physionet-mcp

Lean MCP server for PhysioNet datasets - works with any PhysioNet dataset you have access to.

📺 This is a lean version of m3 with similar BigQuery and PhysioNet setup. Check out detailed videos here: https://rafiattrach.github.io/m3/

Quick Setup

Production (After PyPI release)

{
  "mcpServers": {
    "physionet-mcp": {
      "command": "uvx",
      "args": ["physionet-mcp"],
      "env": {
        "BIGQUERY_PROJECT_ID": "your-project-id"
      }
    }
  }
}

Local Development

{
  "mcpServers": {
    "physionet-mcp": {
      "command": "/path/to/physionet-mcp/venv/bin/python",
      "args": ["-m", "physionet_mcp.mcp_server"],
      "cwd": "/path/to/physionet-mcp",
      "env": {
        "BIGQUERY_PROJECT_ID": "your-project-id"
      }
    }
  }
}

Replace your-project-id with your Google Cloud project ID.

4 Simple Tools

1. list_accessible_datasets → See what you can access
2. get_database_schema → Find tables in a dataset
3. get_table_info → Check structure & sample data
4. execute_query → Run your analysis

Usage Examples

• "What PhysioNet datasets can I access?"
• "Show me MIMIC-IV hospital tables"
• "What's in the patients table?"
• "How many patients are in MIMIC-IV?"

Future Enhancements

Potential improvements for enterprise use:

• Dataset filtering - Restrict access to specific datasets for security
• Query optimization - Add result caching and query cost tracking
• Rate limiting - Implement query throttling for shared environments
• Enhanced metadata - Add column descriptions and data quality metrics

License

MIT