Airflow + Goose: Complete MCP Integration
Airflow is a MCP server that A MCP Server that connects to Apache Airflow using official python client..
When integrated with Goose, you can:
- List all available DAGs in Airflow
- Manually trigger a DAG run
- Get DAG run history and status
This guide provides step-by-step instructions to set up Airflow in Goose, including configuration, examples, and troubleshooting.
What You'll Achieve
After completing this setup:
- Airflow will be fully integrated and operational
- You can use Airflow tools directly in Goose
- All Airflow capabilities will be available for your workflows
- Access to 5 different tools
Prerequisites
Before starting, ensure you have:
- Airflow webserver host URL
- Airflow authentication username
- Airflow authentication password
- Goose installed and configured
- Compatible operating system (Python, Cross-platform, IDE Integration)
Installation
Step 1: Install Airflow
Configuration
Step 2: Configure Goose
- Open Goose settings
- Navigate to MCP server configuration
- Add Airflow server with appropriate settings
- Save and restart if needed
Examples
Once configured, you can use Airflow in Goose:
Pipeline Monitoring
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Ask Goose: "Check status of all DAGs and recent failures"
Expected Result: undefined
Manual DAG Execution
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Ask Goose: "Trigger monthly_report DAG with date parameter"
Expected Result: undefined
Troubleshooting Failed Tasks
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Ask Goose: "Show failed tasks in data_pipeline and their error logs"
Expected Result: undefined
Testing Your Setup
- Launch Goose
- Verify Airflow is available in the tools list
- Test basic Airflow functionality
Troubleshooting
Common Issues
Goose Installation Failed
Symptoms: pip install errors, Missing dependencies
Cause: Python environment or dependency issues
Solution:
- Verify Python 3.8+ is installed
- Use virtual environment for clean installation
- Install with pipx for isolated environment
- Check for conflicting packages
Configuration Not Loading
Symptoms: Config errors, Settings not applied
Cause: YAML syntax or file location issues
Solution:
- Verify YAML syntax in goose.yaml
- Check configuration file location
- Use goose config validate command
- Review configuration documentation
MCP Server Not Starting
Symptoms: Server connection failed, Agent cannot access tools
Cause: Server installation or configuration problems
Solution:
- Verify MCP server installation
- Test server independently before Goose integration
- Check server executable permissions
- Review Goose logs for connection errors
IDE Automation Not Working
Symptoms: Agent not controlling IDE, Automation failures
Cause: IDE integration or permission issues
Solution:
- Install required IDE plugins or extensions
- Check IDE automation permissions
- Verify IDE API access is enabled
- Test with simpler automation tasks first
Airflow not appearing in Goose
Symptoms: Server not listed, Tools not available
Cause: Configuration or installation issue
Solution:
- Verify configuration syntax
- Check Airflow installation
- Restart Goose
- Check logs for error messages
Next Steps
Now that Airflow is integrated with Goose:
- Explore all Airflow capabilities through Goose
- Check out other MCP servers that work with Goose
- Join the MCP community for tips and support
- Consider contributing to Airflow development
Need Help?
- Search for Airflow documentation
- Check the Goose MCP guide
- Join the MCP community discussions