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    Mcp Bigquery 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 a...

    128 stars
    JavaScript
    Updated Oct 17, 2025
    bigquery
    google-cloud
    mcp
    mcp-servers
    model-context-protocol
    sql

    Table of Contents

    • What is this? 🤔
    • Quick Example
    • How Does It Work? 🛠️
    • What Can It Do? 📊
    • Quick Start 🚀
    • Prerequisites
    • Option 1: Quick Install via Smithery (Recommended)
    • Option 2: Manual Setup
    • Command Line Arguments
    • Permissions Needed
    • Developer Setup (Optional) 🔧
    • Current Limitations ⚠️
    • Support & Resources 💬
    • License 📝
    • Author ✍️
    • Sponsorship
    • Version History 📋

    Table of Contents

    • What is this? 🤔
    • Quick Example
    • How Does It Work? 🛠️
    • What Can It Do? 📊
    • Quick Start 🚀
    • Prerequisites
    • Option 1: Quick Install via Smithery (Recommended)
    • Option 2: Manual Setup
    • Command Line Arguments
    • Permissions Needed
    • Developer Setup (Optional) 🔧
    • Current Limitations ⚠️
    • Support & Resources 💬
    • License 📝
    • Author ✍️
    • Sponsorship
    • Version History 📋

    Documentation

    BigQuery MCP Server

    smithery badge

    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

    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!

    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:

    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.

    Option 2: Manual Setup

    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.

    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:

    bash
    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:

    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.

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