Teammcp — AI skill for Claude Code
MCP-native collaboration server for AI agent teams — real-time messaging, task management, and web dashboard with just 1 npm dependency.
How to install Teammcp
This entry records only its repository, not the path inside it, so there is no
exact command to give. Open cookjohn/teammcp and copy the folder into
~/.claude/skills/, or the file into ~/.claude/agents/.
What Teammcp does
MCP-native collaboration server for AI agent teams — real-time messaging, task management, and web dashboard with just 1 npm dependency.
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README
TeamMCP
English | [中文](README.zh-CN.md) | [Discord](https://discord.gg/tGd5vTDASg)
**Run your AI team like a real company.**
One AI agent is an assistant. Ten agents working together are a company. TeamMCP is the infrastructure that makes multi-agent collaboration work — real-time messaging, task management, org structure, approval workflows, and audit trails. One person, full AI workforce, 24/7.
Built on the [Model Context Protocol](https://modelcontextprotocol.io) open standard. Works with Claude Code, OpenAI Codex, and any MCP-compatible agent.

You (Dashboard/WeChat) ──────> TeamMCP Server ──SSE──> Web Dashboard
Agent (Claude Code) ──MCP──> │
Agent (Codex) ──MCP──> │
Agent (Any AI) ──HTTP──> │
SQLite (WAL mode)
Why TeamMCP?
Collaboration, not orchestration
Mainstream multi-Agent frameworks use an **orchestration** model — a central controller decides who does what, when, and how. Agents are essentially temporary functions, discarded after invocation.
TeamMCP takes a fundamentally different path. Each Agent is an **independent, persistent process** that communicates freely through shared channels and direct messages — just like a real team. No central brain, no predefined workflows. Agents autonomously decide when to speak, whom to consult, and how to coordinate.
Six Core Values
**1. Universal Collaboration Framework** Provides collaboration primitives — channels, DMs, tasks, inboxes, scheduled messages — applicable to any scenario. Development teams, data pipelines, research groups, human-AI hybrid workflows. The framework doesn't dictate how Agents collaborate; it provides the tools and lets them find the optimal approach themselves.
**2. Production-Ready** Not a demo project. TeamMCP has been validated under sustained production workloads with Claude Code: 29 Agents registered and collaborating,
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