFiber 9
$249.00
*
SFP/SFP+
PoE
ARM
Outdoors
IP 54
ROS v7
A remarkable outdoor switch for setting up an optical 10G network that can even perform some light routing. The spiritual successor to the beloved FiberBox. Gigabit Ethernet, SFP/SFP+, PoE.
Product page for CRS326-24G-2S+IN
CRS326-24G-2S+IN
$199.00
*
SFP/SFP+
PoE
ARM
24 Gigabit ports, 2 SFP+ cages and a desktop case – server room power for your home!...
|
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-4271956811115627647
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visual_change
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accessibility
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NULL
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Product page for CRS804 DDQ
DXP4800PLUS-B5F8
Inbox Product page for CRS804 DDQ
DXP4800PLUS-B5F8
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Western Digital Red Plus 3.5 6TB 5400rpm 256MB SATA3 (WD60EFPX) от 241,72 € (472,76 лв.) Вътрешен хард диск Western Digital - Pazaruvaj.com
Western Digital Red Plus 3.5 6TB 5400rpm 256MB SATA3 (WD60EFPX) от 241,72 € (472,76 лв.) Вътрешен хард диск Western Digital - Pazaruvaj.com
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Claude Code works better when you stop treating it like a machine - [EMAIL] - Gmail
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SQLite Web: archive.db
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Claude Platform
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Hey @louis030195 Ill check during my - screenpipe.com
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GitHub - screenpipe/screenpipe: Run agents that work for you based on what you do. AI finally knows what you are doing · GitHub
GitHub - screenpipe/screenpipe: Run agents that work for you based on what you do. AI finally knows what you are doing · GitHub
Gong Pricing in 2026: Costs, Plans & Is It Worth It?
Gong Pricing in 2026: Costs, Plans & Is It Worth It?
GLM 5.1 Thinks Strategically, Data-Center Revolt Intensifies, When Helpful LLMs Turn Unhelpful, Humanoid Robots Get to Work - [EMAIL] - Gmail
GLM 5.1 Thinks Strategically, Data-Center Revolt Intensifies, When Helpful LLMs Turn Unhelpful, Humanoid Robots Get to Work - [EMAIL] - Gmail
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Product page for netPower Lite 8P
NEW
netPower Lite 8P
$199.00
*
SFP/SFP+
PoE
Outdoors
IP 54
Low-cost. Tough. And always ON! Compact PoE switch with built-in UPS and smart battery charger – because your CCTV cameras and access points deserve true off-the-grid resilience.
Product page for CRS804 DDQ
NEW
CRS804 DDQ
$1,295.00
*
400G
10G
ARM64
Quad-core CPU
ROS v7
A compact 1U 400G switch built for AI clusters, storage fabrics, and high-speed aggregation, featuring four 400G QSFP56-DD ports, dual 10 Gigabit Ethernet, and RouterOS v7. With hot-swap power supplies, robust cooling, and low power consumption, it delivers ultra-high bandwidth, wire-speed performance, and future-proof scalability at an accessible price point.
Product page for CRS304-4XG-IN
CRS304-4XG-IN
$199.00
*
10G
PoE
ARM64
ROS v7
Compact, powerful, and ready to simplify your 10 Gigabit network setups with 4x10G Ethernet ports ready to use out-of-the-box. No extra modules needed!
Product page for CRS305-1G-4S+IN
CRS305-1G-4S+IN
$149.00
*
SFP/SFP+
PoE
ARM
Five-port desktop switch with one Gigabit Ethernet port and four SFP+ 10Gbps ports
Product page for CRS312-4C+8XG-RM
CRS312-4C+8XG-RM
$699.00
*
10G
Combo ports
ROS v7
Switch of the future: the first MikroTik product with 10G RJ45 Ethernet ports and SFP+
Product page for CRS320-8P-8B-4S+RM
CRS320-8P-8B-4S+RM
$489.00
*
SFP/SFP+
PoE
ARM
ROS v7
The first MikroTik high-power PoE++ switch – for easy and cost-effective powering of industry standard 802.3af/at/bt devices. Forget about countless power cables – create a cleaner space with PoE++!
Product page for CRS317-1G-16S+RM
CRS317-1G-16S+RM
$499.00
*
SFP/SFP+
ARM
Smart Switch, 1 x Gigabit LAN, 16 x SFP+ cages, Dual Core 800MHz CPU, 1GB RAM, 1U rackmount passive cooling case, Dual Power Supplies
Product page for CRS309-1G-8S+IN
CRS309-1G-8S+IN
$269.00
*
SFP/SFP+
PoE
ARM
Desktop switch with one Gigabit Ethernet port and eight SFP+ 10Gbps ports
Product page for CRS518-16XS-2XQ-RM
CRS518-16XS-2XQ-RM
$1,595.00
*
100G
ROS v7
A 100 Gigabit switch for enterprise networks and data centers. Hot-swappable parts and insane port density with 1.2 Tbps switching capacity!
Product page for CRS310-1G-5S-4S+IN
CRS310-1G-5S-4S+IN
$199.00
*
SFP/SFP+
PoE
ARM
ROS v7
10 Gigabit fibre connectivity way over a 100 meters – for small offices or ISPs. Hardware offloaded VLAN-filtering and even some L3 routing on a budget!
Product page for CRS310-8G+2S+IN
CRS310-8G+2S+IN
$219.00
*
SFP/SFP+
2.5G
ARM
ROS v7
Take advantage of the blazing fast 2.5/10 Gigabit combo and upgrade your workspace! This switch can utilize the full potential of RouterOS v7: run VLANs, Jumbo frames, link aggregation, ACL rules, and so much more!
Product page for netPower 16P
netPower 16P
$279.00
*
SFP/SFP+
PoE
ARM
Outdoors
IP 54
An outdoor 18 port switch with 16 Gigabit PoE-out ports and 2 SFP+. Power all your access points anywhere!
Product page for netPower 15FR
netPower 15FR
$169.00
*
SFP/SFP+
PoE
ARM
Outdoors
IP 54
An outdoor 18 port switch with 15 reverse PoE ports and SFP. Cut costs, not speed – choose GPEN over GPON!
