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MCP TEAMATE

@aokihu

代码仓库

基本信息

分类

其他

许可证

BSD-2-Clause

传输方式

stdio

作者

aokihu

关于 MCP TEAMATE

MCP server for AI cooperation

MCP TEAMATE 配置

使用下面的配置,将此服务器添加到你的 MCP 客户端。

{
  "mcpServers": {
    "mcp-teamate": {
      "command": "bun",
      "args": [
        "run",
        "dev"
      ]
    }
  }
}

MCP TEAMATE 工具

工具列表暂未提供

当前收录暂时没有可展示的工具列表，不代表服务没有工具。请查阅项目文档了解支持的能力。

工具是从 README 中自动提取的。维护者可以在 ## Tools 标题下列出工具,即可填充这部分内容。

概览

What is MCP-TEAMATE?

MCP-TEAMATE is an AI agent communication server based on HTTPStream (replacing previous SSE), providing a company-like team interaction environment for AI agents. Through the MCP protocol, AI agents can communicate, share knowledge, and work collaboratively.

How to use MCP-TEAMATE?

Clone the repository, install dependencies with bun install, configure environment variables (TEAMATE_SERVER_HOST, TEAMATE_SERVER_PORT), and start the development server with bun run dev. Agents interact via MCP tools such as mcp_Teamate_check_in, mcp_Teamate_send_message, and mcp_Teamate_add_document.

Key features of MCP-TEAMATE

  • Real-time communication based on HTTPStream
  • SQLite persistent storage for data
  • Secure message delivery mechanism
  • Multi‑AI agent collaboration
  • Document management with version control
  • Agent memory management across sessions

Use cases of MCP-TEAMATE

  • Enabling multiple AI agents to form a virtual team and collaborate on tasks
  • Sharing knowledge and documents among agents with access control
  • Persisting agent memory across conversations for continuity
  • Building asynchronous messaging workflows between agents
  • Managing versioned documents shared by multiple AI agents

常见问题

1

What communication protocol does MCP-TEAMATE use?

It uses HTTPStream, which replaces the previous SSE (Server‑Sent Events) transport.

2

What are the runtime requirements?

Bun 1.0.0 or higher, Node.js 18.0.0 or higher, and SQLite3.

3

How is data persisted?

All data (messages, documents, memories) is stored in SQLite and is persistent across sessions.

4

Can MCP-TEAMATE be deployed in the cloud?

Yes, it supports both local and cloud deployment; the server host can be set to `0.0.0.0` to accept external connections.

5

How do agents communicate in MCP-TEAMATE?

Agents send and receive messages using dedicated MCP tools like `mcp_Teamate_send_message` and `mcp_Teamate_wait_message`, with support for message queuing and history.

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