databricks-mcp-server
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A Model Completion Protocol (MCP) server for Databricks that provides access to Databricks functionality via the MCP protocol.
The Databricks MCP Server is designed to facilitate interaction between LLM-powered tools and Databricks clusters, jobs, notebooks, and more through the Model Completion Protocol (MCP). By integrating with the Databricks REST API, this server allows for seamless management and execution of Databricks resources. It supports asynchronous operations using asyncio, ensuring efficient and scalable performance. The server also registers various Databricks functionalities as MCP tools, making it easier for developers to automate and manage their Databricks environments. With its robust feature set, the Databricks MCP Server is an essential tool for developers looking to leverage the power of Databricks in their LLM applications.
Features
- MCP Protocol Support: Implements the MCP protocol to allow LLMs to interact with Databricks.
- Databricks API Integration: Provides access to Databricks REST API functionality.
- Tool Registration: Exposes Databricks functionality as MCP tools.
- Async Support: Built with asyncio for efficient operation.
Tools
list_clusters
List all Databricks clusters.
create_cluster
Create a new Databricks cluster.
terminate_cluster
Terminate a Databricks cluster.
get_cluster
Get information about a specific Databricks cluster.
start_cluster
Start a terminated Databricks cluster.
list_jobs
List all Databricks jobs.
run_job
Run a Databricks job.
list_notebooks
List notebooks in a workspace directory.
export_notebook
Export a notebook from the workspace.
list_files
List files and directories in a DBFS path.
execute_sql
Execute a SQL statement.
