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Airflow MCP

Airflow MCP

by zamax14
OverviewSchemaSourceRelated ServersDiscussionsAdmin
Python
Hybrid

get_dag_run

Retrieve comprehensive details for a specific DAG run, including its trigger configuration. Use this to inspect run status and input parameters.

Instructions

Get details for a single DAG run, including its trigger conf.

Tool call template

Replace each placeholder with a value matching the input schema. Only required parameters are included; add optional parameters as needed.

{
  "id": 1,
  "jsonrpc": "2.0",
  "method": "tools/call",
  "params": {
    "arguments": {
      "dag_id": "<dag_id>",
      "dag_run_id": "<dag_run_id>"
    },
    "name": "get_dag_run"
  }
}

Input Schema

NameRequiredDescriptionDefault
dag_idYes
dag_run_idYes

Output Schema

NameRequiredDescriptionDefault

No arguments

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv0.1.0

TDQS

C2.8/5.0
Behavior2/5

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

No annotations provided, so description must disclose behaviors. It only states the output includes details and trigger conf, but does not mention error handling (e.g., for missing run), idempotency, or that it's a read-only operation.

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

Conciseness4/5

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

Single sentence, efficient, no fluff. However, slightly too terse, missing important details that could be added without losing conciseness.

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 schema descriptions and no annotations, the description should provide more context. Though output schema exists, the description does not mention required inputs or any usage constraints, leaving gaps.

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%, and the description adds no meaning to the two required parameters (dag_id, dag_run_id). Their purpose is only inferred from names.

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

Purpose5/5

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

The description clearly states it gets details for a single DAG run, including trigger conf. This distinguishes it from sibling tools like 'list_dag_runs' (which lists multiple) and 'get_dag' (which gets the DAG definition).

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 on when to use vs alternatives. Does not mention prerequisites, context, or that this tool is for retrieving a specific run after identifying its ID.

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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