The mcp-server-apache-airflow exposes Apache Airflow's DAG management, task execution, and monitoring capabilities to AI agents. It provides tools to create, trigger, and monitor workflows. It connects to Airflow's REST API and metadata database. Developers use it to automate and manage data pipelines, schedule tasks, and integrate Airflow workflows with other AI agents.
The mcp-server-apache-airflow exposes Apache Airflow's DAG management, task execution, and monitoring capabilities to AI agents. It provides tools to create, trigger, and monitor workflows. It connects to Airflow's REST API and metadata database. Developers use it to automate and manage data pipelines, schedule tasks, and integrate Airflow workflows with other AI agents.
pip install mcp-server-apache-airflowAdd this configuration to your claude_desktop_config.json:
{
"mcpServers": {
"yangkyeongmo-mcp-server-apache-airflow-github": {
"command": "uvx",
"args": [
"pip install mcp-server-apache-airflow"
]
}
}
}Restart Claude Desktop, then ask:
"What tools do you have available from apache airflow?"
No configuration required. This server works out of the box.
"What resources are available in apache airflow?"
Claude will query available resources and return a list of what you can access.
"Show me details about [specific item] in apache airflow"
Claude will fetch and display detailed information about the requested item.
"Create a new [item] in apache airflow with [details]"
Claude will use the appropriate tool to create the resource and confirm success.
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