About Databricks MCP Server
Databricks MCP Server provides a protocol interface to Databricks workspaces, with tools for listing catalogs, schemas, tables, and SQL warehouses and executing SQL. It is intended for MCP clients that need workspace metadata or query results.
Key features
- 01List catalogs and schemas
- 02List and filter tables
- 03Execute SQL queries
- 04List SQL warehouses
Use cases
- 01Inspect workspace catalogs and tables
- 02Run queries on a SQL warehouse
MCP support
The MCP server exposes Databricks workspace tools to clients, including metadata listing, SQL execution, and warehouse discovery.
Configuration
Local server config is the same for every client. Copy it into your client’s MCP config file.
Tools
6Saved tool list · updated 3w ago
| Parameter | Type | Required | Description |
|---|---|---|---|
| max_rows | number | No | Maximum number of rows to return in the result |
| statement | string | Yes | SQL statement to execute |
| warehouse_id | string | No | ID of the warehouse to use for execution. If not specified, the first available warehouse will be used |
| execution_timeout_seconds | number | No | Maximum time in seconds to wait for query execution |
Details
From the project READMEDatabricks 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"]}'
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-server
The server will start and listen for MCP protocol commands on standard input/output.
Development
Prerequisites
- Go 1.24 or later
Comments
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