mcp-server-apache-airflow

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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]