# MCP Server for Apache Airflow

> Use this tool when you need to automate and manage Apache Airflow workflows, monitor DAG runs, and control tasks programmatically. It provides integration with Airflow's REST API, allowing AI assistants to interact with workflows and retrieve or send data as inputs and outputs. Ideal for automating workflow management, monitoring, and optimization in data pipeline and workflow orchestration contexts.

Canonical page: https://skillsregistry.net/skills/tomnagengast-mcp-server-airflow  
JSON: https://api.skillsregistry.net/v1/skills/tomnagengast-mcp-server-airflow

## Description

Provides integration with Apache Airflow's REST API, allowing AI assistants to programmatically interact with Airflow workflows, monitor DAG runs, and manage tasks.

## Trust

- **Trust score (0–1):** 0.60
- **Verification tier:** unverified

## Facts

- **Version:** 1.0.0
- **Skill type:** atomic
- **Execution layer:** mcp-remote
- **Runtime environment:** api
- **Category:** monitoring
- **Updated:** 2026-05-05

## Source

- **Source listing:** [Glama](https://glama.ai/mcp/servers/ck0imwnxcm)
- **Repository:** <https://github.com/tomnagengast/mcp-server-airflow>

## Use it

Resolve this record through the SkillsRegistry MCP server (no auth, read-only):

```
claude mcp add --transport http --scope user skillsregistry https://api.skillsregistry.net/mcp
```

```json
{
  "jsonrpc": "2.0",
  "id": 1,
  "method": "tools/call",
  "params": {
    "name": "get_skill",
    "arguments": {
      "slug": "tomnagengast-mcp-server-airflow"
    }
  }
}
```

REST: `GET https://api.skillsregistry.net/v1/skills/tomnagengast-mcp-server-airflow` · pull for local use: `GET https://api.skillsregistry.net/v1/skills/tomnagengast-mcp-server-airflow/pull`

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