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.

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``text
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:
1. Set up authentication (see below)
2. Add your project details to Claude Desktop's config file
3. Start chatting with your BigQuery data naturally!

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- 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 🚀

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- 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)

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To install BigQuery MCP Server for Claude Desktop automatically via Smithery, run this command in your terminal:

`bash
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.

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If you prefer manual configuration or need more control:

1. Authenticate with Google Cloud (choose one method):
- Using Google Cloud CLI (great for development):
`bash
gcloud auth application-default login
`
- Using a service account (recommended for production):
`bash
# 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
`

2. Add to your Claude Desktop config
Add this to your claude_desktop_config.json:

- Basic configuration:
`json
{
"mcpServers": {
"bigquery": {
"command": "npx",
"args": [
"-y",
"@ergut/mcp-bigquery-server",
"--project-id",
"your-project-id",
"--location",
"us-central1"
]
}
}
}
`

- With service account:
`json
{
"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"
]
}
}
}
`


3. Start chatting!
Open Claude Desktop and start asking questions about your data.

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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:
`bash
npx @ergut/mcp-bigquery-server --project-id your-project-id --location europe-west1 --key-file /path/to/key.json
`

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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:

`bash


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:
`json
{
"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.