# Airflow ETL Pipeline Generator

> Use this tool when you need to automate ETL pipeline creation and management in enterprise data environments. It solves problems such as data source connectivity testing, schema extraction, and pipeline configuration, and takes inputs from various data sources like PostgreSQL, Kafka, and S3, outputting production-ready Airflow DAGs. Ideal for data engineers and analysts who need to rapidly prototype and deploy ETL processes, it streamlines data migration, file processing, and real-time data ingestion workflows.

Canonical page: https://skillsregistry.net/skills/anatoliyaksenov-airflow-etl-pipeline-generator  
JSON: https://api.skillsregistry.net/v1/skills/anatoliyaksenov-airflow-etl-pipeline-generator

## Description

Data Engineering Agent MCP Server provides tools for building and managing ETL pipelines in enterprise data environments. Built by Anatoliy A Aksenov, it integrates with Apache Airflow, GitLab, Kafka, PostgreSQL, S3-compatible storage, and SMB file systems to enable end-to-end data pipeline creation through conversational interfaces. The server offers connectivity testing, schema extraction, file sampling across multiple data sources, form-based pipeline configuration for database-to-datalake, file-to-datalake, and API-to-datalake workflows, plus automatic GitLab issue creation for pipeline requests with pre-built Spark application templates. Particularly valuable for data engineers and analysts who need to rapidly prototype ETL processes, validate data source connectivity, and generate production-ready Airflow DAGs without manual coding, supporting common enterprise scenarios like PostgreSQL to data lake migrations, S3 file processing, and real-time Kafka stream ingestion.

## Trust

- **Trust score (0–1):** 0.87
- **Verification tier:** verified
- **Last scanned:** 2026-09-28

## Facts

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

## Source

- **Source listing:** [PulseMCP](https://www.pulsemcp.com/servers/anatoliyaksenov-airflow-etl-pipeline-generator)
- **Repository:** <https://github.com/anatoliyaksenov/chat-app-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": "anatoliyaksenov-airflow-etl-pipeline-generator"
    }
  }
}
```

REST: `GET https://api.skillsregistry.net/v1/skills/anatoliyaksenov-airflow-etl-pipeline-generator` · pull for local use: `GET https://api.skillsregistry.net/v1/skills/anatoliyaksenov-airflow-etl-pipeline-generator/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