Product page for netFiber 9
netFiber 9
$249.00
*
SFP/SFP+
PoE
ARM
Outdoors
IP 54
ROS v7
A remarkable outdoor switch for setting up an optical 10G network that can even perform some light routing. The spiritual successor to the beloved FiberBox. Gigabit Ethernet, SFP/SFP+, PoE.
Product page for CRS326-24G-2S+IN
CRS326-24G-2S+IN
$199.00
*
SFP/SFP+
PoE
ARM
24 Gigabit ports, 2 SFP+ cages and a desktop case – server room power for your home!...
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2026-04-25T15:36:25.322954+00:00
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Firefox
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MikroTik · Switches — Personal
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mikrotik.com/products/group/switches
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DXP4800PLUS-B5F8
Inbox (7) - [EMAIL] - Gmail
(56) DXP4800PLUS-B5F8
Inbox (7) - [EMAIL] - Gmail
(56) Inbox | [EMAIL] | Proton Mail
Welcome back
Welcome back
Western Digital Red Plus 3.5 6TB 5400rpm 256MB SATA3 (WD60EFPX) от 241,72 € (472,76 лв.) Вътрешен хард диск Western Digital - Pazaruvaj.com
Western Digital Red Plus 3.5 6TB 5400rpm 256MB SATA3 (WD60EFPX) от 241,72 € (472,76 лв.) Вътрешен хард диск Western Digital - Pazaruvaj.com
Today's Deals
Today's Deals
architecture - screenpipe docs
architecture - screenpipe docs
Claude Code works better when you stop treating it like a machine - [EMAIL] - Gmail
Claude Code works better when you stop treating it like a machine - [EMAIL] - Gmail
Screenpipe — Archive
Screenpipe — Archive
SQLite Web: archive.db
SQLite Web: archive.db
SQLite Web: db.sqlite
SQLite Web: db.sqlite
Claude Platform
Claude Platform
Hey @louis030195 Ill check during my - screenpipe.com
Hey @louis030195 Ill check during my - screenpipe.com
GitHub - screenpipe/screenpipe: Run agents that work for you based on what you do. AI finally knows what you are doing · GitHub
GitHub - screenpipe/screenpipe: Run agents that work for you based on what you do. AI finally knows what you are doing · GitHub
Gong Pricing in 2026: Costs, Plans & Is It Worth It?
Gong Pricing in 2026: Costs, Plans & Is It Worth It?
GLM 5.1 Thinks Strategically, Data-Center Revolt Intensifies, When Helpful LLMs Turn Unhelpful, Humanoid Robots Get to Work - [EMAIL] - Gmail
GLM 5.1 Thinks Strategically, Data-Center Revolt Intensifies, When Helpful LLMs Turn Unhelpful, Humanoid Robots Get to Work - [EMAIL] - Gmail
Gitea Official Website
Gitea Official Website
lakylak/screenpipe - screenpipe - Gitea: Git with a cup of tea
lakylak/screenpipe - screenpipe - Gitea: Git with a cup of tea
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MikroTik · Switches
MikroTik · Switches
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Product page for netPower Lite 8P
NEW
netPower Lite 8P
$199.00
*
SFP/SFP+
PoE
Outdoors
IP 54
Low-cost. Tough. And always ON! Compact PoE switch with built-in UPS and smart battery charger – because your CCTV cameras and access points deserve true off-the-grid resilience.
Product page for CRS804 DDQ
NEW
CRS804 DDQ
$1,295.00
*
400G
10G
ARM64
Quad-core CPU
ROS v7
A compact 1U 400G switch built for AI clusters, storage fabrics, and high-speed aggregation, featuring four 400G QSFP56-DD ports, dual 10 Gigabit Ethernet, and RouterOS v7. With hot-swap power supplies, robust cooling, and low power consumption, it delivers ultra-high bandwidth, wire-speed performance, and future-proof scalability at an accessible price point.
Product page for CRS304-4XG-IN
CRS304-4XG-IN
$199.00
*
10G
PoE
ARM64
ROS v7
Compact, powerful, and ready to simplify your 10 Gigabit network setups with 4x10G Ethernet ports ready to use out-of-the-box. No extra modules needed!
Product page for CRS305-1G-4S+IN
CRS305-1G-4S+IN
$149.00
*
SFP/SFP+
PoE
ARM
Five-port desktop switch with one Gigabit Ethernet port and four SFP+ 10Gbps ports
Product page for CRS312-4C+8XG-RM
CRS312-4C+8XG-RM
$699.00
*
10G
Combo ports
ROS v7
Switch of the future: the first MikroTik product with 10G RJ45 Ethernet ports and SFP+
Product page for CRS320-8P-8B-4S+RM
CRS320-8P-8B-4S+RM
$489.00
*
SFP/SFP+
PoE
ARM
ROS v7
The first MikroTik high-power PoE++ switch – for easy and cost-effective powering of industry standard 802.3af/at/bt devices. Forget about countless power cables – create a cleaner space with PoE++!
Product page for CRS317-1G-16S+RM
CRS317-1G-16S+RM
$499.00
*
SFP/SFP+
ARM
Smart Switch, 1 x Gigabit LAN, 16 x SFP+ cages, Dual Core 800MHz CPU, 1GB RAM, 1U rackmount passive cooling case, Dual Power Supplies
Product page for CRS309-1G-8S+IN
CRS309-1G-8S+IN
$269.00
*
SFP/SFP+
PoE
ARM
Desktop switch with one Gigabit Ethernet port and eight SFP+ 10Gbps ports
Product page for CRS518-16XS-2XQ-RM
CRS518-16XS-2XQ-RM
$1,595.00
*
100G
ROS v7
A 100 Gigabit switch for enterprise networks and data centers. Hot-swappable parts and insane port density with 1.2 Tbps switching capacity!
Product page for CRS310-1G-5S-4S+IN
CRS310-1G-5S-4S+IN
$199.00
*
SFP/SFP+
PoE
ARM
ROS v7
10 Gigabit fibre connectivity way over a 100 meters – for small offices or ISPs. Hardware offloaded VLAN-filtering and even some L3 routing on a budget!
Product page for CRS310-8G+2S+IN
CRS310-8G+2S+IN
$219.00
*
SFP/SFP+
2.5G
ARM
ROS v7
Take advantage of the blazing fast 2.5/10 Gigabit combo and upgrade your workspace! This switch can utilize the full potential of RouterOS v7: run VLANs, Jumbo frames, link aggregation, ACL rules, and so much more!
