"Databricks" matching MCP servers:

Enables natural-language interaction with a Databricks Lakehouse, including running SQL on warehouses, tracking and canceling long-running queries, and exploring Unity Catalog metadata via the workspace REST API.

Enables MCP-compatible clients to execute Databricks CLI commands without shell interpolation, with pipes and redirects stripped so clients can filter or format raw output. It supports any subcommand permitted by the configured Databricks authentication profile.

Enables read-only interaction with a Databricks workspace, exposing catalog metadata and bounded SQL querying while preserving caller identity through OAuth-protected authorization.

Enables management of Unity Catalog resources (catalogs, schemas, tables) and execution of SQL queries on Databricks SQL Warehouses.

Provides MCP tools to interact with Databricks SQL warehouses, enabling metadata discovery, table reading, and DDL operations.

Exposes Databricks REST API as MCP tools for managing clusters, jobs, notebooks, SQL queries, Unity Catalog, and more. Enables AI agents to interact with Databricks workspaces through natural language.

databricks-mcp-server

Enables AI assistants like Claude to interact with Databricks workspaces through a secure MCP server running on Databricks Apps. Supports custom prompts and tools using the Databricks SDK.

A Model Context Protocol server that lets LLM clients answer business questions in natural language over a Databricks dataset without writing SQL by hand.

Enables LLMs to manage Databricks clusters, jobs, and notebooks while providing schema references for gold and silver data layers. It allows agents to perform data discovery and execute SQL queries directly against Databricks environments.

MCP server for Databricks Unity Catalog, enabling table listing, schema description, and read-only SQL query execution via natural language. Built from scratch to demonstrate JSON-RPC 2.0 protocol depth.

Enables AI agents to explore Unity Catalog metadata, execute SQL queries, and analyze data lineage including notebooks and jobs, empowering autonomous data discovery and query generation in Databricks.

Enables AI assistants to interact with Databricks workspaces programmatically, providing comprehensive tools for cluster management, notebook operations, job orchestration, Unity Catalog data governance, user management, permissions control, and FinOps cost analytics.

This is a Model Context Protocol (MCP) server for executing SQL queries against Databricks using the Statement Execution API. It enables AI assistants to directly query Databricks data warehouses, analyze database schemas, and retrieve query results in a structured format

Enables AI assistants to interact with the Databricks platform through 263 tools and 8 prompt templates, covering Unity Catalog, SQL, Compute, Jobs, Pipelines, and more.

Provides tools for interacting with Databricks clusters, jobs, and workspace operations via the Model Context Protocol.

Enables interaction with Databricks for running SQL queries, managing clusters, triggering jobs, running notebooks, exploring Unity Catalog metadata, managing secrets, and interacting with DBFS.

Enables AI agents to interact with Coalesce and Snowflake to perform data transformations, run operations, and manage Coalesce resources via natural language.

A Model Context Protocol server that enables LLMs to interact with Databricks workspaces through natural language, allowing SQL query execution and job management operations.

Enables management and monitoring of Databricks jobs, including listing, running, and canceling jobs, through the Model Context Protocol.