MCP-Airflow-API

get_dag

Retrieve detailed information for a specific Airflow DAG by supplying its DAG ID. Returns complete DAG details to support monitoring and configuration.

Instructions

[Tool Role]: Retrieves detailed information for a specific DAG.

Args: dag_id: The DAG ID to get details for

Returns: Comprehensive DAG details

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>"
    },
    "name": "get_dag"
  }
}

Input Schema

Name	Required	Description	Default
`dag_id`	Yes

Output Schema

Name	Required	Description	Default
No arguments

Schema Changelog

Changes observed during successful MCP inspections.

First observedv0.0.0Jul 31, 2026

TDQS

C2.8/5.0

Behavior2/5

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

With no annotations, the description is the only source of behavioral transparency. It uses 'Retrieves,' implying read-only, but does not disclose permissions, error behavior, or side-effect safety. No additional behavioral traits beyond the basic getter are described.

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?

The description is concise, with a clear first sentence and standard Args/Returns structure. The Returns line ('Comprehensive DAG details') is somewhat vague but does not add excessive length.

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

Completeness3/5

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

For a simple one-parameter getter with an output schema, the description provides the essential purpose and parameter. However, it lacks disambiguation from numerous sibling DAG tools and provides no context about read-only safety or when to choose this over alternatives.

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?

The Args section repeats the parameter name and basic description ('The DAG ID to get details for'), which adds no meaning beyond the schema's type and title. Schema description coverage is 0%, and the description does not compensate with examples, formats, or constraints.

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 states 'Retrieves detailed information for a specific DAG,' using a specific verb and resource. It distinguishes from list_dags (list) and get_dags_detailed_batch (batch) by implying single DAG scope, though it does not explicitly name alternatives.

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?

The description provides no guidance on when to use this tool versus alternatives like get_dags_detailed_batch or dag_graph. It only states what the tool does, leaving the agent to infer usage.

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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