Skip to main content
Glama

MCP Server Airflow Token

delete_dag

Remove a Directed Acyclic Graph (DAG) from Apache Airflow to clean up workflows and manage Airflow deployments.

Instructions

Delete a DAG

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 main handler function for the 'delete_dag' tool. It takes a dag_id parameter, calls the Airflow DAG API to delete the DAG, and returns a TextContent response.
    async def delete_dag(dag_id: str) -> List[Union[types.TextContent, types.ImageContent, types.EmbeddedResource]]: response = dag_api.delete_dag(dag_id=dag_id) return [types.TextContent(type="text", text=str(response.to_dict()))]
  • Local registration list within the DAG module that includes the delete_dag tool tuple: (delete_dag, "delete_dag", "Delete a DAG", False). This list is imported and used in main.py for final 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), ]
  • src/main.py:78-98 (registration)
    Top-level registration loop in main.py that imports get_dag_functions from dag.py (line 7) and calls app.add_tool for each tool, including delete_dag.
    for api in apis: logging.debug(f"Adding API: {api}") get_function = APITYPE_TO_FUNCTIONS[APIType(api)] try: functions = get_function() except NotImplementedError: continue # Filter functions for read-only mode if requested if read_only: functions = filter_functions_for_read_only(functions) for func, name, description, *_ in functions: app.add_tool(func, name=name, description=description) if transport == "sse": logging.debug("Starting MCP server for Apache Airflow with SSE transport") app.run(transport="sse") else: logging.debug("Starting MCP server for Apache Airflow with stdio transport") app.run(transport="stdio")

Latest Blog Posts

MCP directory API

We provide all the information about MCP servers via our MCP API.

curl -X GET 'https://glama.ai/api/mcp/v1/servers/nikhil-ganage/mcp-server-airflow-token'

If you have feedback or need assistance with the MCP directory API, please join our Discord server