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MCP Server for Apache Airflow

by yangkyeongmo

set_dag_run_note

Add or update notes for specific DAG runs in Apache Airflow by providing the DAG ID, run ID, and note content. Simplify task tracking and documentation.

Instructions

Update the DagRun note

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
dag_idYes
dag_run_idYes
noteYes

Implementation Reference

  • The main handler function that executes the set_dag_run_note tool logic. It takes dag_id, dag_run_id, and note as parameters, creates a SetDagRunNote model, calls the Airflow API, and returns the response.
    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()))]
  • The get_all_functions() which returns the list of DAG run related tools for MCP registration, including the set_dag_run_note tool.
    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), ]
  • Import of the SetDagRunNote schema/model used to structure the input parameters for the set_dag_run_note tool.
    from airflow_client.client.model.set_dag_run_note import SetDagRunNote

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