Skip to main content
Glama
astronomer

astro-airflow-mcp

Official
by astronomer

diagnose_dag_run

Diagnose issues in a specific DAG run by retrieving run details and identifying failed tasks for troubleshooting.

Instructions

Diagnose issues with a specific DAG run - get run details and failed tasks.

USE THIS TOOL WHEN troubleshooting a failed or problematic DAG run. Returns all the information you need to understand what went wrong.

This is the preferred tool when:

  • User asks "Why did this DAG run fail?"

  • User asks "What's wrong with run X?"

  • You need to investigate task failures in a specific run

Returns combined data:

  • DAG run metadata (state, start/end times, trigger type)

  • All task instances for this run with their states

  • Highlighted failed/upstream_failed tasks with details

  • Summary of task states

Args: dag_id: The ID of the DAG dag_run_id: The ID of the DAG run (e.g., "manual__2024-01-01T00:00:00+00:00")

Returns: JSON with diagnostic information about the DAG run

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
dag_idYes
dag_run_idYes

Latest Blog Posts

MCP directory API

We provide all the information about MCP servers via our MCP API.

curl -X GET 'https://glama.ai/api/mcp/v1/servers/astronomer/astro-airflow-mcp'

If you have feedback or need assistance with the MCP directory API, please join our Discord server