Product page for netPower 16P
netPower 16P
$279.00
*
SFP/SFP+
PoE
ARM
Outdoors
IP 54
An outdoor 18 port switch with 16 Gigabit PoE-out ports and 2 SFP+. Power all your access points anywhere!
Product page for netPower 15FR
netPower 15FR
$169.00
*
SFP/SFP+
PoE
ARM
Outdoors
IP 54
An outdoor 18 port switch with 15 reverse PoE ports and SFP. Cut costs, not speed – choose GPEN over GPON!
Product page for netFiber 9
netFiber 9
$249.00
*
SFP/SFP+
PoE
ARM
Outdoors
IP 54
ROS v7
A remarkable outdoor switch for setting up an optical 10G network that can even perform some light routing. The spiritual successor to the beloved FiberBox. Gigabit Ethernet, SFP/SFP+, PoE.
Product page for CRS326-24G-2S+IN
CRS326-24G-2S+IN
$199.00
*
SFP/SFP+
PoE
ARM
24 Gigabit ports, 2 SFP+ cages and a desktop case – server room power for your home!
Product page for CRS326-24G-2S+RM
CRS326-24G-2S+RM
$209.00
*
SFP/SFP+
PoE
ARM
24 Gigabit port switch with 2 x SFP+ cages in 1U rackmount case, Dual boot (RouterOS or SwitchOS)
Product page for CRS326-24S+2Q+RM
CRS326-24S+2Q+RM
$599.00
*...
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8167717031046980451
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visual_change
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accessibility
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NULL
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DXP4800PLUS-B5F8
Inbox (7) - [EMAIL] - Gmail
(56) DXP4800PLUS-B5F8
Inbox (7) - [EMAIL] - Gmail
(56) Inbox | [EMAIL] | Proton Mail
Welcome back
Welcome back
Western Digital Red Plus 3.5 6TB 5400rpm 256MB SATA3 (WD60EFPX) от 241,72 € (472,76 лв.) Вътрешен хард диск Western Digital - Pazaruvaj.com
Western Digital Red Plus 3.5 6TB 5400rpm 256MB SATA3 (WD60EFPX) от 241,72 € (472,76 лв.) Вътрешен хард диск Western Digital - Pazaruvaj.com
Today's Deals
Today's Deals
architecture - screenpipe docs
architecture - screenpipe docs
Claude Code works better when you stop treating it like a machine - [EMAIL] - Gmail
Claude Code works better when you stop treating it like a machine - [EMAIL] - Gmail
Screenpipe — Archive
Screenpipe — Archive
SQLite Web: archive.db
SQLite Web: archive.db
SQLite Web: db.sqlite
SQLite Web: db.sqlite
Claude Platform
Claude Platform
Hey @louis030195 Ill check during my - screenpipe.com
Hey @louis030195 Ill check during my - screenpipe.com
GitHub - screenpipe/screenpipe: Run agents that work for you based on what you do. AI finally knows what you are doing · GitHub
GitHub - screenpipe/screenpipe: Run agents that work for you based on what you do. AI finally knows what you are doing · GitHub
Gong Pricing in 2026: Costs, Plans & Is It Worth It?
Gong Pricing in 2026: Costs, Plans & Is It Worth It?
GLM 5.1 Thinks Strategically, Data-Center Revolt Intensifies, When Helpful LLMs Turn Unhelpful, Humanoid Robots Get to Work - [EMAIL] - Gmail
GLM 5.1 Thinks Strategically, Data-Center Revolt Intensifies, When Helpful LLMs Turn Unhelpful, Humanoid Robots Get to Work - [EMAIL] - Gmail
Gitea Official Website
Gitea Official Website
lakylak/screenpipe - screenpipe - Gitea: Git with a cup of tea
lakylak/screenpipe - screenpipe - Gitea: Git with a cup of tea
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Product page for netPower Lite 8P
NEW
netPower Lite 8P
$199.00
*
SFP/SFP+
PoE
Outdoors
IP 54
Low-cost. Tough. And always ON! Compact PoE switch with built-in UPS and smart battery charger – because your CCTV cameras and access points deserve true off-the-grid resilience.
Product page for CRS804 DDQ
NEW
CRS804 DDQ
$1,295.00
*
400G
10G
ARM64
Quad-core CPU
ROS v7
A compact 1U 400G switch built for AI clusters, storage fabrics, and high-speed aggregation, featuring four 400G QSFP56-DD ports, dual 10 Gigabit Ethernet, and RouterOS v7. With hot-swap power supplies, robust cooling, and low power consumption, it delivers ultra-high bandwidth, wire-speed performance, and future-proof scalability at an accessible price point.
Product page for CRS304-4XG-IN
CRS304-4XG-IN
$199.00
*
10G
PoE
ARM64
ROS v7
Compact, powerful, and ready to simplify your 10 Gigabit network setups with 4x10G Ethernet ports ready to use out-of-the-box. No extra modules needed!
Product page for CRS305-1G-4S+IN
CRS305-1G-4S+IN
$149.00
*
SFP/SFP+
PoE
ARM
Five-port desktop switch with one Gigabit Ethernet port and four SFP+ 10Gbps ports
Product page for CRS312-4C+8XG-RM
CRS312-4C+8XG-RM
$699.00
*
10G
Combo ports
ROS v7
Switch of the future: the first MikroTik product with 10G RJ45 Ethernet ports and SFP+
Product page for CRS320-8P-8B-4S+RM
CRS320-8P-8B-4S+RM
$489.00
*
SFP/SFP+
PoE
ARM
ROS v7
The first MikroTik high-power PoE++ switch – for easy and cost-effective powering of industry standard 802.3af/at/bt devices. Forget about countless power cables – create a cleaner space with PoE++!
