Airflow

MCP server that exposes Apache Airflow REST API operations as tools. Built with FastMCP.

Install

# Run directly with uvx (no install needed)
uvx mcp-airflow

# Or install with pip
pip install mcp-airflow

For development:

uv pip install -e ".[dev]"
# or with dependency groups
uv sync --group dev

Configuration

Set these environment variables (or create a .env file from .env.example):

Variable	Description	Example
AIRFLOW_BASE_URL	Airflow REST API base URL. Use /api/v2 for Airflow 3.x or /api/v1 for 2.x	http://100.x.x.x:8080/api/v2
AIRFLOW_USERNAME	Auth username (JWT on 3.x, basic auth on 2.x)	admin
AIRFLOW_PASSWORD	Auth password

Authentication

The client picks the auth scheme automatically based on your Airflow version:

• Airflow 3.x (JWT) — a JWT token is obtained from the /auth/token endpoint using AIRFLOW_USERNAME/AIRFLOW_PASSWORD, sent as a Bearer token, and refreshed automatically. Point AIRFLOW_BASE_URL at /api/v2.
• Airflow 2.x (basic auth) — if the JWT flow is unavailable, the client falls back to HTTP basic auth with the same username/password. Point AIRFLOW_BASE_URL at /api/v1.

Usage

Run the server:

mcp-airflow

Or add to your MCP client config (e.g., Claude Desktop):

{
  "mcpServers": {
    "airflow": {
      "command": "mcp-airflow",
      "env": {
        "AIRFLOW_BASE_URL": "http://100.x.x.x:8080/api/v2",
        "AIRFLOW_USERNAME": "admin",
        "AIRFLOW_PASSWORD": "your-password"
      }
    }
  }
}

Tools

Tool	Description
list_dags	List all DAGs with paused/active status
get_dag_runs_today	Get all DAG runs from today with status
get_dag_run_status	Get the latest run status for a specific DAG
trigger_dag_run	Trigger a manual DAG run
get_task_instances	Get task instances for a specific DAG run
check_failed_dags	Check for failed DAGs in the last 24 hours
check_scheduler_health	Check scheduler heartbeat and metadatabase status

Tests

pytest

License

MIT