MCP-Airflow-API

running_dags

List all currently running DAG runs in your Airflow cluster to monitor active workflows and troubleshoot issues.

Instructions

[Tool Role]: Lists all currently running 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": "running_dags"
  }
}

Input Schema

Name	Required	Description	Default
No arguments

Output Schema

Name	Required	Description	Default
No arguments

Schema Changelog

Changes observed during successful MCP inspections.

First observedv0.0.0Jul 31, 2026

TDQS

A4.3/5.0

Behavior3/5

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

With no annotations provided, the description carries full burden. It discloses that the tool filters to 'currently running' DAG runs and returns a list, but it does not mention potential pagination, permission requirements, or empty-list behavior. The description adds the running-status filter, which is useful, but lacks deeper behavioral detail expected for a tool with no annotation safety signals.

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 sentence that is front-loaded with the action ('Lists') and immediately specifies the resource and scope. Every word earns its place, with no redundancy or filler.

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

Completeness5/5

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

Given the tool has no parameters and an output schema is present, the description adequately covers the core purpose and scope. It clearly identifies what is being listed (running DAG runs) and in what context (Airflow cluster), making it complete for this simple tool.

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?

The tool has zero parameters, so there is no schema to compensate. According to the baseline rule for 0 params, the description already provides sufficient meaning through its clear statement of what the tool lists, making extra parameter explanation unnecessary.

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 currently running DAG runs in the Airflow cluster.' It uses a specific verb ('Lists'), identifies the resource ('DAG runs'), and adds a scope filter ('currently running'), which distinguishes it from sibling tools like list_dags or failed_dags.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines4/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

The description gives clear context that this tool is for retrieving currently running DAG runs, implying when it should be used versus historical or failed runs. However, it does not explicitly mention alternatives or when not to use it, so it stops short of full exclusions.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

Deploy Server