Advanced MCP server for Databricks workspace intelligence — dependency scanning, impact analysis, notebook review, and job/pipeline operations.
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# Databricks Advanced MCP Server [](https://www.python.org/downloads/) [](https://pypi.org/project/databricks-advanced-mcp/) [](LICENSE) [](https://modelcontextprotocol.io) [](https://github.com/henrybravo/databricks-advanced-mcp-server/actions/workflows/ci.yml) [](https://codecov.io/gh/henrybravo/databricks-advanced-mcp-server) An advanced [Model Context Protocol (MCP)](https://modelcontextprotocol.io) server that gives AI assistants deep visibility into your Databricks workspace — 43 tools covering dependency scanning, impact analysis, notebook review, job/pipeline operations, SQL execution, catalog management, compute & warehouse control, and Unity Catalog volumes. ## Features | Domain | What it does | |---|---| | **SQL Execution** | Run SQL queries against Databricks SQL warehouses with configurable result limits | | **Table Information** | Inspect table metadata, schemas, column details, row counts, and storage info | | **Dependency Scanning** | Scan notebooks, jobs, and DLT pipelines to build a workspace dependency graph (DAG) | | **Graph Operations** | Build, query, and refresh the workspace dependency graph | | **Impact Analysis** | Predict downstream breakage from column drops, schema changes, or pipeline failures | | **Notebook Review** | Detect performance anti-patterns, coding standard violations, and suggest optimizations | | **Job & Pipeline Ops** | List jobs/pipelines, get run status with error diagnostics, trigger reruns | | **Catalog & Schema** | List catalogs, list/describe/create/dr…
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