debugpy-mcp

An enhanced MCP server for Cursor that helps an agent attach debugpy to an already-running Python process inside a Docker container, inspect context, retrieve logs, and suggest breakpoint plans for FastAPI-style services.

Features

• List running containers
• Autodiscover a likely target container by name, image, or service hint
• Inspect whether a target container is ready for debugpy attach
• Inject debugpy into a live PID inside the container
• Prefer uvicorn and gunicorn worker processes automatically
• Return rich debugging context for an agent
• Fetch recent container logs and debugpy log files
• Suggest a breakpoint plan from logs and process metadata

Tools

• debugpy_connect — check if debugpy is already listening at a host:port (no Docker required)
• debugpy_list_containers
• debugpy_autodiscover_target
• debugpy_status
• debugpy_attach
• debugpy_context
• debugpy_logs
• debugpy_debugpy_logs
• debugpy_breakpoint_plan

Install

pip / venv

python -m venv .venv
source .venv/bin/activate
pip install -e .

uv

uv venv
uv pip install -e .

Or install directly without cloning:

uv tool install debugpy-mcp

Poetry

poetry install

Run manually

pip / venv

debugpy-mcp

uv

uv run debugpy-mcp

Poetry

poetry run debugpy-mcp

Cursor MCP config

Cursor reads MCP server config from ~/.cursor/mcp.json (global) or .cursor/mcp.json (project-local).

pip / venv

{
  "mcpServers": {
    "debugpy-docker": {
      "command": "/absolute/path/to/debugpy-mcp/.venv/bin/debugpy-mcp",
      "args": []
    }
  }
}

uv (recommended)

If you installed with uv tool install, uvx can run the server without activating an environment:

{
  "mcpServers": {
    "debugpy-docker": {
      "command": "uvx",
      "args": ["debugpy-mcp"]
    }
  }
}

If you installed with uv pip install -e . into a project venv, point directly at the binary:

{
  "mcpServers": {
    "debugpy-docker": {
      "command": "/absolute/path/to/debugpy-mcp/.venv/bin/debugpy-mcp",
      "args": []
    }
  }
}

Or run via uv run from the project directory:

{
  "mcpServers": {
    "debugpy-docker": {
      "command": "uv",
      "args": ["--directory", "/absolute/path/to/debugpy-mcp", "run", "debugpy-mcp"]
    }
  }
}

Poetry

Poetry manages its own virtualenv. Use poetry run so Cursor doesn't need to know the venv path:

{
  "mcpServers": {
    "debugpy-docker": {
      "command": "poetry",
      "args": ["--directory", "/absolute/path/to/debugpy-mcp", "run", "debugpy-mcp"]
    }
  }
}

Alternatively, find the venv path with poetry env info --path and reference the binary directly:

{
  "mcpServers": {
    "debugpy-docker": {
      "command": "/path/from/poetry-env-info/bin/debugpy-mcp",
      "args": []
    }
  }
}

Example workflow in Cursor

1. Ask the agent to run debugpy_autodiscover_target with service_hint="api".
2. Ask the agent to run debugpy_status.
3. Ask the agent to run debugpy_attach.
4. Start your existing Attach configuration in Cursor.
5. Ask the agent to run debugpy_context, debugpy_logs, or debugpy_breakpoint_plan.

Notes

debugpy must exist inside the container

You need debugpy installed in the target image or container.

PID attach may require ptrace permissions

If attach fails with Operation not permitted, the container may need additional capabilities such as:

• cap_add: [SYS_PTRACE]
• relaxed seccomp profile if required in your environment

Gunicorn/Uvicorn worker setups

Attaching to a master process is often less useful than attaching to a worker process. The tool prefers uvicorn and worker processes first, but you can always pass a specific PID manually.

Path mappings still matter

Your IDE attach config must map local source paths to remote container source paths.

Example:

{
  "name": "Attach FastAPI in Docker",
  "type": "debugpy",
  "request": "attach",
  "connect": {
    "host": "localhost",
    "port": 5678
  },
  "pathMappings": [
    {
      "localRoot": "${workspaceFolder}",
      "remoteRoot": "/app"
    }
  ]
}