I craft unique cereal names, stories, and ridiculously cute Cereal Baby images.

ergut_mcp-bigquery-server
Mirror ofhttps://github.com/ergut/mcp-bigquery-server
3 years
Works with Finder
0
Github Watches
1
Github Forks
0
Github Stars
BigQuery MCP Server

What is this? 🤔
This is a server that lets your LLMs (like Claude) talk directly to your BigQuery data! Think of it as a friendly translator that sits between your AI assistant and your database, making sure they can chat securely and efficiently.
Quick Example
You: "What were our top 10 customers last month?"
Claude: *queries your BigQuery database and gives you the answer in plain English*
No more writing SQL queries by hand - just chat naturally with your data!
How Does It Work? 🛠️
This server uses the Model Context Protocol (MCP), which is like a universal translator for AI-database communication. While MCP is designed to work with any AI model, right now it's available as a developer preview in Claude Desktop.
Here's all you need to do:
- Set up authentication (see below)
- Add your project details to Claude Desktop's config file
- Start chatting with your BigQuery data naturally!
What Can It Do? 📊
- Run SQL queries by just asking questions in plain English
- Access both tables and materialized views in your datasets
- Explore dataset schemas with clear labeling of resource types (tables vs views)
- Analyze data within safe limits (1GB query limit by default)
- Keep your data secure (read-only access)
Quick Start 🚀
Prerequisites
- Node.js 14 or higher
- Google Cloud project with BigQuery enabled
- Either Google Cloud CLI installed or a service account key file
- Claude Desktop (currently the only supported LLM interface)
Option 1: Quick Install via Smithery (Recommended)
To install BigQuery MCP Server for Claude Desktop automatically via Smithery, run this command in your terminal:
npx @smithery/cli install @ergut/mcp-bigquery-server --client claude
The installer will prompt you for:
- Your Google Cloud project ID
- BigQuery location (defaults to us-central1)
Once configured, Smithery will automatically update your Claude Desktop configuration and restart the application.
Option 2: Manual Setup
If you prefer manual configuration or need more control:
-
Authenticate with Google Cloud (choose one method):
- Using Google Cloud CLI (great for development):
gcloud auth application-default login
- Using a service account (recommended for production):
# Save your service account key file and use --key-file parameter # Remember to keep your service account key file secure and never commit it to version control
- Using Google Cloud CLI (great for development):
-
Add to your Claude Desktop config Add this to your
claude_desktop_config.json
:-
Basic configuration:
{ "mcpServers": { "bigquery": { "command": "npx", "args": [ "-y", "@ergut/mcp-bigquery-server", "--project-id", "your-project-id", "--location", "us-central1" ] } } }
-
With service account:
{ "mcpServers": { "bigquery": { "command": "npx", "args": [ "-y", "@ergut/mcp-bigquery-server", "--project-id", "your-project-id", "--location", "us-central1", "--key-file", "/path/to/service-account-key.json" ] } } }
-
-
Start chatting! Open Claude Desktop and start asking questions about your data.
Command Line Arguments
The server accepts the following arguments:
-
--project-id
: (Required) Your Google Cloud project ID -
--location
: (Optional) BigQuery location, defaults to 'us-central1' -
--key-file
: (Optional) Path to service account key JSON file
Example using service account:
npx @ergut/mcp-bigquery-server --project-id your-project-id --location europe-west1 --key-file /path/to/key.json
Permissions Needed
You'll need one of these:
-
roles/bigquery.user
(recommended) - OR both:
-
roles/bigquery.dataViewer
-
roles/bigquery.jobUser
-
Developer Setup (Optional) 🔧
Want to customize or contribute? Here's how to set it up locally:
# Clone and install
git clone https://github.com/ergut/mcp-bigquery-server
cd mcp-bigquery-server
npm install
# Build
npm run build
Then update your Claude Desktop config to point to your local build:
{
"mcpServers": {
"bigquery": {
"command": "node",
"args": [
"/path/to/your/clone/mcp-bigquery-server/dist/index.js",
"--project-id",
"your-project-id",
"--location",
"us-central1",
"--key-file",
"/path/to/service-account-key.json"
]
}
}
}
Current Limitations ⚠️
- MCP support is currently only available in Claude Desktop (developer preview)
- Connections are limited to local MCP servers running on the same machine
- Queries are read-only with a 1GB processing limit
- While both tables and views are supported, some complex view types might have limitations
Support & Resources 💬
License 📝
MIT License - See LICENSE file for details.
Author ✍️
Salih Ergüt
Sponsorship
This project is proudly sponsored by:
Version History 📋
See CHANGELOG.md for updates and version history.
相关推荐
Evaluator for marketplace product descriptions, checks for relevancy and keyword stuffing.
Confidential guide on numerology and astrology, based of GG33 Public information
Professional Flask/SQLAlchemy code guide. Follow: https://x.com/navid_re
A geek-themed horoscope generator blending Bitcoin prices, tech jargon, and astrological whimsy.
Converts Figma frames into front-end code for various mobile frameworks.
Discover the most comprehensive and up-to-date collection of MCP servers in the market. This repository serves as a centralized hub, offering an extensive catalog of open-source and proprietary MCP servers, complete with features, documentation links, and contributors.
Micropython I2C-based manipulation of the MCP series GPIO expander, derived from Adafruit_MCP230xx
A unified API gateway for integrating multiple etherscan-like blockchain explorer APIs with Model Context Protocol (MCP) support for AI assistants.
Mirror ofhttps://github.com/agentience/practices_mcp_server
Mirror ofhttps://github.com/bitrefill/bitrefill-mcp-server
Reviews

user_JVLGf5S0
Pentest MCP is an outstanding tool for professional penetration testing! It provides comprehensive features that streamline the entire testing process, from initial reconnaissance to final report generation. The user interface is intuitive and the extensive range of utilities ensures that no stone is left unturned in your security assessments. A must-have for any serious cybersecurity professional!