Product page for CRS317-1G-16S+RM
CRS317-1G-16S+RM
$499.00
*
SFP/SFP+
ARM
Smart Switch, 1 x Gigabit LAN, 16 x SFP+ cages, Dual Core 800MHz CPU, 1GB RAM, 1U rackmount passive cooling case, Dual Power Supplies
Product page for CRS309-1G-8S+IN
CRS309-1G-8S+IN
$269.00
*
SFP/SFP+
PoE
ARM
Desktop switch with one Gigabit Ethernet port and eight SFP+ 10Gbps ports
Product page for CRS518-16XS-2XQ-RM
CRS518-16XS-2XQ-RM
$1,595.00
*
100G
ROS v7
A 100 Gigabit switch for enterprise networks and data centers. Hot-swappable parts and insane port density with 1.2 Tbps switching capacity!
Product page for CRS310-1G-5S-4S+IN
CRS310-1G-5S-4S+IN
$199.00
*
SFP/SFP+
PoE
ARM
ROS v7
10 Gigabit fibre connectivity way over a 100 meters – for small offices or ISPs. Hardware offloaded VLAN-filtering and even some L3 routing on a budget!
Product page for CRS310-8G+2S+IN
CRS310-8G+2S+IN
$219.00
*
SFP/SFP+
2.5G
ARM
ROS v7
Take advantage of the blazing fast 2.5/10 Gigabit combo and upgrade your workspace! This switch can utilize the full potential of RouterOS v7: run VLANs, Jumbo frames, link aggregation, ACL rules, and so much more!
Product page for netPower 16P
netPower 16P
$279.00
*
SFP/SFP+
PoE
ARM
Outdoors
IP 54
An outdoor 18 port switch with 16 Gigabit PoE-out ports and 2 SFP+. Power all your access points anywhere!
Product page for netPower 15FR
netPower 15FR
$169.00
*
SFP/SFP+
PoE
ARM
Outdoors
IP 54
An outdoor 18 port switch with 15 reverse PoE ports and SFP. Cut costs, not speed – choose GPEN over GPON!
Product page for netFiber 9
netFiber 9
$249.00
*
SFP/SFP+
PoE
ARM
Outdoors
IP 54
ROS v7
A remarkable outdoor switch for setting up an optical 10G network that can even perform some light routing. The spiritual successor to the beloved FiberBox. Gigabit Ethernet, SFP/SFP+, PoE.
Product page for CRS326-24G-2S+IN
CRS326-24G-2S+IN
$199.00
*
SFP/SFP+
PoE
ARM
24 Gigabit ports, 2 SFP+ cages and a desktop case – server room power for your home!
Product page for CRS326-24G-2S+RM
CRS326-24G-2S+RM
$209.00
*
SFP/SFP+
PoE
ARM
24 Gigabit port switch with 2 x SFP+ cages in 1U rackmount case, Dual boot (RouterOS or SwitchOS)
Product page for CRS326-24S+2Q+RM
CRS326-24S+2Q+RM
$599.00
*...
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80927
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2148
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0
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2026-04-25T15:36:35.913551+00:00
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/Users/lukas/.screenpipe/data/data/2026-04-25/1777 /Users/lukas/.screenpipe/data/data/2026-04-25/1777131395913_m1.jpg...
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Firefox
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MikroTik · Switches — Personal
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True
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mikrotik.com/products/group/switches
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monitor_1
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NULL
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NULL
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NULL
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NULL
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Product page for CRS310-8G+2S+IN
DXP4800PLUS-B5F8
Product page for CRS310-8G+2S+IN
DXP4800PLUS-B5F8
Inbox (7) - [EMAIL] - Gmail
(56) Inbox | [EMAIL] | Proton Mail
Welcome back
Welcome back
Western Digital Red Plus 3.5 6TB 5400rpm 256MB SATA3 (WD60EFPX) от 241,72 € (472,76 лв.) Вътрешен хард диск Western Digital - Pazaruvaj.com
Western Digital Red Plus 3.5 6TB 5400rpm 256MB SATA3 (WD60EFPX) от 241,72 € (472,76 лв.) Вътрешен хард диск Western Digital - Pazaruvaj.com
Today's Deals
Today's Deals
architecture - screenpipe docs
architecture - screenpipe docs
Claude Code works better when you stop treating it like a machine - [EMAIL] - Gmail
Claude Code works better when you stop treating it like a machine - [EMAIL] - Gmail
Screenpipe — Archive
Screenpipe — Archive
SQLite Web: archive.db
SQLite Web: archive.db
SQLite Web: db.sqlite
SQLite Web: db.sqlite
Claude Platform
Claude Platform
Hey @louis030195 Ill check during my - screenpipe.com
Hey @louis030195 Ill check during my - screenpipe.com
GitHub - screenpipe/screenpipe: Run agents that work for you based on what you do. AI finally knows what you are doing · GitHub
GitHub - screenpipe/screenpipe: Run agents that work for you based on what you do. AI finally knows what you are doing · GitHub
Gong Pricing in 2026: Costs, Plans & Is It Worth It?
Gong Pricing in 2026: Costs, Plans & Is It Worth It?
GLM 5.1 Thinks Strategically, Data-Center Revolt Intensifies, When Helpful LLMs Turn Unhelpful, Humanoid Robots Get to Work - [EMAIL] - Gmail
GLM 5.1 Thinks Strategically, Data-Center Revolt Intensifies, When Helpful LLMs Turn Unhelpful, Humanoid Robots Get to Work - [EMAIL] - Gmail
Gitea Official Website
Gitea Official Website
lakylak/screenpipe - screenpipe - Gitea: Git with a cup of tea
lakylak/screenpipe - screenpipe - Gitea: Git with a cup of tea
New Tab
New Tab
MikroTik · Switches
MikroTik · Switches
Close tab
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Customize sidebar
Open Le Chat Mistral (⌃X)
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HOME
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Status
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Operating System
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Architecture
Product page for netPower Lite 8P
NEW
netPower Lite 8P
$199.00
*
SFP/SFP+
PoE
Outdoors
IP 54
Low-cost. Tough. And always ON! Compact PoE switch with built-in UPS and smart battery charger – because your CCTV cameras and access points deserve true off-the-grid resilience.
Product page for CRS804 DDQ
NEW
CRS804 DDQ
$1,295.00
*
400G
10G
ARM64
Quad-core CPU
ROS v7
A compact 1U 400G switch built for AI clusters, storage fabrics, and high-speed aggregation, featuring four 400G QSFP56-DD ports, dual 10 Gigabit Ethernet, and RouterOS v7. With hot-swap power supplies, robust cooling, and low power consumption, it delivers ultra-high bandwidth, wire-speed performance, and future-proof scalability at an accessible price point.
