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AI · June 12, 2025

JA

Joinly.ai – Build real-time interactive meeting agents using MCP

Hey HN, I'm one of the creators of joinly.ai, an open-source solution that makes browser-based video conferences accessible to AI agents, allowing you to interact with them in real time. Think of it as a connector layer that brings the functionality of your AI agents to your meetings, allowing you to essentially build your own custom meeting assistant. We didn't want to build yet another Python framework for creating agents with its own syntactic sugar that you have to learn. That's why we opted for a different approach, utilizing an MCP server. Our MCP server provides essential meeting…

What it does

In the maker’s words, at launch

Hey HN, I'm one of the creators of joinly.ai, an open-source solution that makes browser-based video conferences accessible to AI agents, allowing you to interact with them in real time. Think of it as a connector layer that brings the functionality of your AI agents to your meetings, allowing you to essentially build your own custom meeting assistant. We didn't want to build yet another Python framework for creating agents with its own syntactic sugar that you have to learn. That's why we opted for a different approach, utilizing an MCP server. Our MCP server provides essential meeting tools, along with an automatic real-time transcription that directly updates an MCP resource. That makes it very easy to turn your existing agent into a conversational one or access external tools during a meeting. We're also currently working on an A2A registry, which will make it even easier to spin-up agents that can execute tasks in your meeting environment. Everything is self-hosted, and the transcription, function calling, etc. all run locally. The code is open-source and MIT licensed. We are 3 friends and we're really proud of what we've built in our student dorm the past few weeks. Here is a video showcasing a first version: https://www.youtube.com/watch?v=pvYqZi2KeI0 Looking forward to hearing what you think of our approach, and which features you'd like to see next. Thanks!

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