# Apache Airflow

> Use this tool when you need to manage and monitor Apache Airflow clusters, automate workflow tasks, and access detailed analytics through a REST API interface. It solves problems related to DAG management, cluster health monitoring, and performance optimization, providing inputs such as API requests and outputs like task instance tracking and event logs. Ideal for DevOps teams, data engineers, and organizations seeking conversational access to Airflow operations without direct UI interaction.

Canonical page: https://skillsregistry.net/skills/call518-airflow-api  
JSON: https://api.skillsregistry.net/v1/skills/call518-airflow-api

## Description

MCP server implementation by call518 that provides AI assistants with complete access to Apache Airflow cluster management and monitoring through REST API integration, built using Python with FastMCP and aiohttp for high-performance async operations. The implementation offers 43 tools covering DAG management (listing, triggering, pausing), cluster health monitoring, pool and variable management, task instance tracking with comprehensive filtering, XCom data access, configuration management, and detailed analytics including event logs, import errors, and performance metrics. Built with modern async HTTP architecture featuring connection pooling, persistent sessions, and optimized pagination defaults, it serves DevOps teams managing Airflow workflows, data engineers monitoring pipeline health, and organizations requiring conversational access to Airflow operations without direct UI interaction, with support for both stdio and HTTP transport methods plus Docker deployment options.

## Trust

- **Trust score (0–1):** 0.79
- **Verification tier:** verified
- **Last scanned:** 2026-09-28

## Facts

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

## Source

- **Source listing:** [PulseMCP](https://www.pulsemcp.com/servers/call518-airflow-api)
- **Repository:** <https://github.com/call518/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": "call518-airflow-api"
    }
  }
}
```

REST: `GET https://api.skillsregistry.net/v1/skills/call518-airflow-api` · pull for local use: `GET https://api.skillsregistry.net/v1/skills/call518-airflow-api/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