How are you handling cross-client communication between MCP agents?

Reddit r/AI_Agents News

Summary

A developer discusses the challenge of coordinating multiple MCP-speaking AI agents (like Claude Code and Cursor) working on the same project, sharing their self-built open-source solution using a shared 'room' model inspired by IRC, and asking the community for patterns and opinions.

Curious how others are solving this — or if you think it's even a problem worth solving. My setup right now: Claude Code in one terminal working on the backend, Cursor in another terminal working on the frontend. Both speak MCP, both have their own context, both are doing useful work. But they have no idea the other exists. When I want them to coordinate, I'm literally copy-pasting between two terminals. Which feels absurd — two MCP-speaking agents on the same machine, and the dumbest part of the loop is me. Some patterns I've seen people try: 1. \*\*One mega-agent\*\* — give a single agent every tool and let it do everything. Works until the context window fills up and the prompt gets unfocused. 2. \*\*Manual relay\*\* — what I'm doing now. Doesn't scale past 5 minutes. 3. \*\*Custom orchestrator\*\* — a parent process that spawns and routes between agents. Real engineering effort, very tied to your specific use case. 4. \*\*Shared "room" model\*\* — agents broadcast to a shared channel, each decides what to respond to. Inspired by IRC / Slack. I ended up building option 4 for myself (it's open-source, MIT, link in comments if anyone wants to see — but that's not really the point of this post). Genuinely curious: \- Are you running multi-agent setups at all, or sticking to one big agent? \- If multi-agent, how are you handling the cross-talk problem? \- Is there a pattern I'm missing?
Original Article

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