What is the Apache Airflow MCP server?

Apache Airflow is a Model Context Protocol (MCP) server profile on explainx.ai. MCP lets AI hosts (e.g. Claude Desktop, Cursor) call tools and resources through a standard interface; this page summarizes categories, install hints, and community ratings.

How do MCP servers relate to agent skills?

Skills are reusable instruction packages (often SKILL.md); MCP servers expose live capabilities. Teams frequently combine both—skills for workflows, MCP for APIs and data. See explainx.ai/skills and explainx.ai/mcp-servers for parallel directories.

How are reviews shown for Apache Airflow?

This profile displays 10 aggregated ratings (sample rows for discoverability plus signed-in user reviews). Average score is about 4.5 out of 5—verify behavior in your own environment before production use.

Apache Airflow▌

by yangkyeongmo

Manage and monitor workflows using Apache Airflow. Streamline workflow automation software and enable automated approval

Provides a bridge to Apache Airflow for managing and monitoring workflows through natural language, enabling DAG management, task execution, and resource administration without leaving your assistant interface.

github stars

★ 144

GitHub npm

Natural language workflow managementSupports Airflow API v1 and v2Complete REST API coverage

best for

/ Data engineers managing Airflow workflows
/ DevOps teams monitoring pipeline health
/ Analysts accessing workflow performance data
/ Teams wanting natural language Airflow control

capabilities

/ Manage DAG operations and lifecycle
/ Monitor task execution and status
/ Access XCom data between tasks
/ Control connection pools and variables
/ Track performance analytics and logs
/ Handle import errors and debugging

what it does

Connects to Apache Airflow clusters via REST API to let you manage workflows, monitor tasks, and access performance data using natural language commands instead of complex API calls.

about

Apache Airflow is a community-built MCP server published by yangkyeongmo that provides AI assistants with tools and capabilities via the Model Context Protocol. Manage and monitor workflows using Apache Airflow. Streamline workflow automation software and enable automated approval

how to install

You can install Apache Airflow in your AI client of choice. Use the install panel on this page to get one-click setup for Cursor, Claude Desktop, VS Code, and other MCP-compatible clients. This server runs locally on your machine via the stdio transport.

license

MIT

Apache Airflow is released under the MIT license. This is a permissive open-source license, meaning you can freely use, modify, and distribute the software.

readme

README content is unavailable from source data for this server.

Open GitHub repository

FAQ

What is the Apache Airflow MCP server?: Apache Airflow is a Model Context Protocol (MCP) server profile on explainx.ai. MCP lets AI hosts (e.g. Claude Desktop, Cursor) call tools and resources through a standard interface; this page summarizes categories, install hints, and community ratings.
How do MCP servers relate to agent skills?: Skills are reusable instruction packages (often SKILL.md); MCP servers expose live capabilities. Teams frequently combine both—skills for workflows, MCP for APIs and data. See explainx.ai/skills and explainx.ai/mcp-servers for parallel directories.
How are reviews shown for Apache Airflow?: This profile displays 10 aggregated ratings (sample rows for discoverability plus signed-in user reviews). Average score is about 4.5 out of 5—verify behavior in your own environment before production use.

MCP server reviews

Ratings

4.5★★★★★10 reviews

★★★★★Shikha Mishra· Oct 10, 2024
Apache Airflow is among the better-indexed MCP projects we tried; the explainx.ai summary tracks the official description.
★★★★★Piyush G· Sep 9, 2024
We evaluated Apache Airflow against two servers with overlapping tools; this profile had the clearer scope statement.
★★★★★Chaitanya Patil· Aug 8, 2024
Useful MCP listing: Apache Airflow is the kind of server we cite when onboarding engineers to host + tool permissions.
★★★★★Sakshi Patil· Jul 7, 2024
Apache Airflow reduced integration guesswork — categories and install configs on the listing matched the upstream repo.
★★★★★Ganesh Mohane· Jun 6, 2024
I recommend Apache Airflow for teams standardizing on MCP; the explainx.ai page compares cleanly with sibling servers.
★★★★★Oshnikdeep· May 5, 2024
Strong directory entry: Apache Airflow surfaces stars and publisher context so we could sanity-check maintenance before adopting.
★★★★★Dhruvi Jain· Apr 4, 2024
Apache Airflow has been reliable for tool-calling workflows; the MCP profile page is a good permalink for internal docs.
★★★★★Rahul Santra· Mar 3, 2024
According to our notes, Apache Airflow benefits from clear Model Context Protocol framing — fewer ambiguous “AI plugin” claims.
★★★★★Pratham Ware· Feb 2, 2024
We wired Apache Airflow into a staging workspace; the listing’s GitHub and npm pointers saved time versus hunting across READMEs.
★★★★★Yash Thakker· Jan 1, 2024
Apache Airflow is a well-scoped MCP server in the explainx.ai directory — install snippets and categories matched our Claude Code setup.