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Python Medical MCP Server

@HeyBatlle1

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基本情報

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その他

トランスポート

stdio

作者

HeyBatlle1

Python Medical MCP Server について

this is a cloned version of

#medical-mcp-server#python#fastapi

Python Medical 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": {
    "medical-mcp-server": {
      "command": "python3",
      "args": [
        "-m",
        "venv",
        "venv"
      ]
    }
  }
}

Python Medical 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 Python Medical MCP Server?

A Python-based server that provides a dual interface – direct Model Context Protocol (MCP) and an HTTP REST API (FastAPI) – for performing trauma assessments. It uses a shared core medical logic module and is designed for medical assessment applications.

How to use Python Medical MCP Server?

Clone the repository, create a Python virtual environment, install dependencies from requirements.txt, then run two processes: your existing MCP script and api_server.py. You can manage them manually or with PM2. Example commands: pm2 start your_original_mcp_script.py --name "python-mcp-direct" --interpreter python3 and pm2 start "uvicorn api_server:app --host 0.0.0.0 --port 8002" --name "python-mcp-http-api".

Key features of Python Medical MCP Server

  • Shared medical logic centralized in medical_core.py
  • FastAPI HTTP server with RESTful endpoints
  • CORS enabled for frontend applications
  • Pydantic validation for request and response
  • PM2 ready for process management

Use cases of Python Medical MCP Server

  • Performing trauma assessments via a direct MCP client
  • Integrating trauma assessment into web applications (e.g., Bolt.new) through the HTTP API
  • Deploying a medical assessment service usable by both AI agents and web frontends

よくある質問

1

What interfaces does the Python Medical MCP Server provide?

It provides a direct MCP interface (via your original script) and an HTTP REST API interface (via FastAPI in `api_server.py`).

2

What are the main API endpoints?

`GET /api/status` returns the server status; `POST /api/medical/trauma-assessment` performs a trauma assessment and returns severity, immediate actions, and red flags.

3

How do I install and run the server?

Clone the repo, create a virtual environment, run `pip install -r requirements.txt`, then start the MCP script and the API server either manually or with PM2.

4

What dependencies are required?

Python dependencies listed in `requirements.txt`, including FastAPI, uvicorn, and Pydantic. PM2 (Node.js) is optional for process management

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