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MCP Server for Apache Airflow

by yangkyeongmo

delete_dag_run

Remove a specific DAG run in Apache Airflow by specifying the DAG ID and DAG run ID through MCP Server for efficient workflow management.

Instructions

Delete a DAG run by DAG ID and DAG run ID

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
dag_idYes
dag_run_idYes

Implementation Reference

  • The main handler function for the 'delete_dag_run' tool. It calls the Airflow DAGRunApi to delete the DAG run specified by dag_id and dag_run_id, and returns a text response with the API result.
    async def delete_dag_run( dag_id: str, dag_run_id: str ) -> List[Union[types.TextContent, types.ImageContent, types.EmbeddedResource]]: response = dag_run_api.delete_dag_run(dag_id=dag_id, dag_run_id=dag_run_id) return [types.TextContent(type="text", text=str(response.to_dict()))]
  • The get_all_functions() in this module returns the list of all DAG run tools, including the registration tuple for 'delete_dag_run' (function reference, name, description, read-only=false).
    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:95-96 (registration)
    The central registration loop in main.py that adds all tools from various modules (including dagrun) 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))

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