mcp-airflow
Allows interaction with Apache Airflow REST API, providing tools to list DAGs, get DAG runs, trigger runs, check task instances, and monitor scheduler health.
mcp-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-airflowFor development:
uv pip install -e ".[dev]"
# or with dependency groups
uv sync --group devConfiguration
Set these environment variables (or create a .env file from .env.example):
Variable | Description | Example |
| Airflow REST API base URL. Use |
|
| Auth username (JWT on 3.x, basic auth on 2.x) |
|
| 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/tokenendpoint usingAIRFLOW_USERNAME/AIRFLOW_PASSWORD, sent as aBearertoken, and refreshed automatically. PointAIRFLOW_BASE_URLat/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_URLat/api/v1.
Usage
Run the server:
mcp-airflowOr 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 all DAGs with paused/active status |
| Get all DAG runs from today with status |
| Get the latest run status for a specific DAG |
| Trigger a manual DAG run |
| Get task instances for a specific DAG run |
| Check for failed DAGs in the last 24 hours |
| Check scheduler heartbeat and metadatabase status |
Tests
pytestLicense
MIT
Maintenance
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