databricks-mcp-server
Provides tools for interacting with Databricks workspaces, allowing users to list catalogs, schemas, and tables, execute SQL statements, and retrieve information about SQL warehouses.
This server does not currently have a deployable release on Glama. Follow the repository's setup instructions to install and configure it for your MCP client, including any required credentials and local dependencies.
Databricks MCP Server
A Model Context Protocol (MCP) server for interacting with Databricks.
Installation
You can download the latest release for your platform from the Releases page.
VS Code
Install the Databricks MCP Server extension in VS Code by pressing the following link:
Alternatively, you can install the extension manually by running the following command:
# For VS Code
code --add-mcp '{"name":"databricks","command":"npx","args":["databricks-mcp-server@latest"]}'
# For VS Code Insiders
code-insiders --add-mcp '{"name":"databricks","command":"npx","args":["databricks-mcp-server@latest"]}'Related MCP server: mcp-server-cloudbrowser
Tools
The Databricks MCP Server provides a Model Context Protocol (MCP) interface to interact with Databricks workspaces. It offers the following functionalities:
List Catalogs
Lists all catalogs available in the Databricks workspace.
Tool name: list_catalogs
Parameters: None
Returns: JSON array of catalog objects
List Schemas
Lists all schemas in a specified Databricks catalog.
Tool name: list_schemas
Parameters:
catalog(string, required): Name of the catalog to list schemas from
Returns: JSON array of schema objects
List Tables
Lists all tables in a specified Databricks schema with optional filtering.
Tool name: list_tables
Parameters:
catalog(string, required): Name of the catalog containing the schemaschema(string, required): Name of the schema to list tables fromfilter_pattern(string, optional, default: ".*"): Regular expression pattern to filter table names
Returns: JSON array of table objects
Execute SQL
Executes SQL statements on a Databricks SQL warehouse and returns the results.
Tool name: execute_sql
Parameters:
statement(string, required): SQL statement to executetimeout_seconds(number, optional, default: 60): Timeout in seconds for the statement executionrow_limit(number, optional, default: 100): Maximum number of rows to return in the result
Returns: JSON object containing columns and rows from the query result, with information of the SQL warehouse used to execute the statement.
List SQL Warehouses
Lists all SQL warehouses available in the Databricks workspace.
Tool name: list_warehouses
Parameters: None
Returns: JSON array of SQL warehouse objects
Supported Platforms
Linux (amd64)
Windows (amd64)
macOS (Intel/amd64)
macOS (Apple Silicon/arm64)
Usage
Authentication
The application uses Databricks unified authentication. For details on how to configure authentication, please refer to the Databricks Authentication documentation.
Running the Server
Start the MCP server:
./databricks-mcp-serverThe server will start and listen for MCP protocol commands on standard input/output.
Development
Prerequisites
Go 1.24 or later
Tool Schema Changelog
Recent tool additions, removals, and schema changes observed during successful MCP inspections.
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This server cannot be deployed
Maintenance
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