JordiNei/mcp-databricks-server

Overview

An open-source Python server that exposes Databricks workspace resources through the Model Context Protocol. It allows MCP-compatible AI agents to interact with Databricks clusters, jobs, and notebooks via a standardized interface.

Best for

Best for
Developers building agentic workflows that need read/write access to Databricks resources

Use cases

• Retrieve status of Databricks job runs from an agent
• List and inspect available clusters in a workspace
• Trigger notebook executions and check results programmatically

Notes

An open-source Python server that exposes Databricks workspace resources through the Model Context Protocol. It allows MCP-compatible AI agents to interact with Databricks clusters, jobs, and notebooks via a standardized interface.

49 stars on GitHub. Last updated 2025-04-24.

Use cases

• Retrieve status of Databricks job runs from an agent
• List and inspect available clusters in a workspace
• Trigger notebook executions and check results programmatically

Pros

• Lightweight Python implementation easy to extend
• Compatible with any MCP client (e.g., Claude, custom agents)
• Open source with permissive licensing

Cons

• Small community (49 stars) and limited documentation
• Requires a Databricks API token and workspace URL
• Feature set likely basic; may miss advanced Databricks APIs

Indexed from awesome-mcp-servers-punkpeye and enriched against its public facts.