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joinly-ai/joinly

by Various

Make your meetings accessible to AI Agents

J

MCP

joinly-ai/joinly

Added 1 June 2026

#agentic-ai #ai-agent #ai-tool #conversational-ai #llm #mcp #meeting-agent #meeting-assistant

Overview

A Python library that bridges meeting platforms with AI agent workflows. It enables AI agents to join, listen, and interact in virtual meetings by providing a unified interface for real-time audio and video streams.

Best for

Best for
Developers building AI agents that need to access meeting content

Use cases

  • Integrating AI assistants into virtual meetings
  • Automating meeting transcription and analysis
  • Building AI agents that participate in real-time discussions

How to use

Install

docker run -p 8000:8000 ghcr.io/joinly-ai/joinly:latest

Example client config

{\n    "mcpServers": {\n        "localServer": {\n            "command": "npx",\n            "args": ["-y", "package@0.1.0"]\n        },\n        "remoteServer": {\n            "url": "http://mcp.example.com",\n            "auth": "oauth"\n        }\n    }\n}

Notes

A Python library that bridges meeting platforms with AI agent workflows. It enables AI agents to join, listen, and interact in virtual meetings by providing a unified interface for real-time audio and video streams.

522 stars on GitHub. Last updated 2026-03-19. Licensed MIT.

Use cases

  • Integrating AI assistants into virtual meetings
  • Automating meeting transcription and analysis
  • Building AI agents that participate in real-time discussions

Pros

  • Open source with an active community (522 stars)
  • Python-based, easy to integrate into existing AI pipelines
  • Simplifies connecting multiple meeting platforms to AI agents

Cons

  • Limited documentation or examples may slow onboarding
  • Requires additional setup for specific meeting platform APIs
  • Dependency on third-party services for audio/video access

Indexed from awesome-mcp-servers-punkpeye and enriched against its public facts.

Pros

  • Open source with an active community (522 stars)
  • Python-based, easy to integrate into existing AI pipelines
  • Simplifies connecting multiple meeting platforms to AI agents

Cons

  • Limited documentation or examples may slow onboarding
  • Requires additional setup for specific meeting platform APIs
  • Dependency on third-party services for audio/video access
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