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Airflow MCP

Airflow MCP

by zamax14
OverviewSchemaSourceRelated ServersDiscussionsAdmin
Python
Hybrid

list_dag_runs

Retrieve the history of DAG runs for a specified DAG ID, with optional filtering by state and limit.

Instructions

List DAG run history for a given DAG.

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": "list_dag_runs"
  }
}

Input Schema

NameRequiredDescriptionDefault
limitNo
stateNo
dag_idYes

Output Schema

NameRequiredDescriptionDefault
resultYes

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv0.1.0

TDQS

C2.4/5.0
Behavior2/5

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

With no annotations, the description should disclose behavioral traits. It only says 'list history,' implying read-only, but does not mention pagination, default behavior, or any side effects. Minimal behavioral insight.

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

Conciseness3/5

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

The description is a single sentence, which is concise, but it lacks structure and important details. It earns its place but should be expanded to include param behavior.

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 presence of an output schema and optional parameters, the description is incomplete. It does not explain return values, filtering, or pagination, leaving gaps for effective tool invocation.

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 tool description provides no additional meaning for the parameters (dag_id, limit, state). The agent receives only parameter names and types from the schema, which is insufficient for correct usage.

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 tool lists DAG run history for a given DAG, specifying the verb and resource. It distinguishes from siblings like get_dag_run (which fetches a single run) and list_dags (which lists DAGs), though it does not explicitly mention these distinctions.

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 this tool versus alternatives like get_dag_run or list_task_instances. The description lacks any contextual cues for appropriate selection.

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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