Manage Apache Airflow DAGs, runs, tasks, variables, connections, pools, and XComs through MCP.
Copy the AI prompt to install this server into Claude Code, Cursor, or another agent โ or use 1-click editor setup below.
We haven't yet run this listing's install command through our automated sandbox check. This isn't a red flag โ we're steadily working through the catalog.
๐ก Paste the JSON block into your client's configuration file under mcpServers, then restart the application.
Inspect callable tools, capabilities, and parameters exposed to AI agents by MCP Server Apache Airflow.
yangkyeongmo@/mcp-server-apache-airflow provides an MCP interface over Apache Airflow's REST API. It is intended for MCP clients that need to work with Airflow objects through standardized tool calls rather than constructing HTTP requests themselves. The implementation uses Apache Airflow's official client library.
The supported resource areas include DAG definitions, DAG runs, task metadata and instances, Airflow variables, connections, pools, and XCom entries. The feature table also lists dataset operations, including listing datasets, although the supplied excerpt ends before the complete dataset section is shown.
The server translates MCP requests into operations against Airflow REST API endpoints under /api/v1. Read operations can retrieve DAGs, run details, task information, logs, variables, connections, pools, XCom entries, and related resources. Write operations cover actions such as pausing or unpausing DAGs, creating or updating DAG runs, changing task states, managing variables and connections, and modifying pools.
The API mapping follows Airflow resource paths. For example, DAG operations use /api/v1/dags, DAG-run operations use paths beneath a DAG identifier, and task-instance operations use paths beneath a specific run and task. The implementation also includes operations for clearing runs or task instances, reparsing a DAG source, testing a connection, and setting a DAG-run note.
The documented capabilities cover:
These operations include both monitoring-oriented access and mutating actions. Agents using the server may therefore need permissions appropriate to the Airflow actions they are allowed to perform.
yangkyeongmo@/mcp-server-apache-airflow is described as an Airflow REST API wrapper, so its usable scope depends on the API and permissions available from the target Airflow deployment. The material does not specify an Airflow version matrix, authentication method, required environment variables, transport configuration, or a command for launching the package.
The feature table marks the listed endpoints as implemented, but it does not document request schemas, response formats, pagination behavior, error handling, or permission requirements for individual operations. Review the target Airflow deployment and the project's current source before enabling write operations in an automated agent workflow.
Factual signals from GitHub, npm, and our automated checks โ not a rating.
No reviews yet โ be the first to share how this listing worked for you.
Showcase your server listing on GitHub or your project documentation. Embed this dynamic SVG badge to highlight official listing status and live engagement.
[](https://allmcps.com/mcp/yangkyeongmo-mcp-server-apache-airflow)<a href="https://allmcps.com/mcp/yangkyeongmo-mcp-server-apache-airflow"><img src="https://allmcps.com/api/badge/yangkyeongmo-mcp-server-apache-airflow?style=directory" alt="MCP Server Apache Airflow on AllMCPs" /></a>