Airflow ETL Pipeline Generator
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.
Composite of vulnerability cleanliness, spec conformance, provenance, stability, and usage signals — scanned and weighted by Cognium. Human and agent signals are tracked separately. Last scanned 2026-09-28.
Scan details: Circle-IR · 2026-09-28 · Appeal
View full trust & usage report →Metadata
- Version
- 1.0.0
- Skill type
- atomic
- Execution layer
- mcp-remote
- Category
- database
- Source
- PulseMCP
- Repository
- github.com/anatoliyaksenov/chat-app-mcp
- Author type
- human
- Last scanned
- 2026-09-28
- Updated
- 2026-09-28
Use via MCP
Resolve Airflow ETL Pipeline Generator from your agent
Streamable HTTP transport at https://api.skillsregistry.net/mcp. No auth for read tools. Discovery: .well-known/mcp.json.
One command in your shell — Claude Code wires it up and verifies the connection. Run /mcp in any session to confirm.
claude mcp add --transport http --scope user skillsregistry https://api.skillsregistry.net/mcp--scope user for --scope project to commit it to .mcp.json.