clear_task_instances

Instructions

Implementation Reference

• src/airflow/dag.py:190-231 (handler)

  The main handler function for the 'clear_task_instances' tool. It constructs a ClearTaskInstances object from input parameters and calls the Airflow DAG API to clear the specified task instances.

  async def clear_task_instances(
      dag_id: str,
      task_ids: Optional[List[str]] = None,
      start_date: Optional[str] = None,
      end_date: Optional[str] = None,
      include_subdags: Optional[bool] = None,
      include_parentdag: Optional[bool] = None,
      include_upstream: Optional[bool] = None,
      include_downstream: Optional[bool] = None,
      include_future: Optional[bool] = None,
      include_past: Optional[bool] = None,
      dry_run: Optional[bool] = None,
      reset_dag_runs: Optional[bool] = None,
  ) -> List[Union[types.TextContent, types.ImageContent, types.EmbeddedResource]]:
      clear_request = {}
      if task_ids is not None:
          clear_request["task_ids"] = task_ids
      if start_date is not None:
          clear_request["start_date"] = start_date
      if end_date is not None:
          clear_request["end_date"] = end_date
      if include_subdags is not None:
          clear_request["include_subdags"] = include_subdags
      if include_parentdag is not None:
          clear_request["include_parentdag"] = include_parentdag
      if include_upstream is not None:
          clear_request["include_upstream"] = include_upstream
      if include_downstream is not None:
          clear_request["include_downstream"] = include_downstream
      if include_future is not None:
          clear_request["include_future"] = include_future
      if include_past is not None:
          clear_request["include_past"] = include_past
      if dry_run is not None:
          clear_request["dry_run"] = dry_run
      if reset_dag_runs is not None:
          clear_request["reset_dag_runs"] = reset_dag_runs
  
      clear_task_instances = ClearTaskInstances(**clear_request)
  
      response = dag_api.post_clear_task_instances(dag_id=dag_id, clear_task_instances=clear_task_instances)
      return [types.TextContent(type="text", text=str(response.to_dict()))]

• src/airflow/dag.py:15-33 (registration)

  The get_all_functions in dag.py includes the registration tuple for clear_task_instances, which is later used in main.py to add the tool.

  def get_all_functions() -> list[tuple[Callable, str, str, bool]]:
      """Return list of (function, name, description, is_read_only) tuples for registration."""
      return [
          (get_dags, "fetch_dags", "Fetch all DAGs", True),
          (get_dag, "get_dag", "Get a DAG by ID", True),
          (get_dag_details, "get_dag_details", "Get a simplified representation of DAG", True),
          (get_dag_source, "get_dag_source", "Get a source code", True),
          (pause_dag, "pause_dag", "Pause a DAG by ID", False),
          (unpause_dag, "unpause_dag", "Unpause a DAG by ID", False),
          (get_dag_tasks, "get_dag_tasks", "Get tasks for DAG", True),
          (get_task, "get_task", "Get a task by ID", True),
          (get_tasks, "get_tasks", "Get tasks for DAG", True),
          (patch_dag, "patch_dag", "Update a DAG", False),
          (patch_dags, "patch_dags", "Update multiple DAGs", False),
          (delete_dag, "delete_dag", "Delete a DAG", False),
          (clear_task_instances, "clear_task_instances", "Clear a set of task instances", False),
          (set_task_instances_state, "set_task_instances_state", "Set a state of task instances", False),
          (reparse_dag_file, "reparse_dag_file", "Request re-parsing of a DAG file", False),
      ]

• src/main.py:90-92 (registration)

  The generic registration loop in main.py where tools from all modules, including clear_task_instances from dag.py, are added to the MCP app using app.add_tool.

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