mcp-server-apache-airflow

A Model Context Protocol (MCP) server implementation for Apache Airflow, enabling seamless integration with MCP clients. This project provides a standardized way to interact with Apache Airflow through the Model Context Protocol.

About

This project implements a Model Context Protocol server that wraps Apache Airflow's REST API, allowing MCP clients to interact with Airflow in a standardized way.

Feature Implementation Status

Feature	API Path	Status
DAG Management
List DAGs	/api/v1/dags	✅
Get DAG Details	/api/v1/dags/{dag_id}	✅
Pause DAG	/api/v1/dags/{dag_id}	✅
Unpause DAG	/api/v1/dags/{dag_id}	✅
Update DAG	/api/v1/dags/{dag_id}	❌
Delete DAG	/api/v1/dags/{dag_id}	❌
DAG Runs
List DAG Runs	/api/v1/dags/{dag_id}/dagRuns	✅
Create DAG Run	/api/v1/dags/{dag_id}/dagRuns	✅
Get DAG Run Details	/api/v1/dags/{dag_id}/dagRuns/{dag_run_id}	❌
Update DAG Run	/api/v1/dags/{dag_id}/dagRuns/{dag_run_id}	❌
Delete DAG Run	/api/v1/dags/{dag_id}/dagRuns/{dag_run_id}	❌
Tasks
List DAG Tasks	/api/v1/dags/{dag_id}/tasks	✅
Get Task Details	/api/v1/dags/{dag_id}/tasks/{task_id}	❌
Get Task Instance	/api/v1/dags/{dag_id}/dagRuns/{dag_run_id}/taskInstances/{task_id}	✅
List Task Instances	/api/v1/dags/{dag_id}/dagRuns/{dag_run_id}/taskInstances	✅
Update Task Instance	/api/v1/dags/{dag_id}/dagRuns/{dag_run_id}/taskInstances/{task_id}	❌
System
Get Import Errors	/api/v1/importErrors	✅
Get Import Error Details	/api/v1/importErrors/{import_error_id}	✅
Get Health Status	/api/v1/health	✅
Get Version	/api/v1/version	✅
Variables
List Variables	/api/v1/variables	❌
Create Variable	/api/v1/variables	❌
Get Variable	/api/v1/variables/{variable_key}	❌
Update Variable	/api/v1/variables/{variable_key}	❌
Delete Variable	/api/v1/variables/{variable_key}	❌
Connections
List Connections	/api/v1/connections	❌
Create Connection	/api/v1/connections	❌
Get Connection	/api/v1/connections/{connection_id}	❌
Update Connection	/api/v1/connections/{connection_id}	❌
Delete Connection	/api/v1/connections/{connection_id}	❌

Setup

Environment Variables

Set the following environment variables:

AIRFLOW_HOST=<your-airflow-host>
AIRFLOW_USERNAME=<your-airflow-username>
AIRFLOW_PASSWORD=<your-airflow-password>

Usage with Claude Desktop

Add to your claude_desktop_config.json:

{
  "mcpServers": {
    "mcp-server-apache-airflow": {
      "command": "uvx",
      "args": ["mcp-server-apache-airflow"],
      "env": {
        "AIRFLOW_HOST": "https://your-airflow-host",
        "AIRFLOW_USERNAME": "your-username",
        "AIRFLOW_PASSWORD": "your-password"
      }
    }
  }
}

Alternative configuration using uv:

{
  "mcpServers": {
    "mcp-server-apache-airflow": {
      "command": "uv",
      "args": [
        "--directory",
        "/path/to/mcp-server-apache-airflow",
        "run",
        "mcp-server-apache-airflow"
      ],
      "env": {
        "AIRFLOW_HOST": "https://your-airflow-host",
        "AIRFLOW_USERNAME": "your-username",
        "AIRFLOW_PASSWORD": "your-password"
      }
    }
  }
}

Replace /path/to/mcp-server-apache-airflow with the actual path where you've cloned the repository.

Manual Execution

You can also run the server manually:

python src/server.py

Options:

• --port: Port to listen on for SSE (default: 8000)
• --transport: Transport type (stdio/sse, default: stdio)

Contributing

Contributions are welcome! Please feel free to submit a Pull Request.

License

[Add your license information here]