patch_dags
Modify multiple DAGs in Apache Airflow by updating parameters like pause state, tags, or filtering by ID pattern efficiently.
Instructions
Update multiple DAGs
Input Schema
TableJSON Schema
| Name | Required | Description | Default |
|---|---|---|---|
| dag_id_pattern | No | ||
| is_paused | No | ||
| tags | No |
Implementation Reference
- src/airflow/dag.py:144-166 (handler)The async handler function implementing the 'patch_dags' tool. It builds an update request for DAG properties (is_paused, tags) and calls the Airflow DAG API to patch matching DAGs based on dag_id_pattern.async def patch_dags( dag_id_pattern: Optional[str] = None, is_paused: Optional[bool] = None, tags: Optional[List[str]] = None, ) -> List[Union[types.TextContent, types.ImageContent, types.EmbeddedResource]]: update_request = {} update_mask = [] if is_paused is not None: update_request["is_paused"] = is_paused update_mask.append("is_paused") if tags is not None: update_request["tags"] = tags update_mask.append("tags") dag = DAG(**update_request) kwargs = {} if dag_id_pattern is not None: kwargs["dag_id_pattern"] = dag_id_pattern response = dag_api.patch_dags(dag_id_pattern=dag_id_pattern, dag=dag, update_mask=update_mask, **kwargs) return [types.TextContent(type="text", text=str(response.to_dict()))]
- src/airflow/dag.py:15-33 (registration)Module-level registration function get_all_functions() that returns tuples for all DAG-related tools, including (patch_dags, 'patch_dags', 'Update multiple DAGs', False). This list is imported and used in src/main.py to register the tools with the MCP server.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:95-96 (registration)The registration loop in the main entrypoint that adds each tool (including patch_dags when DAG API is enabled) to the FastMCP app using Tool.from_function.for func, name, description, *_ in functions: app.add_tool(Tool.from_function(func, name=name, description=description))