get_tasks
Retrieve and list tasks associated with a specific DAG in Apache Airflow deployments, enabling users to view task details and organization within workflows.
Instructions
Get tasks for DAG
Input Schema
| Name | Required | Description | Default |
|---|---|---|---|
| dag_id | Yes | ||
| order_by | No |
Input Schema (JSON Schema)
{
"properties": {
"dag_id": {
"title": "Dag Id",
"type": "string"
},
"order_by": {
"anyOf": [
{
"type": "string"
},
{
"type": "null"
}
],
"default": null,
"title": "Order By"
}
},
"required": [
"dag_id"
],
"type": "object"
}
Implementation Reference
- src/airflow/dag.py:179-187 (handler)The main handler function that executes the 'get_tasks' tool. It accepts a required 'dag_id' and optional 'order_by', calls the Airflow DAG API to retrieve tasks, and returns the response formatted as MCP TextContent.async def get_tasks( dag_id: str, order_by: Optional[str] = None ) -> List[Union[types.TextContent, types.ImageContent, types.EmbeddedResource]]: kwargs = {} if order_by is not None: kwargs["order_by"] = order_by response = dag_api.get_tasks(dag_id=dag_id, **kwargs) return [types.TextContent(type="text", text=str(response.to_dict()))]
- src/airflow/dag.py:15-33 (registration)Registers the 'get_tasks' tool (at line 26 of the returned list) by including it in the list of DAG-related functions provided to the MCP server via src/main.py. Each entry is a tuple of (function, name, description, read_only).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:22-38 (registration)Maps APIType.DAG to get_dag_functions (imported from src.airflow.dag.get_all_functions at line 7), enabling the registration of DAG tools including 'get_tasks' when the DAG API is selected.APITYPE_TO_FUNCTIONS = { APIType.CONFIG: get_config_functions, APIType.CONNECTION: get_connection_functions, APIType.DAG: get_dag_functions, APIType.DAGRUN: get_dagrun_functions, APIType.DAGSTATS: get_dagstats_functions, APIType.DATASET: get_dataset_functions, APIType.EVENTLOG: get_eventlog_functions, APIType.IMPORTERROR: get_importerror_functions, APIType.MONITORING: get_monitoring_functions, APIType.PLUGIN: get_plugin_functions, APIType.POOL: get_pool_functions, APIType.PROVIDER: get_provider_functions, APIType.TASKINSTANCE: get_taskinstance_functions, APIType.VARIABLE: get_variable_functions, APIType.XCOM: get_xcom_functions, }
- src/main.py:90-91 (registration)The loop in main() that actually calls app.add_tool for each function from get_all_functions(), registering 'get_tasks' with its name and description in the MCP app.for func, name, description, *_ in functions: app.add_tool(func, name=name, description=description)