# mcp-airflow-simple

> Use this tool when you need to manage and monitor Apache Airflow workflows, as it provides DAG management, monitoring, debugging, and connection testing capabilities through the MCP protocol, solving issues related to workflow orchestration and automation. It accepts Airflow DAGs and configuration inputs, and outputs monitoring and debugging data. Ideal for use cases involving complex workflow management and automation.

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

## Description

Enables DAG management, monitoring, debugging, and connection testing for Apache Airflow through the MCP protocol.

## Trust

- **Trust score (0–1):** 0.70
- **Verification tier:** verified
- **Last scanned:** 2026-08-31

## Facts

- **Version:** 1.0.0
- **Skill type:** atomic
- **Execution layer:** mcp-remote
- **Runtime environment:** api
- **Category:** monitoring
- **Updated:** 2026-08-31

## Source

- **Source listing:** [Glama](https://glama.ai/mcp/servers/pqc18nbtg0)
- **Repository:** <https://github.com/chayasin/mcp-airflow-simple>

## 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": "chayasin-mcp-airflow-simple"
    }
  }
}
```

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