Product page for CRS304-4XG-IN
CRS304-4XG-IN
$199.00
*
10G
PoE
ARM64
ROS v7
Compact, powerful, and ready to simplify your 10 Gigabit network setups with 4x10G Ethernet ports ready to use out-of-the-box. No extra modules needed!
Product page for CRS305-1G-4S+IN
CRS305-1G-4S+IN
$149.00
*
SFP/SFP+
PoE
ARM
Five-port desktop switch with one Gigabit Ethernet port and four SFP+ 10Gbps ports
Product page for CRS312-4C+8XG-RM
CRS312-4C+8XG-RM
$699.00
*
10G
Combo ports
ROS v7
Switch of the future: the first MikroTik product with 10G RJ45 Ethernet ports and SFP+
Product page for CRS320-8P-8B-4S+RM
CRS320-8P-8B-4S+RM
$489.00
*
SFP/SFP+
PoE
ARM
ROS v7
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Product page for CRS317-1G-16S+RM
CRS317-1G-16S+RM
$499.00
*
SFP/SFP+
ARM
Smart Switch, 1 x Gigabit LAN, 16 x SFP+ cages, Dual Core 800MHz CPU, 1GB RAM, 1U rackmount passive cooling case, Dual Power Supplies
Product page for CRS309-1G-8S+IN
CRS309-1G-8S+IN
$269.00
*
SFP/SFP+
PoE
ARM
Desktop switch with one Gigabit Ethernet port and eight SFP+ 10Gbps ports
Product page for CRS518-16XS-2XQ-RM
CRS518-16XS-2XQ-RM
$1,595.00
*
100G
ROS v7
A 100 Gigabit switch for enterprise networks and data centers. Hot-swappable parts and insane port density with 1.2 Tbps switching capacity!
Product page for CRS310-1G-5S-4S+IN
CRS310-1G-5S-4S+IN
$199.00
*
SFP/SFP+
PoE
ARM
ROS v7
10 Gigabit fibre connectivity way over a 100 meters – for small offices or ISPs. Hardware offloaded VLAN-filtering and even some L3 routing on a budget!
Product page for CRS310-8G+2S+IN
CRS310-8G+2S+IN
$219.00
*
SFP/SFP+
2.5G
ARM
ROS v7
Take advantage of the blazing fast 2.5/10 Gigabit combo and upgrade your workspace! This switch can utilize the full potential of RouterOS v7: run VLANs, Jumbo frames, link aggregation, ACL rules, and so much more!
Product page for netPower 16P
netPower 16P
$279.00
*
SFP/SFP+
PoE
ARM
Outdoors
IP 54
An outdoor 18 port switch with 16 Gigabit PoE-out ports and 2 SFP+. Power all your access points anywhere!
Product page for netPower 15FR
netPower 15FR
$169.00
*
SFP/SFP+
PoE
ARM
Outdoors
IP 54
An outdoor 18 port switch with 15 reverse PoE ports and SFP. Cut costs, not speed – choose GPEN over GPON!
Product page for netFiber 9
netFiber 9
$249.00
*
SFP/SFP+
PoE
ARM
Outdoors
IP 54
ROS v7
A remarkable outdoor switch for setting up an optical 10G network that can even perform some light routing. The spiritual successor to the beloved FiberBox. Gigabit Ethernet, SFP/SFP+, PoE.
Product page for CRS326-24G-2S+IN
CRS326-24G-2S+IN
$199.00
*
SFP/SFP+
PoE
ARM
24 Gigabit ports, 2 SFP+ cages and a desktop case – server room power for your home!
Product page for CRS326-24G-2S+RM...
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8373258547681612659
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-4271956819705562239
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idle
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accessibility
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NULL
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Product page for CRS310-8G+2S+IN
DXP4800PLUS-B5F8
Product page for CRS310-8G+2S+IN
DXP4800PLUS-B5F8
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Welcome back
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Western Digital Red Plus 3.5 6TB 5400rpm 256MB SATA3 (WD60EFPX) от 241,72 € (472,76 лв.) Вътрешен хард диск Western Digital - Pazaruvaj.com
Western Digital Red Plus 3.5 6TB 5400rpm 256MB SATA3 (WD60EFPX) от 241,72 € (472,76 лв.) Вътрешен хард диск Western Digital - Pazaruvaj.com
Today's Deals
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architecture - screenpipe docs
architecture - screenpipe docs
Claude Code works better when you stop treating it like a machine - [EMAIL] - Gmail
Claude Code works better when you stop treating it like a machine - [EMAIL] - Gmail
Screenpipe — Archive
Screenpipe — Archive
SQLite Web: archive.db
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SQLite Web: db.sqlite
SQLite Web: db.sqlite
Claude Platform
Claude Platform
Hey @louis030195 Ill check during my - screenpipe.com
Hey @louis030195 Ill check during my - screenpipe.com
GitHub - screenpipe/screenpipe: Run agents that work for you based on what you do. AI finally knows what you are doing · GitHub
GitHub - screenpipe/screenpipe: Run agents that work for you based on what you do. AI finally knows what you are doing · GitHub
Gong Pricing in 2026: Costs, Plans & Is It Worth It?
Gong Pricing in 2026: Costs, Plans & Is It Worth It?
GLM 5.1 Thinks Strategically, Data-Center Revolt Intensifies, When Helpful LLMs Turn Unhelpful, Humanoid Robots Get to Work - [EMAIL] - Gmail
GLM 5.1 Thinks Strategically, Data-Center Revolt Intensifies, When Helpful LLMs Turn Unhelpful, Humanoid Robots Get to Work - [EMAIL] - Gmail
Gitea Official Website
Gitea Official Website
lakylak/screenpipe - screenpipe - Gitea: Git with a cup of tea
lakylak/screenpipe - screenpipe - Gitea: Git with a cup of tea
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Product page for netPower Lite 8P
NEW
netPower Lite 8P
$199.00
*
SFP/SFP+
PoE
Outdoors
IP 54
Low-cost. Tough. And always ON! Compact PoE switch with built-in UPS and smart battery charger – because your CCTV cameras and access points deserve true off-the-grid resilience.
