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Auto MCP Server

@NapthaAI

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基本情報

カテゴリ

その他

ライセンス

Apache-2.0

トランスポート

stdio

作者

NapthaAI

Auto MCP Server について

Easily convert tool, agents and orchestrators from existing agent frameworks to MCP servers

#auto-mcp#mcp-servers#automation

Auto MCP Server の設定

以下の設定を使って、このサーバーを MCP 対応クライアントに追加してください。

{
  "mcpServers": {
    "auto-mcp": {
      "command": "uv",
      "args": [
        "venv"
      ]
    }
  }
}

Auto MCP Server のツール

ツール一覧はまだありません

この掲載には表示できるツール一覧がまだありません。サーバーにツールがないという意味ではありません。対応機能はプロジェクトのドキュメントをご確認ください。

ツールは README から自動的に抽出されます。メンテナーは ## Tools という見出しの下に記載することで、このタブに反映できます。

概要

What is auto-mcp?

auto-mcp converts tools, agents, and orchestrators from CrewAI, LangGraph, Llama Index, OpenAI Agents SDK, Pydantic AI, and mcp-agent into MCP servers for standardized access via clients like Cursor and Claude Desktop.

How to use auto-mcp?

Install the package (pip install naptha-automcp), run automcp init -f <framework> in your project directory to generate run_mcp.py, edit it to import your agent and define an input schema with Pydantic, then run automcp serve -t sse or automcp serve -t stdio. The server can also be run directly with Python or uv.

Key features of auto-mcp

  • Converts existing agent frameworks into MCP servers
  • Supports CrewAI, LangGraph, Llama Index, OpenAI Agents SDK, Pydantic AI, and mcp-agent
  • Generates run_mcp.py with STDIO and SSE transport handlers
  • CLI commands for initialization and server serving
  • Includes examples for each supported framework
  • Can deploy to Naptha's MCPaaS platform

Use cases of auto-mcp

  • Integrate existing CrewAI crews into Cursor IDE
  • Expose LangGraph agents as MCP tools for Claude Desktop
  • Deploy Llama Index agents via Naptha's MCPaaS platform
  • Create standardized MCP endpoints for OpenAI Agents SDK orchestrators

よくある質問

1

Which agent frameworks does auto-mcp support?

CrewAI, LangGraph, Llama Index, OpenAI Agents SDK, Pydantic AI, and mcp-agent.

2

What transport modes are available?

STDIO (client starts the server automatically) and SSE (user starts the server separately, then client connects).

3

How do I avoid STDIO protocol corruption with print statements?

The generated server includes utilities to suppress warnings, and print statements in agent code can corrupt STDIO.

4

Where can I deploy my auto-mcp server?

You can deploy locally or use Naptha's MCPaaS platform after configuring pyproject.toml correctly.

5

What are the runtime dependencies?

Python, pip or uv, and the target agent framework (e.g., crewai, langgraph) along with their API keys.

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