# Airflow MCP

> Use this tool when you need to interact with Apache Airflow using natural language, enabling efficient querying of DAGs, monitoring of execution, and troubleshooting of failures. It solves problems related to workflow management, task monitoring, and error diagnosis, providing a user-friendly interface for inputs and outputs. Ideal for data engineers and operators seeking to streamline their workflow management and optimization processes.

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

## Description

Enables natural language interaction with Apache Airflow for querying DAGs, monitoring execution, and troubleshooting failures.

## Trust

- **Trust score (0–1):** 0.70
- **Verification tier:** verified
- **Last scanned:** 2026-09-01

## Facts

- **Version:** 1.0.0
- **Skill type:** atomic
- **Execution layer:** mcp-remote
- **Runtime environment:** api
- **Category:** monitoring
- **Updated:** 2026-09-01

## Source

- **Source listing:** [Glama](https://glama.ai/mcp/servers/x519le3uuq)
- **Repository:** <https://github.com/ponderedw/airflow-mcp>

## 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": "ponderedw-airflow-mcp"
    }
  }
}
```

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

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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