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`).
@HeyBatlle1
Basic information
this is a cloned version of
Add this server to your MCP-compatible client using the configuration below.
{
"mcpServers": {
"medical-mcp-server": {
"command": "python3",
"args": [
"-m",
"venv",
"venv"
]
}
}
}Tool list not available yet
This listing does not currently have a tool list to display. This does not mean the server has no tools; check its documentation for supported capabilities.
We auto-extract tools from the README. The maintainer can list them under a ## Tools heading to populate this section.
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.
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".
medical_core.pyIt provides a direct MCP interface (via your original script) and an HTTP REST API interface (via FastAPI in `api_server.py`).
`GET /api/status` returns the server status; `POST /api/medical/trauma-assessment` performs a trauma assessment and returns severity, immediate actions, and red flags.
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.
Python dependencies listed in `requirements.txt`, including FastAPI, uvicorn, and Pydantic. PM2 (Node.js) is optional for process management

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