Airflow + fast-agent: Complete MCP Integration
Airflow is a MCP server that A MCP Server that connects to Apache Airflow using official python client..
When integrated with fast-agent, 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 fast-agent, 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 fast-agent
- 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
- fast-agent installed and configured
- Compatible operating system (Node.js, Cross-platform, Edge Environments)
Installation
Step 1: Install Airflow
Configuration
Step 2: Configure fast-agent
- Open fast-agent 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 fast-agent:
Pipeline Monitoring
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Ask fast-agent: "Check status of all DAGs and recent failures"
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Manual DAG Execution
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Ask fast-agent: "Trigger monthly_report DAG with date parameter"
Expected Result: undefined
Troubleshooting Failed Tasks
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Ask fast-agent: "Show failed tasks in data_pipeline and their error logs"
Expected Result: undefined
Testing Your Setup
- Launch fast-agent
- Verify Airflow is available in the tools list
- Test basic Airflow functionality
Troubleshooting
Common Issues
Poor Performance
Symptoms: Slow startup, High memory usage, Slow tool execution
Cause: Suboptimal configuration or resource constraints
Solution:
- Tune concurrency and pool size settings
- Optimize MCP server performance
- Check system resources and limits
- Profile application for bottlenecks
Agent Crashes Under Load
Symptoms: Out of memory errors, Process crashes
Cause: Resource limits exceeded
Solution:
- Reduce concurrency limits
- Increase memory limits if possible
- Implement graceful degradation
- Monitor resource usage patterns
MCP Server Timeouts
Symptoms: Tool execution timeouts, Connection errors
Cause: Server overload or network issues
Solution:
- Increase timeout values
- Implement retry logic
- Scale MCP server infrastructure
- Use connection pooling and caching
Airflow not appearing in fast-agent
Symptoms: Server not listed, Tools not available
Cause: Configuration or installation issue
Solution:
- Verify configuration syntax
- Check Airflow installation
- Restart fast-agent
- Check logs for error messages
Next Steps
Now that Airflow is integrated with fast-agent:
- Explore all Airflow capabilities through fast-agent
- Check out other MCP servers that work with fast-agent
- Join the MCP community for tips and support
- Consider contributing to Airflow development
Need Help?
- Search for Airflow documentation
- Check the fast-agent MCP guide
- Join the MCP community discussions