Airflow Integrations
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Enables AI assistants to interact with Apache Airflow workflows, monitor DAG runs, and programmatically manage tasks.
About
Integrates Apache Airflow with AI assistants through the Model Context Protocol, offering tools for DAG management, run monitoring, and comprehensive logging. It supports a wide range of Airflow hosting platforms, allowing AI to trigger workflows, track task instances, and access real-time logs for enhanced debugging and troubleshooting.
Key Features
- Comprehensive Logging: Access and monitor logs for debugging and troubleshooting
- Universal Compatibility: Works with all popular Airflow hosting platforms
- DAG Run Operations: Trigger new runs, list existing runs, and get detailed run information
- DAG Management: List, view details, pause, and unpause DAGs
- Task Instance Monitoring: View task instances and their execution details
- 0 GitHub stars
Use Cases
- Facilitate AI-assisted debugging and troubleshooting through log access.
- Allow AI assistants to trigger and manage Airflow DAGs.
- Enable AI-driven monitoring of Airflow workflow executions.
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