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.dataViewerroles/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 💬
- 🐛 Report issues
- 💡 Feature requests
- 📖 Documentation
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.
BigQuery
Project Details
- ergut/mcp-bigquery-server
- @ergut/mcp-bigquery-server
- MIT License
- Last Updated: 4/22/2025
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