debugpy_logs

Implementation Reference

• src/debugpy_mcp/server.py:523-533 (handler)

  The main handler for the 'debugpy_logs' tool. Decorated with @mcp.tool(), it runs 'docker logs --tail' on the specified container, combines stdout and stderr, and returns a LogsResult with the combined logs.

  @mcp.tool()
  def debugpy_logs(container: str, tail: int = 250) -> dict[str, Any]:
      proc = run(["docker", "logs", "--tail", str(tail), container], timeout=30, check=False)
      combined = ""
      if proc.stdout:
          combined += proc.stdout
      if proc.stderr:
          if combined:
              combined += "\n"
          combined += proc.stderr
      return LogsResult(ok=proc.returncode == 0, container=container, tail=tail, logs=combined.strip()).model_dump()

• src/debugpy_mcp/server.py:83-88 (schema)

  Pydantic model defining the output schema for debugpy_logs. Contains fields: ok (bool), container (str), tail (int), and logs (str).

  class LogsResult(BaseModel):
      ok: bool
      container: str
      tail: int
      logs: str

• src/debugpy_mcp/server.py:523-523 (registration)

  The @mcp.tool() decorator registers the debugpy_logs function as an MCP tool with the FastMCP server instance.

  @mcp.tool()

• src/debugpy_mcp/server.py:116-123 (helper)

  Helper function 'run' that executes subprocess commands with configurable timeout and error checking. Used by debugpy_logs to invoke 'docker logs'.

  def run(cmd: list[str], *, timeout: int = DEFAULT_TIMEOUT, check: bool = True) -> subprocess.CompletedProcess[str]:
      proc = subprocess.run(cmd, capture_output=True, text=True, timeout=timeout)
      if check and proc.returncode != 0:
          raise ToolError(
              f"Command failed ({proc.returncode}): {' '.join(cmd)}\n"
              f"STDOUT:\n{proc.stdout}\nSTDERR:\n{proc.stderr}"
          )
      return proc