Databricks MCP Server

What is Mcp Databricks Server? Mcp Databricks Server is a Model Context Protocol (MCP) server designed for executing SQL queries against Databricks using the Statement Execution API. It allows AI assistants to directly query Databricks data warehouses, analyze database schemas, and retrieve query results in a structured format while adhering to permission boundaries. How to use Mcp Databricks Server? To use the server, install the required dependencies, set up your environment variables with your Databricks credentials, and run the server in standalone mode or configure it with Cursor for AI assistance. Key features of Mcp Databricks Server? Execute SQL queries on Databricks. List available schemas in a catalog. List tables in a schema. Describe table schemas. Handle long-running queries with polling. Use cases of Mcp Databricks Server? Executing complex SQL queries on large datasets. Analyzing database schemas for better data management. Integrating with AI assistants for automated data retrieval. FAQ from Mcp Databricks Server? What are the system requirements? Python 3.10+ is required along with necessary dependencies. How do I set up permissions? Ensure that the user associated with the provided token has appropriate permissions for SQL warehouse access and data access. Can I run long queries? Yes, the server is designed to handle long-running queries with a default timeout of 10 minutes.

As an MCP (Model Context Protocol) server, Databricks MCP Server enables AI agents to communicate effectively through standardized interfaces. The Model Context Protocol simplifies integration between different AI models and agent systems.

To use the server, install the required dependencies, set up your environment variables with your Databricks credentials, and run the server in standalone mode or configure it with Cursor for AI assistance. Key features of Mcp Databricks Server? Execute SQL queries on Databricks. List available schemas in a catalog. List tables in a schema. Describe table schemas. Handle long-running queries with polling. Use cases of Mcp Databricks Server? Executing complex SQL queries on large datasets. Analyzing database schemas for better data management. Integrating with AI assistants for automated data retrieval. FAQ from Mcp Databricks Server? What are the system requirements? Python 3.10+ is required along with necessary dependencies. How do I set up permissions? Ensure that the user associated with the provided token has appropriate permissions for SQL warehouse access and data access. Can I run long queries? Yes, the server is designed to handle long-running queries with a default timeout of 10 minutes.

Learn how to integrate this MCP server with your AI agents and leverage the Model Context Protocol for enhanced capabilities.