Product page for CRS804 DDQ
NEW
CRS804 DDQ
$1,295.00
*
400G
10G
ARM64
Quad-core CPU
ROS v7
A compact 1U 400G switch built for AI clusters, storage fabrics, and high-speed aggregation, featuring four 400G QSFP56-DD ports, dual 10 Gigabit Ethernet, and RouterOS v7. With hot-swap power supplies, robust cooling, and low power consumption, it delivers ultra-high bandwidth, wire-speed performance, and future-proof scalability at an accessible price point.
Product page for CRS304-4XG-IN
CRS304-4XG-IN
$199.00
*
10G
PoE
ARM64
ROS v7
Compact, powerful, and ready to simplify your 10 Gigabit network setups with 4x10G Ethernet ports ready to use out-of-the-box. No extra modules needed!
Product page for CRS305-1G-4S+IN
CRS305-1G-4S+IN
$149.00
*
SFP/SFP+
PoE
ARM
Five-port desktop switch with one Gigabit Ethernet port and four SFP+ 10Gbps ports
Product page for CRS312-4C+8XG-RM
CRS312-4C+8XG-RM
$699.00
*
10G
Combo ports
ROS v7
Switch of the future: the first MikroTik product with 10G RJ45 Ethernet ports and SFP+
Product page for CRS320-8P-8B-4S+RM
CRS320-8P-8B-4S+RM
$489.00
*
SFP/SFP+
PoE
ARM
ROS v7
The first MikroTik high-power PoE++ switch – for easy and cost-effective powering of industry standard 802.3af/at/bt devices. Forget about countless power cables – create a cleaner space with PoE++!
Product page for CRS317-1G-16S+RM
CRS317-1G-16S+RM
$499.00
*
SFP/SFP+
ARM
Smart Switch, 1 x Gigabit LAN, 16 x SFP+ cages, Dual Core 800MHz CPU, 1GB RAM, 1U rackmount passive cooling case, Dual Power Supplies
Product page for CRS309-1G-8S+IN
CRS309-1G-8S+IN
$269.00
*
SFP/SFP+
PoE
ARM
Desktop switch with one Gigabit Ethernet port and eight SFP+ 10Gbps ports
Product page for CRS518-16XS-2XQ-RM
CRS518-16XS-2XQ-RM
$1,595.00
*
100G
ROS v7
A 100 Gigabit switch for enterprise networks and data centers. Hot-swappable parts and insane port density with 1.2 Tbps switching capacity!
Product page for CRS310-1G-5S-4S+IN
CRS310-1G-5S-4S+IN
$199.00
*
SFP/SFP+
PoE
ARM
ROS v7
10 Gigabit fibre connectivity way over a 100 meters – for small offices or ISPs. Hardware offloaded VLAN-filtering and even some L3 routing on a budget!
Product page for CRS310-8G+2S+IN
CRS310-8G+2S+IN
$219.00
*
SFP/SFP+
2.5G
ARM
ROS v7
Take advantage of the blazing fast 2.5/10 Gigabit combo and upgrade your workspace! This switch can utilize the full potential of RouterOS v7: run VLANs, Jumbo frames, link aggregation, ACL rules, and so much more!
Product page for netPower 16P
netPower 16P
$279.00
*
SFP/SFP+
PoE
ARM
Outdoors
IP 54
An outdoor 18 port switch with 16 Gigabit PoE-out ports and 2 SFP+. Power all your access points anywhere!
Product page for netPower 15FR
netPower 15FR
$169.00
*
SFP/SFP+
PoE
ARM
Outdoors
IP 54
An outdoor 18 port switch with 15 reverse PoE ports and SFP. Cut costs, not speed – choose GPEN over GPON!
Product page for netFiber 9
netFiber 9
$249.00
*
SFP/SFP+
PoE
ARM
Outdoors
IP 54
ROS v7
A remarkable outdoor switch for setting up an optical 10G network that can even perform some light routing. The spiritual successor to the beloved FiberBox. Gigabit Ethernet, SFP/SFP+, PoE.
Product page for CRS326-24G-2S+IN
CRS326-24G-2S+IN
$199.00
*
SFP/SFP+
PoE
ARM
24 Gigabit ports, 2 SFP+ cages and a desktop case – server room power for your home!
Product page for CRS326-24G-2S+RM...
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2149
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2
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2026-04-25T15:36:55.699033+00:00
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/Users/lukas/.screenpipe/data/data/2026-04-25/1777 /Users/lukas/.screenpipe/data/data/2026-04-25/1777131415699_m2.jpg...
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Firefox
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MikroTik · Switches — Personal
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True
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mikrotik.com/products/group/switches
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monitor_2
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NULL
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NULL
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NULL
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Product page for CRS310-8G+2S+IN
DXP4800PLUS-B5F8
Product page for CRS310-8G+2S+IN
DXP4800PLUS-B5F8
Inbox (7) - [EMAIL] - Gmail
(56) Inbox | [EMAIL] | Proton Mail
Welcome back
Welcome back
Western Digital Red Plus 3.5 6TB 5400rpm 256MB SATA3 (WD60EFPX) от 241,72 € (472,76 лв.) Вътрешен хард диск Western Digital - Pazaruvaj.com
Western Digital Red Plus 3.5 6TB 5400rpm 256MB SATA3 (WD60EFPX) от 241,72 € (472,76 лв.) Вътрешен хард диск Western Digital - Pazaruvaj.com
Today's Deals
Today's Deals
architecture - screenpipe docs
architecture - screenpipe docs
Claude Code works better when you stop treating it like a machine - [EMAIL] - Gmail
Claude Code works better when you stop treating it like a machine - [EMAIL] - Gmail
Screenpipe — Archive
Screenpipe — Archive
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Claude Platform
Claude Platform
Hey @louis030195 Ill check during my - screenpipe.com
Hey @louis030195 Ill check during my - screenpipe.com
GitHub - screenpipe/screenpipe: Run agents that work for you based on what you do. AI finally knows what you are doing · GitHub
GitHub - screenpipe/screenpipe: Run agents that work for you based on what you do. AI finally knows what you are doing · GitHub
Gong Pricing in 2026: Costs, Plans & Is It Worth It?
Gong Pricing in 2026: Costs, Plans & Is It Worth It?
