MCP Server Airflow Token

Instructions

Implementation Reference

• src/airflow/dagrun.py:215-220 (handler)

  The async handler function that implements the core logic of the set_dag_run_note tool by creating a SetDagRunNote model and calling the Airflow DAGRunApi to update the DAG run note.

  async def set_dag_run_note(
      dag_id: str, dag_run_id: str, note: str
  ) -> List[Union[types.TextContent, types.ImageContent, types.EmbeddedResource]]:
      set_dag_run_note = SetDagRunNote(note=note)
      response = dag_run_api.set_dag_run_note(dag_id=dag_id, dag_run_id=dag_run_id, set_dag_run_note=set_dag_run_note)
      return [types.TextContent(type="text", text=str(response.to_dict()))]

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

  The registration point where the set_dag_run_note tool is listed in the get_all_functions() return value for MCP tool registration, specifying the handler function, name, description, and read-only status.

  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/airflow/dagrun.py:8-8 (schema)

  Import of the SetDagRunNote model class, which defines the input schema (note field) for the set_dag_run_note tool.

  from airflow_client.client.model.set_dag_run_note import SetDagRunNote