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MCP Server Apache Airflow

by yangkyeongmo@

Manage Apache Airflow DAGs, runs, tasks, variables, connections, pools, and XComs through MCP.

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Install MCP Server Apache Airflow

Pick your client, then add it in one click or paste the config.

STDIOPython
~/Library/Application Support/Claude/claude_desktop_config.json
claude_desktop_config.json
{
  "mcpServers": {
    "yangkyeongmo-mcp-server-apache-airflow": {
      "command": "uvx",
      "args": [
        "mcp-server-apache-airflow"
      ]
    }
  }
}

Settings → Developer → Edit Config, merge this into mcpServers, then fully quit and reopen Claude Desktop.

Automated check passed— started and listed 68 tools correctly (26d ago).

Overview

yangkyeongmo@/mcp-server-apache-airflow wraps Apache Airflow's REST API for access through MCP clients. It uses the official Apache Airflow client library and exposes operations across DAGs, DAG runs, tasks, variables, connections, pools, and XCom entries. Reach for it when an MCP-compatible agent needs to inspect or modify Airflow resources without calling the REST API directly.

Use cases

  • Inspect DAG definitions and task metadata
  • Monitor DAG runs and task-instance logs
  • Trigger and update Airflow DAG runs
  • Manage Airflow variables, connections, and pools
  • Read XCom values from completed task instances

Key features

  • Wraps Apache Airflow REST API endpoints
  • Uses the official Apache Airflow client library
  • Manages DAGs and DAG runs
  • Inspects and updates tasks and task instances
  • Manages variables, connections, and pools
  • Reads XCom entries and task logs

Tools68

What MCP Server Apache Airflow lets your agent do. Expand a tool for its parameters.

Verified live~6.1k tokens of context

Security & health

What it can reach and how reliably it runs — from our own checks, not the maintainer’s claims.

ActiveLast checked 1d ago

Recent health check succeeded.

7/8 checks healthy over the last 78d

Supply-chain signal

No high-severity advisories surfaced by our automated scan.

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Scanned 14d ago via OSV.dev · mcp-server-apache-airflow (PyPI)

Adoption & maintenance

Factual signals from GitHub, npm, and our automated checks — not a rating.

GitHub stars180Stargazers on the source repository.
Last commit7mo agoMost recent push to the default branch.
Availability100%Our rolling endpoint + install checks that succeeded.
Install checkPassedOur sandbox started it and listed its tools.
Tools exposed68Callable tools this server registers over MCP.
Directory activity6 viewsConfig copies, upvotes, and views on AllMCPs.

How MCP Server Apache Airflow works

What yangkyeongmo@/mcp-server-apache-airflow MCP server does

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.

How it works

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.

Tools and capabilities

The documented capabilities cover:

  • Listing, retrieving, updating, pausing, unpausing, deleting, and batch-patching DAGs.
  • Reading DAG source files and requesting DAG-file reparsing.
  • Listing, creating, updating, deleting, clearing, and inspecting DAG runs.
  • Reading task definitions, task instances, task tries, and task-instance logs.
  • Updating task instances and changing the state of multiple task instances.
  • Creating, reading, updating, and deleting Airflow variables.
  • Creating, reading, updating, deleting, and testing Airflow connections.
  • Creating, reading, updating, and deleting pools.
  • Listing and retrieving XCom entries for a task instance.

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.

Limitations and notes

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.

Read the full README View source on GitHub

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Frequently Asked Questions about MCP Server Apache Airflow

It exposes Apache Airflow REST API operations for DAGs, DAG runs, tasks, variables, connections, pools, XCom entries, and related resources.

The material says it supports MCP clients but does not name Claude Desktop or document a Claude Desktop configuration.

Yes. The documented operations include updating and deleting DAGs and DAG runs, changing task states, and managing variables, connections, and pools.

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