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MCP-Airflow-API

MCP-Airflow-API

by fastmcp-me
OverviewSchemaSourceRelated ServersDiscussionsAdmin
Python
Remote

failed_dags

List recently failed DAG runs in Airflow to detect and troubleshoot workflow problems.

Instructions

[Tool Role]: Lists all recently failed DAG runs in the Airflow cluster.

Tool call template

This tool declares no required parameters. Add optional parameters from the input schema as needed.

{
  "id": 1,
  "jsonrpc": "2.0",
  "method": "tools/call",
  "params": {
    "arguments": {},
    "name": "failed_dags"
  }
}

Input Schema

NameRequiredDescriptionDefault

No arguments

Output Schema

NameRequiredDescriptionDefault

No arguments

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv0.0.0

TDQS

A3.7/5.0
Behavior3/5

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

With no annotations, the description carries the burden of behavioral disclosure. It states the core behavior (listing failed runs) and the 'recently' filter, implying a read operation. However, it does not define the time window, mention limits, or explicitly confirm read-only semantics. It adds moderate context but leaves key details undefined.

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, front-loaded sentence with no filler. It is immediately clear and efficiently communicates the tool's purpose.

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?

The tool is simple, has no parameters, and an output schema exists, so return structure is covered. However, the term 'recently' is ambiguous and not defined, leaving the time window unclear. An agent may not know whether this returns the last hour, day, or all failed runs ever. This gap makes it adequate but incomplete.

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

Parameters4/5

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

There are zero parameters, and the schema reflects this with an empty object. The description correctly implies no input is needed. Baseline 4 applies since there are no parameters to describe.

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 the tool's function: 'Lists all recently failed DAG runs in the Airflow cluster.' It uses a specific verb ('Lists') and resource ('failed DAG runs'), and the 'recently' qualifier plus cluster scope help distinguish it from siblings like running_dags or list_dags.

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. The description does not mention other tools, prerequisites, or exclusions. An agent would have to infer from the name that this is for failed runs, but no explicit usage context is given.

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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