Apache Airflow
Provides a bridge to Apache Airflow for managing and monitoring workflows through natural language, enabling DAG management, task
MCP-Server-Apache-Airflow provides a bridge between AI assistants and Apache Airflow, enabling management and monitoring of workflows through natural language. Developed by Gyeongmo Yang, this Python-based server exposes a comprehensive set of Airflow API endpoints including DAG management, task instances, variables, connections, and monitoring capabilities. The implementation supports both stdio and SSE transport modes, authenticates with Airflow via username/password, and returns responses as structured text content. This server is particularly valuable for data engineers and workflow administrators who need to trigger DAG runs, check execution status, or manage Airflow resources without leaving their AI assistant interface.
Source
Repository: https://github.com/yangkyeongmo/mcp-server-apache-airflow
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