set_task_instances_state
Change the state of Airflow task instances to manage workflow execution, such as marking tasks as failed or successful for troubleshooting or manual intervention.
Instructions
Set a state of task instances
Input Schema
TableJSON Schema
| Name | Required | Description | Default |
|---|---|---|---|
| dag_id | Yes | ||
| state | Yes | ||
| task_ids | No | ||
| execution_date | No | ||
| include_upstream | No | ||
| include_downstream | No | ||
| include_future | No | ||
| include_past | No | ||
| dry_run | No |
Implementation Reference
- src/airflow/dag.py:236-269 (handler)The main asynchronous handler function for the 'set_task_instances_state' tool. It constructs an UpdateTaskInstancesState object from the input parameters and calls the Airflow DAG API to set the state of the specified task instances.
async def set_task_instances_state( dag_id: str, state: str, task_ids: Optional[List[str]] = None, execution_date: Optional[str] = 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, ) -> List[Union[types.TextContent, types.ImageContent, types.EmbeddedResource]]: state_request = {"state": state} if task_ids is not None: state_request["task_ids"] = task_ids if execution_date is not None: state_request["execution_date"] = execution_date if include_upstream is not None: state_request["include_upstream"] = include_upstream if include_downstream is not None: state_request["include_downstream"] = include_downstream if include_future is not None: state_request["include_future"] = include_future if include_past is not None: state_request["include_past"] = include_past if dry_run is not None: state_request["dry_run"] = dry_run update_task_instances_state = UpdateTaskInstancesState(**state_request) response = dag_api.post_set_task_instances_state( dag_id=dag_id, update_task_instances_state=update_task_instances_state, ) return [types.TextContent(type="text", text=str(response.to_dict()))] - src/airflow/dag.py:15-33 (registration)The registration of all tools, including 'set_task_instances_state' as a tuple (function, name, description, is_read_only=False). This list is returned by get_all_functions() for MCP tool registration.
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), ]