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MCP Server for Apache Airflow

by yangkyeongmo
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Python
Remote

get_dag_dataset_queued_event

Retrieve queued Dataset events for Apache Airflow DAGs to monitor dataset-triggered workflow status and identify pending executions.

Instructions

Get a queued Dataset event for a DAG

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
dag_idYes
uriYes

Implementation Reference

  • src/airflow/dataset.py:120-125 (handler)
    The main handler function that executes the tool: fetches the queued dataset event via the dataset_api and formats the response as TextContent.
    async def get_dag_dataset_queued_event(
    dag_id: str,
    uri: str,
) -> List[Union[types.TextContent, types.ImageContent, types.EmbeddedResource]]:
    response = dataset_api.get_dag_dataset_queued_event(dag_id=dag_id, uri=uri)
    return [types.TextContent(type="text", text=str(response.to_dict()))]
  • src/airflow/dataset.py:18-18 (registration)
    Tool registration entry in the get_all_functions() list, including the function reference, name, description, and read-only flag.
    (get_dag_dataset_queued_event, "get_dag_dataset_queued_event", "Get a queued Dataset event 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 full burden. It states 'Get' implying a read operation, but doesn't disclose behavioral traits like authentication needs, rate limits, error handling, or what 'queued' means operationally. For a tool with no annotation coverage, this leaves significant gaps.

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 with no wasted words. It's front-loaded with the core action and resource, making it easy to parse quickly.

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 no annotations, 0% schema coverage, no output schema, and multiple similar sibling tools, the description is incomplete. It lacks details on behavior, parameter usage, return values, and differentiation from alternatives, making it inadequate for a tool with 2 required parameters.

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 parameters 'dag_id' and 'uri' are undocumented in the schema. The description adds no meaning beyond the tool name, failing to explain what these parameters represent, their format, or how they identify the event. This doesn't compensate for the coverage gap.

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 target resource ('queued Dataset event for a DAG'), making the purpose understandable. However, it doesn't differentiate from sibling tools like 'get_dag_dataset_queued_events' (plural) or 'get_dataset_queued_events', 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. With siblings like 'get_dag_dataset_queued_events' (plural) and 'get_dataset_queued_events', the description lacks context on whether this fetches a single event, how it relates to other get_* tools, or any prerequisites.

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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