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Databricks-MCP-Server
2025-04-14
3 years
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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"]}'
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 schema -
schema(string, required): Name of the schema to list tables from -
filter_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 execute -
timeout_seconds(number, optional, default: 60): Timeout in seconds for the statement execution -
row_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
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Reviews
3
(9)
user_wj6DgblE
2025-04-25
As a dedicated user of the databricks-mcp-server by characat0, I am thoroughly impressed with its functionality and performance. This server seamlessly integrates into our workflows, providing reliability and efficiency. The start URL and welcome information make it incredibly user-friendly, ensuring a smooth onboarding process for new users. Highly recommend!
user_1uTyNkOc
2025-04-25
Databricks-MCP-Server by characat0 is an exceptional product for handling massive data workloads. It seamlessly integrates with existing infrastructures and provides efficient performance. The user-friendly interface and comprehensive documentation make it easy to get started. Highly recommended for data professionals seeking robust and reliable server solutions.
user_L5CWnXDD
2025-04-25
I have been using the databricks-mcp-server by characat0 for some time now, and it has proven to be an outstanding tool for managing my data processing tasks. The user interface is intuitive, making it easy for both beginners and experienced users to navigate. Performance-wise, it is incredibly reliable and efficient, streamlining my workflows significantly. The support and welcome information provided are also top-notch, ensuring a smooth start. Highly recommend this for anyone in need of a robust data management server.
user_okJtsZwX
2025-04-25
As a dedicated user of databricks-mcp-server, I find it incredibly useful for managing my Databricks clusters efficiently. characat0 has done an excellent job with this tool. The user-friendly interface and seamless integration with Databricks make it an indispensable asset for my workflows. Highly recommended for anyone looking to streamline their data operations!
user_OFabcCpm
2025-04-25
As a dedicated user of the databricks-mcp-server, I am continually impressed by its seamless performance and robust features. Developed by characat0, this tool has significantly improved my data processing efficiency. The user-friendly interface and comprehensive support make it a standout choice for any data professional. Highly recommend it for anyone seeking reliable, high-quality server solutions!
user_FubupVaE
2025-04-25
I've been using databricks-mcp-server by characat0 for a while now, and it has significantly improved my data workflow. Its intuitive interface and powerful features streamline complex processes, making data management more efficient. Highly recommend for anyone in need of a reliable and effective data management tool!
user_nvKwgXmP
2025-04-25
As a loyal user of the databricks-mcp-server, I must say it has been a game-changer for my workflow. Created by characat0, this tool offers seamless integration and robust performance. The user interface is intuitive, and the functionalities are tailored perfectly for my needs. Highly recommend it!
user_Do6XJdpK
2025-04-25
I am absolutely thrilled with the databricks-mcp-server by characat0! This server is a game-changer in data processing and management. It is incredibly efficient, reliable, and easy to use. Whether you're handling large datasets or running complex queries, this server delivers top-notch performance every time. Highly recommended for anyone serious about data operations!
user_bJcJK3yE
2025-04-25
The Databricks-MCP-Server by characat0 is a stellar tool for data processing and management. Its seamless integration and user-friendly interface make it a must-have for any data enthusiast. I've found it to be incredibly efficient in handling large datasets. Highly recommended for anyone looking to streamline their data workflows!