MCP Server for Apache Airflow

Instructions

Implementation Reference

• src/airflow/dagrun.py:70-122 (handler)

  The primary handler function for the 'get_dag_runs' tool. It fetches DAG runs using the Airflow API with optional query parameters, enhances the response with UI links, and returns formatted text content.

  async def get_dag_runs(
      dag_id: str,
      limit: Optional[int] = None,
      offset: Optional[int] = None,
      execution_date_gte: Optional[str] = None,
      execution_date_lte: Optional[str] = None,
      start_date_gte: Optional[str] = None,
      start_date_lte: Optional[str] = None,
      end_date_gte: Optional[str] = None,
      end_date_lte: Optional[str] = None,
      updated_at_gte: Optional[str] = None,
      updated_at_lte: Optional[str] = None,
      state: Optional[List[str]] = None,
      order_by: Optional[str] = None,
  ) -> List[Union[types.TextContent, types.ImageContent, types.EmbeddedResource]]:
      # Build parameters dictionary
      kwargs: Dict[str, Any] = {}
      if limit is not None:
          kwargs["limit"] = limit
      if offset is not None:
          kwargs["offset"] = offset
      if execution_date_gte is not None:
          kwargs["execution_date_gte"] = execution_date_gte
      if execution_date_lte is not None:
          kwargs["execution_date_lte"] = execution_date_lte
      if start_date_gte is not None:
          kwargs["start_date_gte"] = start_date_gte
      if start_date_lte is not None:
          kwargs["start_date_lte"] = start_date_lte
      if end_date_gte is not None:
          kwargs["end_date_gte"] = end_date_gte
      if end_date_lte is not None:
          kwargs["end_date_lte"] = end_date_lte
      if updated_at_gte is not None:
          kwargs["updated_at_gte"] = updated_at_gte
      if updated_at_lte is not None:
          kwargs["updated_at_lte"] = updated_at_lte
      if state is not None:
          kwargs["state"] = state
      if order_by is not None:
          kwargs["order_by"] = order_by
  
      response = dag_run_api.get_dag_runs(dag_id=dag_id, **kwargs)
  
      # Convert response to dictionary for easier manipulation
      response_dict = response.to_dict()
  
      # Add UI links to each DAG run
      for dag_run in response_dict.get("dag_runs", []):
          dag_run["ui_url"] = get_dag_run_url(dag_id, dag_run["dag_run_id"])
  
      return [types.TextContent(type="text", text=str(response_dict))]

• src/airflow/dagrun.py:17-29 (registration)

  Module-level registration function that includes the tuple for 'get_dag_runs' tool, providing the function reference, name, description, and read-only flag.

  def get_all_functions() -> list[tuple[Callable, str, str, bool]]:
      """Return list of (function, name, description, is_read_only) tuples for registration."""
      return [
          (post_dag_run, "post_dag_run", "Trigger a DAG by ID", False),
          (get_dag_runs, "get_dag_runs", "Get DAG runs by ID", True),
          (get_dag_runs_batch, "get_dag_runs_batch", "List DAG runs (batch)", True),
          (get_dag_run, "get_dag_run", "Get a DAG run by DAG ID and DAG run ID", True),
          (update_dag_run_state, "update_dag_run_state", "Update a DAG run state by DAG ID and DAG run ID", False),
          (delete_dag_run, "delete_dag_run", "Delete a DAG run by DAG ID and DAG run ID", False),
          (clear_dag_run, "clear_dag_run", "Clear a DAG run", False),
          (set_dag_run_note, "set_dag_run_note", "Update the DagRun note", False),
          (get_upstream_dataset_events, "get_upstream_dataset_events", "Get dataset events for a DAG run", True),
      ]

• src/main.py:95-97 (registration)

  Top-level tool registration loop in the main entrypoint, which adds the 'get_dag_runs' tool (imported via dagrun module) to the MCP app using Tool.from_function.

  for func, name, description, *_ in functions:
      app.add_tool(Tool.from_function(func, name=name, description=description))

• src/airflow/dagrun.py:32-33 (helper)

  Helper utility to generate the Airflow UI URL for a specific DAG run, used within the get_dag_runs handler to enhance the response.

  def get_dag_run_url(dag_id: str, dag_run_id: str) -> str:
      return f"{AIRFLOW_HOST}/dags/{dag_id}/grid?dag_run_id={dag_run_id}"