GLM 5.1 Thinks Strategically, Data-Center Revolt Intensifies, When Helpful LLMs Turn Unhelpful, Humanoid Robots Get to Work - [EMAIL] - Gmail
GLM 5.1 Thinks Strategically, Data-Center Revolt Intensifies, When Helpful LLMs Turn Unhelpful, Humanoid Robots Get to Work - [EMAIL] - Gmail
Gitea Official Website
Gitea Official Website
lakylak/screenpipe - screenpipe - Gitea: Git with a cup of tea
lakylak/screenpipe - screenpipe - Gitea: Git with a cup of tea
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MikroTik · Switches
MikroTik · Switches
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Product page for netPower Lite 8P
NEW
netPower Lite 8P
$199.00
*
SFP/SFP+
PoE
Outdoors
IP 54
Low-cost. Tough. And always ON! Compact PoE switch with built-in UPS and smart battery charger – because your CCTV cameras and access points deserve true off-the-grid resilience.
Product page for CRS804 DDQ
NEW
CRS804 DDQ
$1,295.00
*
400G
10G
ARM64
Quad-core CPU
ROS v7
A compact 1U 400G switch built for AI clusters, storage fabrics, and high-speed aggregation, featuring four 400G QSFP56-DD ports, dual 10 Gigabit Ethernet, and RouterOS v7. With hot-swap power supplies, robust cooling, and low power consumption, it delivers ultra-high bandwidth, wire-speed performance, and future-proof scalability at an accessible price point.
Product page for CRS304-4XG-IN
CRS304-4XG-IN
$199.00
*
10G
PoE
ARM64
ROS v7
Compact, powerful, and ready to simplify your 10 Gigabit network setups with 4x10G Ethernet ports ready to use out-of-the-box. No extra modules needed!
Product page for CRS305-1G-4S+IN
CRS305-1G-4S+IN
$149.00
*
SFP/SFP+
PoE
ARM
Five-port desktop switch with one Gigabit Ethernet port and four SFP+ 10Gbps ports
Product page for CRS312-4C+8XG-RM
CRS312-4C+8XG-RM
$699.00
*
10G
Combo ports
ROS v7
Switch of the future: the first MikroTik product with 10G RJ45 Ethernet ports and SFP+
Product page for CRS320-8P-8B-4S+RM
CRS320-8P-8B-4S+RM
$489.00
*
SFP/SFP+
PoE
ARM
ROS v7
The first MikroTik high-power PoE++ switch – for easy and cost-effective powering of industry standard 802.3af/at/bt devices. Forget about countless power cables – create a cleaner space with PoE++!
Product page for CRS317-1G-16S+RM
CRS317-1G-16S+RM
$499.00
*
SFP/SFP+
ARM
Smart Switch, 1 x Gigabit LAN, 16 x SFP+ cages, Dual Core 800MHz CPU, 1GB RAM, 1U rackmount passive cooling case, Dual Power Supplies
Product page for CRS309-1G-8S+IN
CRS309-1G-8S+IN
$269.00
*
SFP/SFP+
PoE
ARM
Desktop switch with one Gigabit Ethernet port and eight SFP+ 10Gbps ports
Product page for CRS518-16XS-2XQ-RM
CRS518-16XS-2XQ-RM
$1,595.00
*
100G
ROS v7
A 100 Gigabit switch for enterprise networks and data centers. Hot-swappable parts and insane port density with 1.2 Tbps switching capacity!
Product page for CRS310-1G-5S-4S+IN
CRS310-1G-5S-4S+IN
$199.00
*
SFP/SFP+
PoE
ARM
ROS v7
10 Gigabit fibre connectivity way over a 100 meters – for small offices or ISPs. Hardware offloaded VLAN-filtering and even some L3 routing on a budget!
Product page for CRS310-8G+2S+IN
CRS310-8G+2S+IN
$219.00
*
SFP/SFP+
2.5G
ARM
ROS v7
Take advantage of the blazing fast 2.5/10 Gigabit combo and upgrade your workspace! This switch can utilize the full potential of RouterOS v7: run VLANs, Jumbo frames, link aggregation, ACL rules, and so much more!
Product page for netPower 16P
netPower 16P
$279.00
*
SFP/SFP+
PoE
ARM
Outdoors
IP 54
An outdoor 18 port switch with 16 Gigabit PoE-out ports and 2 SFP+. Power all your access points anywhere!
Product page for netPower 15FR
netPower 15FR
$169.00
*
SFP/SFP+
PoE
ARM
Outdoors
IP 54
An outdoor 18 port switch with 15 reverse PoE ports and SFP. Cut costs, not speed – choose GPEN over GPON!
Product page for netFiber 9
netFiber 9
$249.00
*
SFP/SFP+
PoE
ARM
Outdoors
IP 54
ROS v7
A remarkable outdoor switch for setting up an optical 10G network that can even perform some light routing. The spiritual successor to the beloved FiberBox. Gigabit Ethernet, SFP/SFP+, PoE.
Product page for CRS326-24G-2S+IN
CRS326-24G-2S+IN
$199.00
*
SFP/SFP+
PoE
ARM
24 Gigabit ports, 2 SFP+ cages and a desktop case – server room power for your home!
Product page for CRS326-24G-2S+RM
CRS326-24G-2S+RM
$209.00
*
SFP/SFP+
PoE
ARM
24 Gigabit port switch with 2 x SFP+ cages in 1U rackmount case, Dual boot (RouterOS or SwitchOS)
Product page for CRS326-24S+2Q+RM...
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Product page for CRS310-8G+2S+IN
DXP4800PLUS-B5F8
Product page for CRS310-8G+2S+IN
DXP4800PLUS-B5F8
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Western Digital Red Plus 3.5 6TB 5400rpm 256MB SATA3 (WD60EFPX) от 241,72 € (472,76 лв.) Вътрешен хард диск Western Digital - Pazaruvaj.com
Western Digital Red Plus 3.5 6TB 5400rpm 256MB SATA3 (WD60EFPX) от 241,72 € (472,76 лв.) Вътрешен хард диск Western Digital - Pazaruvaj.com
Today's Deals
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architecture - screenpipe docs
architecture - screenpipe docs
Claude Code works better when you stop treating it like a machine - [EMAIL] - Gmail
Claude Code works better when you stop treating it like a machine - [EMAIL] - Gmail
Screenpipe — Archive
Screenpipe — Archive
SQLite Web: archive.db
SQLite Web: archive.db
SQLite Web: db.sqlite
SQLite Web: db.sqlite
Claude Platform
Claude Platform
Hey @louis030195 Ill check during my - screenpipe.com
Hey @louis030195 Ill check during my - screenpipe.com
GitHub - screenpipe/screenpipe: Run agents that work for you based on what you do. AI finally knows what you are doing · GitHub
GitHub - screenpipe/screenpipe: Run agents that work for you based on what you do. AI finally knows what you are doing · GitHub
Gong Pricing in 2026: Costs, Plans & Is It Worth It?
