mcp-server-apache-airflow

what is mcp-server-apache-airflow? This project is a Model Context Protocol (MCP) server implementation for Apache Airflow, enabling seamless integration with MCP clients. It provides a standardized way to interact with Apache Airflow through the Model Context Protocol. how to use mcp-server-apache-airflow? To use this project, set the required environment variables for your Airflow instance and configure it in your claude_desktop_config.json or run the server manually using Python. key features of mcp-server-apache-airflow? Standardized API for interacting with Apache Airflow Support for DAG management, including listing, pausing, and unpausing DAGs Ability to create and manage DAG runs Health status and version retrieval use cases of mcp-server-apache-airflow? Integrating Apache Airflow with other systems using the Model Context Protocol. Managing workflows in a standardized manner. Monitoring and controlling DAGs and their runs programmatically. FAQ from mcp-server-apache-airflow? What is the Model Context Protocol? The Model Context Protocol is a standard for interacting with data processing systems like Apache Airflow. How do I set up the server? Set the required environment variables and configure your client as per the provided instructions. Can I contribute to this project? Yes! Contributions are welcome, and you can submit a Pull Request.

As an MCP (Model Context Protocol) server, mcp-server-apache-airflow enables AI agents to communicate effectively through standardized interfaces. The Model Context Protocol simplifies integration between different AI models and agent systems.

To use this project, set the required environment variables for your Airflow instance and configure it in your claude_desktop_config.json or run the server manually using Python. key features of mcp-server-apache-airflow? Standardized API for interacting with Apache Airflow Support for DAG management, including listing, pausing, and unpausing DAGs Ability to create and manage DAG runs Health status and version retrieval use cases of mcp-server-apache-airflow? Integrating Apache Airflow with other systems using the Model Context Protocol. Managing workflows in a standardized manner. Monitoring and controlling DAGs and their runs programmatically. FAQ from mcp-server-apache-airflow? What is the Model Context Protocol? The Model Context Protocol is a standard for interacting with data processing systems like Apache Airflow. How do I set up the server? Set the required environment variables and configure your client as per the provided instructions. Can I contribute to this project? Yes! Contributions are welcome, and you can submit a Pull Request.

Learn how to integrate this MCP server with your AI agents and leverage the Model Context Protocol for enhanced capabilities.