# MCP-Airflow-API

> Use this tool when you need to manage Apache Airflow workflows using natural language commands, enabling efficient DAG monitoring, task control, and configuration. It solves problems of workflow orchestration and automation, providing a user-friendly interface for inputs and outputs via the Model Context Protocol. Ideal for use cases requiring simplified workflow management and automation, such as data pipeline monitoring and task scheduling.

Canonical page: https://skillsregistry.net/skills/fastmcp-me-mcp-airflow-api  
JSON: https://api.skillsregistry.net/v1/skills/fastmcp-me-mcp-airflow-api

## Description

Enables natural language management of Apache Airflow workflows, including DAG monitoring, task control, and configuration, via the Model Context Protocol.

## Trust

- **Trust score (0–1):** 0.78
- **Verification tier:** verified
- **Last scanned:** 2026-09-28

## Facts

- **Version:** 1.0.0
- **Skill type:** atomic
- **Execution layer:** mcp-remote
- **Runtime environment:** api
- **Category:** monitoring
- **Updated:** 2026-09-28

## Source

- **Source listing:** [Glama](https://glama.ai/mcp/servers/kshj6kspw1)
- **Repository:** <https://github.com/fastmcp-me/mcp-airflow-api>

## 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": "fastmcp-me-mcp-airflow-api"
    }
  }
}
```

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

---
SkillsRegistry indexes agent skills from public registries and GitHub. Skills we have analysed are scanned with Circle-IR and scored on six dimensions; each listing states its scan coverage. More: https://skillsregistry.net/llms.txt