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MCP Server for Apache Airflow

by yangkyeongmo
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Python
Remote

get_dag_dataset_queued_events

Retrieve queued Dataset events for a specific DAG in Apache Airflow to monitor data dependencies and trigger status.

Instructions

Get queued Dataset events for a DAG

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
dag_idYes

Implementation Reference

  • src/airflow/dataset.py:128-132 (handler)
    The handler function that implements the get_dag_dataset_queued_events tool by calling the Airflow DatasetApi and formatting the response.
    async def get_dag_dataset_queued_events(
    dag_id: str,
) -> List[Union[types.TextContent, types.ImageContent, types.EmbeddedResource]]:
    response = dataset_api.get_dag_dataset_queued_events(dag_id=dag_id)
    return [types.TextContent(type="text", text=str(response.to_dict()))]
  • src/airflow/dataset.py:19-19 (registration)
    Registration of the get_dag_dataset_queued_events tool in the get_all_functions list used for MCP tool registration.
    (get_dag_dataset_queued_events, "get_dag_dataset_queued_events", "Get queued Dataset events for a DAG", True),

Tool Definition Quality

C2.8/5.0
Behavior2/5

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

No annotations are provided, so the description carries the full burden. It states 'Get' implies a read operation, but does not disclose behavioral traits such as whether it returns all queued events, pagination, error handling, or if it requires specific permissions. This is inadequate for a tool with no 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 a single, efficient sentence that is front-loaded and wastes no words. It directly conveys the core purpose without unnecessary elaboration, making it highly concise and well-structured.

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 complexity (a read operation with one parameter), no annotations, no output schema, and 0% schema coverage, the description is incomplete. It lacks details on return values, error conditions, and usage context, which are essential for effective tool invocation in this environment.

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

Parameters2/5

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

Schema description coverage is 0%, so the description must compensate. It does not add any meaning beyond the input schema, which only shows 'dag_id' as a required string. No details on format, constraints, or examples are provided, leaving parameters poorly documented.

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 ('Get') and the resource ('queued Dataset events for a DAG'), which is specific and unambiguous. However, it does not explicitly differentiate from sibling tools like 'get_dag_dataset_queued_event' (singular) or 'get_dataset_queued_events' (general), leaving some ambiguity about scope.

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. For example, it does not specify if this is for monitoring queued events, debugging, or how it differs from 'get_dag_dataset_queued_event' (singular) or 'delete_dag_dataset_queued_events'. The description lacks context for selection among siblings.

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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