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MCP Server for Apache Airflow

by yangkyeongmo

patch_dag

Modify Apache Airflow DAG configurations by updating pause status or tags to manage workflow execution.

Instructions

Update a DAG

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
dag_idYes
is_pausedNo
tagsNo

Implementation Reference

  • The core handler function for the 'patch_dag' tool. It constructs a DAG update request based on provided is_paused and/or tags parameters, then calls the Airflow DAG API to apply the partial update.
    async def patch_dag(
        dag_id: str, 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)
    
        response = dag_api.patch_dag(dag_id=dag_id, dag=dag, update_mask=update_mask)
        return [types.TextContent(type="text", text=str(response.to_dict()))]
  • The get_all_functions() in dag.py lists all DAG-related tools for registration, including the 'patch_dag' tool with name 'patch_dag', description 'Update a DAG', marked as non-read-only (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:95-97 (registration)
    The generic tool registration loop in main.py that adds all functions from imported get_all_functions() lists (including dag.py's patch_dag) as MCP tools using fastmcp's Tool.from_function.
    for func, name, description, *_ in functions:
        app.add_tool(Tool.from_function(func, name=name, description=description))
Behavior1/5

Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

No annotations are provided, so the description carries full burden for behavioral disclosure. 'Update a DAG' implies a mutation operation but provides no information about permissions required, whether changes are reversible, what happens to unspecified fields, error conditions, or response format. This is inadequate for a mutation tool with zero annotation coverage.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness5/5

Is the description appropriately sized, front-loaded, and free of redundancy?

The description is maximally concise with just three words. While severely under-specified, it contains zero wasted words and is front-loaded with the core action. This meets the criteria for perfect conciseness despite the content deficiencies.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness1/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

For a mutation tool with 3 parameters, 0% schema description coverage, no annotations, and no output schema, the description is completely inadequate. It doesn't explain what DAGs are, what fields can be updated, the operation's behavior, or what to expect in return. Given the complexity implied by the sibling tools list, this description fails to provide necessary context.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters1/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Schema description coverage is 0%, meaning none of the three parameters (dag_id, is_paused, tags) are documented in the schema. The description provides absolutely no information about these parameters - not what they represent, their formats, constraints, or how they affect the update operation. This fails to compensate for the complete lack of schema documentation.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Purpose2/5

Does the description clearly state what the tool does and how it differs from similar tools?

The description 'Update a DAG' is a tautology that merely restates the tool name 'patch_dag' without adding specificity. It doesn't clarify what aspects of a DAG are updated, how this differs from other DAG-related tools like 'pause_dag' or 'unpause_dag', or what 'DAG' refers to in this context.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines1/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

No guidance is provided on when to use this tool versus alternatives. With multiple sibling tools like 'pause_dag', 'unpause_dag', 'delete_dag', and 'patch_dags', the description offers no indication of when this specific DAG update tool is appropriate versus those other operations.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

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