Databricks MCP Server
A Model Completion Protocol (MCP) server for interacting with Databricks services
What is Databricks MCP Server?
what is Databricks MCP Server? Databricks MCP Server is a Model Completion Protocol (MCP) server designed to facilitate interaction with Databricks services, enabling LLM-powered tools to communicate with Databricks clusters, jobs, notebooks, and more. how to use Databricks MCP Server? To use the Databricks MCP Server, install the required dependencies, set up environment variables for your Databricks instance, and run the server using provided scripts. key features of Databricks MCP Server? MCP Protocol Support: Allows LLMs to interact with Databricks. Databricks API Integration: Access to Databricks REST API functionality. Tool Registration: Exposes Databricks functionality as MCP tools. Async Support: Built with asyncio for efficient operation. use cases of Databricks MCP Server? Managing Databricks clusters (create, start, terminate). Running and managing Databricks jobs. Accessing and exporting notebooks from Databricks. Executing SQL statements on Databricks. FAQ from Databricks MCP Server? What is the MCP protocol? The MCP protocol is a communication protocol that allows LLMs to interact with Databricks services. What are the prerequisites for installation? You need Python 3.10 or higher and the uv package manager. Is there support for asynchronous operations? Yes, the server is built with asyncio for efficient handling of requests.
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.
How to use Databricks MCP Server
To use the Databricks MCP Server, install the required dependencies, set up environment variables for your Databricks instance, and run the server using provided scripts. key features of Databricks MCP Server? MCP Protocol Support: Allows LLMs to interact with Databricks. Databricks API Integration: Access to Databricks REST API functionality. Tool Registration: Exposes Databricks functionality as MCP tools. Async Support: Built with asyncio for efficient operation. use cases of Databricks MCP Server? Managing Databricks clusters (create, start, terminate). Running and managing Databricks jobs. Accessing and exporting notebooks from Databricks. Executing SQL statements on Databricks. FAQ from Databricks MCP Server? What is the MCP protocol? The MCP protocol is a communication protocol that allows LLMs to interact with Databricks services. What are the prerequisites for installation? You need Python 3.10 or higher and the uv package manager. Is there support for asynchronous operations? Yes, the server is built with asyncio for efficient handling of requests.
Learn how to integrate this MCP server with your AI agents and leverage the Model Context Protocol for enhanced capabilities.
Use Cases for this MCP Server
- No use cases specified.
MCP servers like Databricks MCP Server can be used with various AI models including Claude and other language models to extend their capabilities through the Model Context Protocol.
About Model Context Protocol (MCP)
The Model Context Protocol (MCP) is a standardized way for AI agents to communicate with various services and tools. MCP servers like Databricks MCP Server provide specific capabilities that can be accessed through a consistent interface, making it easier to build powerful AI applications with complex workflows.
Browse the MCP Directory to discover more servers and clients that can enhance your AI agents' capabilities.