RafaelCartenet/mcp-databricks-server

Model Context Protocol (MCP) server for Databricks that empowers AI agents to autonomously interact with Unity Catalog metadata. Enables data discovery, lineage analysis, and intelligent SQL execution. Agents explore catalogs/schemas/tables, understand relationships, discover notebooks/jobs, and execute queries - greatly reducing ad-hoc query time.

52
/ 100
Established

This tool helps data professionals working with Databricks Unity Catalog by enabling AI agents to understand and interact with their data autonomously. It takes your existing data catalog metadata, including descriptions for catalogs, schemas, tables, and columns, and allows an AI agent to use this information to generate accurate SQL queries and analyze data lineage. Data analysts, data scientists, and data engineers who manage data in Databricks and want to leverage AI for data exploration and query generation will find this valuable.

Use this if you want to empower an AI agent to independently explore your Databricks Unity Catalog, understand data assets and lineage, and generate complex SQL queries, significantly reducing manual query writing time.

Not ideal if your Databricks Unity Catalog metadata is not well-documented or if you do not plan to use AI agents for data interaction.

data-catalog data-governance data-analysis data-engineering ai-assistant
No Package No Dependents
Maintenance 10 / 25
Adoption 7 / 25
Maturity 16 / 25
Community 19 / 25

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Stars

36

Forks

20

Language

Python

License

MIT

Last pushed

Jan 27, 2026

Commits (30d)

0

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