mcp-bigquery-server
About This Server
A Model Context Protocol (MCP) server that provides secure, read-only access to BigQuery datasets. Enables Large Language Models (LLMs) to safely query and analyze data through a standardized interface.
Server Information
This webpage is the GitHub repository for the "mcp-bigquery-server" project, created by ergut. This project provides a Model Context Protocol (MCP) server that enables Large Language Models (LLMs) to securely query and analyze BigQuery datasets through a standardized interface. It aims to facilitate natural language interaction with BigQuery data, offering a secure, read-only environment for data analysis.
ā Key Points:
- The project provides a secure, read-only access layer to BigQuery datasets for LLMs.
- It uses the Model Context Protocol (MCP) for AI-database communication.
- The server is currently available as a developer preview in Claude Desktop.
- Users can query BigQuery data using plain English.
- The project offers both quick installation via Smithery and manual setup options.
- The repository is public and has 17 stars and 3 forks.
- The primary programming language used is JavaScript (100%).
- The project uses the MIT license.
- The project has several limitations, including only being supported in Claude Desktop's developer preview.
- The project is sponsored by OREDATA.
- The project utilizes Node.js 14 or higher.
- Authentication with Google Cloud is necessary, either through Google Cloud CLI or a service account key file.
- Queries are read-only with a 1GB processing limit.
- The repository contains files such as ".gitignore", "CHANGELOG.md", "LICENSE", "README.md", "package-lock.json", "package.json", and "tsconfig.json", along with directories ".github/workflows", "assets", and "src".
š Main Findings:
š Details:
šÆ Conclusion:
The "mcp-bigquery-server" project offers a solution for integrating LLMs with BigQuery, providing a secure and user-friendly interface for data analysis. While currently limited to Claude Desktop and local MCP servers, the project aims to simplify data querying for users without SQL expertise and to create a safe environment for LLMs to interact with sensitive data.
Server Features
Natural Language Querying
Run SQL queries by just asking questions in plain English
Dataset Access
Access both tables and materialized views in your datasets
Schema Exploration
Explore dataset schemas with clear labeling of resource types (tables vs views)
Safe Data Analysis
Analyze data within safe limits (1GB query limit by default)
Secure Data Access
Keep your data secure (read-only access)
Provider Information
Ergut
cloud Provider