Skip to main content
Glama
nikhil-ganage

MCP Server Airflow Token

pause_dag

Pause an Airflow DAG to temporarily halt its scheduled runs and task execution. Use this tool to suspend workflow automation for maintenance or debugging.

Instructions

Pause a DAG by ID

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
dag_idYes

Implementation Reference

  • The core handler function for the 'pause_dag' tool. It patches the specified DAG via the Airflow API to set 'is_paused' to True and returns the response.
    async def pause_dag(dag_id: str) -> List[Union[types.TextContent, types.ImageContent, types.EmbeddedResource]]:
        response = dag_api.patch_dag(dag_id=dag_id, dag_update_request={"is_paused": True})
        return [types.TextContent(type="text", text=str(response.to_dict()))]
  • Module-level function that lists all tools in the DAG module, including the registration tuple for 'pause_dag' which provides the tool name, description, and read-only flag.
    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),
        ]
Behavior2/5

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

With no annotations provided, the description carries full burden but offers minimal behavioral insight. It implies a state change (pausing) but doesn't disclose effects (e.g., halts executions, retains history), permissions needed, error conditions (e.g., invalid ID), or response format. For a mutation tool with zero annotation coverage, this leaves critical gaps in understanding its behavior.

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 a single, direct sentence with zero wasted words. It front-loads the core action and resource efficiently, making it easy to parse. Every word earns its place, adhering to ideal conciseness for a simple tool.

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

Completeness2/5

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

Given the tool's complexity (a mutation with no annotations, no output schema, and 0% schema coverage), the description is insufficiently complete. It lacks details on behavior, outcomes, error handling, and usage context, leaving the agent with inadequate information to invoke it correctly beyond the basic action.

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

Parameters3/5

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

The description adds no parameter details beyond the schema, which has 0% description coverage. It mentions 'by ID' but doesn't explain what 'dag_id' represents (e.g., a string identifier) or provide examples. With one parameter and low schema coverage, the description fails to compensate, resulting in a baseline score due to the minimal parameter count.

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

Purpose4/5

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

The description clearly states the action ('Pause') and target resource ('a DAG by ID'), making the purpose immediately understandable. It distinguishes from siblings like 'unpause_dag' by specifying the opposite action, though it doesn't explicitly differentiate from other DAG-related tools like 'delete_dag' or 'patch_dag' beyond the verb itself.

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

Usage Guidelines2/5

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. It doesn't mention prerequisites (e.g., DAG must be running), exclusions (e.g., cannot pause if already paused), or comparisons to siblings like 'unpause_dag' or 'set_task_instances_state'. The description solely states what it does without contextual usage advice.

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

Install Server

Other Tools

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