Gong Pricing in 2026: Costs, Plans & Is It Worth It?
GLM 5.1 Thinks Strategically, Data-Center Revolt Intensifies, When Helpful LLMs Turn Unhelpful, Humanoid Robots Get to Work - [EMAIL] - Gmail
GLM 5.1 Thinks Strategically, Data-Center Revolt Intensifies, When Helpful LLMs Turn Unhelpful, Humanoid Robots Get to Work - [EMAIL] - Gmail
Gitea Official Website
Gitea Official Website
lakylak/screenpipe - screenpipe - Gitea: Git with a cup of tea
lakylak/screenpipe - screenpipe - Gitea: Git with a cup of tea
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Product page for netPower Lite 8P
NEW
netPower Lite 8P
$199.00
*
SFP/SFP+
PoE
Outdoors
IP 54
Low-cost. Tough. And always ON! Compact PoE switch with built-in UPS and smart battery charger – because your CCTV cameras and access points deserve true off-the-grid resilience.
Product page for CRS804 DDQ
NEW
CRS804 DDQ
$1,295.00
*
400G
10G
ARM64
Quad-core CPU
ROS v7
A compact 1U 400G switch built for AI clusters, storage fabrics, and high-speed aggregation, featuring four 400G QSFP56-DD ports, dual 10 Gigabit Ethernet, and RouterOS v7. With hot-swap power supplies, robust cooling, and low power consumption, it delivers ultra-high bandwidth, wire-speed performance, and future-proof scalability at an accessible price point.
Product page for CRS304-4XG-IN
CRS304-4XG-IN
$199.00
*
10G
PoE
ARM64
ROS v7
Compact, powerful, and ready to simplify your 10 Gigabit network setups with 4x10G Ethernet ports ready to use out-of-the-box. No extra modules needed!
Product page for CRS305-1G-4S+IN
CRS305-1G-4S+IN
$149.00
*
SFP/SFP+
PoE
ARM
Five-port desktop switch with one Gigabit Ethernet port and four SFP+ 10Gbps ports
Product page for CRS312-4C+8XG-RM
CRS312-4C+8XG-RM
$699.00
*
10G
Combo ports
ROS v7
Switch of the future: the first MikroTik product with 10G RJ45 Ethernet ports and SFP+
Product page for CRS320-8P-8B-4S+RM
CRS320-8P-8B-4S+RM
$489.00
*
SFP/SFP+
PoE
ARM
ROS v7
The first MikroTik high-power PoE++ switch – for easy and cost-effective powering of industry standard 802.3af/at/bt devices. Forget about countless power cables – create a cleaner space with PoE++!
Product page for CRS317-1G-16S+RM
CRS317-1G-16S+RM
$499.00
*
SFP/SFP+
ARM
Smart Switch, 1 x Gigabit LAN, 16 x SFP+ cages, Dual Core 800MHz CPU, 1GB RAM, 1U rackmount passive cooling case, Dual Power Supplies
Product page for CRS309-1G-8S+IN
CRS309-1G-8S+IN
$269.00
*
SFP/SFP+
PoE
ARM
Desktop switch with one Gigabit Ethernet port and eight SFP+ 10Gbps ports
Product page for CRS518-16XS-2XQ-RM
CRS518-16XS-2XQ-RM
$1,595.00
*
100G
ROS v7
A 100 Gigabit switch for enterprise networks and data centers. Hot-swappable parts and insane port density with 1.2 Tbps switching capacity!
Product page for CRS310-1G-5S-4S+IN
CRS310-1G-5S-4S+IN
$199.00
*
SFP/SFP+
PoE
ARM
ROS v7
10 Gigabit fibre connectivity way over a 100 meters – for small offices or ISPs. Hardware offloaded VLAN-filtering and even some L3 routing on a budget!
Product page for CRS310-8G+2S+IN
CRS310-8G+2S+IN
$219.00
*
SFP/SFP+
2.5G
ARM
ROS v7
Take advantage of the blazing fast 2.5/10 Gigabit combo and upgrade your workspace! This switch can utilize the full potential of RouterOS v7: run VLANs, Jumbo frames, link aggregation, ACL rules, and so much more!
Product page for netPower 16P
netPower 16P
$279.00
*
SFP/SFP+
PoE
ARM
Outdoors
IP 54
An outdoor 18 port switch with 16 Gigabit PoE-out ports and 2 SFP+. Power all your access points anywhere!
Product page for netPower 15FR
netPower 15FR
$169.00
*
SFP/SFP+
PoE
ARM
Outdoors
IP 54
An outdoor 18 port switch with 15 reverse PoE ports and SFP. Cut costs, not speed – choose GPEN over GPON!
Product page for netFiber 9
netFiber 9
$249.00
*
SFP/SFP+
PoE
ARM
Outdoors
IP 54
ROS v7
A remarkable outdoor switch for setting up an optical 10G network that can even perform some light routing. The spiritual successor to the beloved FiberBox. Gigabit Ethernet, SFP/SFP+, PoE.
Product page for CRS326-24G-2S+IN
CRS326-24G-2S+IN
$199.00
*
SFP/SFP+
PoE
ARM
24 Gigabit ports, 2 SFP+ cages and a desktop case – server room power for your home!
Product page for CRS326-24G-2S+RM
CRS326-24G-2S+RM
$209.00
*
SFP/SFP+
PoE
ARM
24 Gigabit port switch with 2 x SFP+ cages in 1U rackmount case, Dual boot (RouterOS or SwitchOS)
Product page for CRS326-24S+2Q+RM...
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