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MCP Server Airflow Token

get_dag

Retrieve a specific Directed Acyclic Graph (DAG) from Apache Airflow by providing its unique identifier, enabling programmatic access to workflow definitions and configurations.

Instructions

Get a DAG by ID

Input Schema

NameRequiredDescriptionDefault
dag_idYes

Input Schema (JSON Schema)

{ "properties": { "dag_id": { "title": "Dag Id", "type": "string" } }, "required": [ "dag_id" ], "type": "object" }

Implementation Reference

  • The core handler function implementing the 'get_dag' tool logic. Fetches DAG details from Airflow API, enhances with UI URL, and formats as MCP TextContent.
    async def get_dag(dag_id: str) -> List[Union[types.TextContent, types.ImageContent, types.EmbeddedResource]]: response = dag_api.get_dag(dag_id=dag_id) # Convert response to dictionary for easier manipulation response_dict = response.to_dict() # Add UI link to DAG response_dict["ui_url"] = get_dag_url(dag_id) return [types.TextContent(type="text", text=str(response_dict))]
  • Local registration tuple for 'get_dag' tool within the list returned by get_all_functions(), which is imported and used in main.py to register 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:90-92 (registration)
    Global registration loop in main.py where functions from get_all_functions() (including get_dag) are added to the MCP app using app.add_tool().
    for func, name, description, *_ in functions: app.add_tool(func, name=name, description=description)
  • Helper function to generate the UI URL for a DAG, which is added to the response in the get_dag handler.
    def get_dag_url(dag_id: str) -> str: return f"{AIRFLOW_HOST}/dags/{dag_id}/grid"
  • Initialization of the Airflow DAGApi client used by the get_dag handler to fetch DAG data.
    dag_api = DAGApi(api_client)

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