Google Sheet Analytics MCP

🚀 TNTM Google Sheets Analytics MCP Server

A clean, practical MCP (Model Context Protocol) server for analyzing Google Sheets data with multi-tab support. Built for Claude Desktop and other MCP-compatible AI assistants by TNTM.

🚀 Quick Start

This is a clean and practical MCP (Model Context Protocol) server designed for analyzing Google Sheets data, supporting multi - tab operations. It is developed by TNTM for Claude Desktop and other MCP - compatible AI assistants.

✨ Features

• Smart Sync - Sync Google Sheets with configurable row limits to prevent timeouts.
• Multi - tab Support - Query across multiple sheets with SQL JOINs.
• SQL Queries - Direct SQL access to synced data.
• Sheet Analysis - Get suggestions for cross - sheet queries.
• Quick Preview - Preview sheets without full sync.
• Performance Optimized - Row limits and result pagination for large datasets.

📦 Installation

Prerequisites

• Python 3.8+
• Claude Desktop or another MCP - compatible client
• Google Cloud Project with Sheets API enabled
• OAuth2 credentials from Google Cloud Console

Setup Steps

1. Clone and Install

git clone https://github.com/yourusername/google-sheet-analytics-mcp.git
cd google-sheet-analytics-mcp
python3 -m venv venv
source venv/bin/activate  # On Windows: venv\Scripts\activate
pip install -r requirements.txt

2. Google Cloud Setup

1. Go to Google Cloud Console.
2. Create a new project or select an existing one.
3. Enable the Google Sheets API.
4. Create OAuth2 credentials (Desktop Application).
5. Download the credentials and save as credentials.json in the project root.

3. Run Automated Setup

python3 setup.py

This will:

• Set up OAuth authentication.
• Configure Claude Desktop automatically.
• Test the connection.

Or configure the MCP client manually:

{
  "mcpServers": {
    "google-sheets-analytics": {
      "command": "/path/to/your/venv/bin/python",
      "args": ["/path/to/google-sheet-analytics-mcp/src/mcp_server.py"]
    }
  }
}

4. First Run

Restart your MCP client (e.g., Claude Desktop), and the OAuth flow will start automatically on the first tool use.

💻 Usage Examples

smart_sync

Sync Google Sheet data with performance controls.

Use smart_sync with url "https://docs.google.com/spreadsheets/d/your_sheet_id" and max_rows 500

• url (required): Google Sheets URL.
• max_rows (optional): Max rows per sheet (default: 1000).
• sheets (optional): Array of specific sheet names to sync.

query_sheets

Run SQL queries on synced data, including JOINs across tabs.

Use query_sheets with query "SELECT * FROM sheet1 JOIN sheet2 ON sheet1.id = sheet2.id LIMIT 10"

• query (required): SQL query to execute.

list_synced_sheets

View all synced sheets and their table names.

Use list_synced_sheets

analyze_sheets

Get suggestions for queries across multiple sheets.

Use analyze_sheets with question "How can I combine sales data with customer data?"

• question (required): What you want to analyze.

get_sheet_preview

Quick preview without syncing.

Use get_sheet_preview with url "https://docs.google.com/spreadsheets/d/your_sheet_id" and rows 20

• url (required): Google Sheets URL.
• sheet_name (optional): Specific sheet to preview.
• rows (optional): Number of rows to preview (default: 10).

📚 Documentation

How It Works

1. Authentication - Uses OAuth2 to securely access the Google Sheets API.
2. Sync - Downloads sheet data to a local SQLite database with configurable limits.
3. Query - Enables SQL queries across all synced sheets.
4. Multi - tab - Each sheet becomes a separate table, joinable via SQL.

Project Structure

google-sheet-analytics-mcp/
├── src/
│   ├── mcp_server.py          # Main MCP server implementation
│   └── auth/
│       └── oauth_setup.py     # Unified OAuth authentication module
├── setup.py                   # Unified setup script (handles everything)
├── requirements.txt           # Python dependencies
├── credentials.json.example   # Example OAuth credentials format
├── README.md                  # This file
├── LICENSE                    # MIT License
├── CLAUDE.md                  # Claude-specific instructions
├── data/                      # Runtime data (created automatically)
│   ├── token.json            # OAuth token (created during setup)
│   └── sheets_data.sqlite    # Local database (created on first sync)
└── venv/                      # Virtual environment (created during setup)

Performance

• Row Limits: Default 1000 rows per sheet (configurable).
• Result Limits: Query results limited to 100 rows.
• Local Storage: SQLite database for fast repeated queries.
• Metadata Tracking: Efficient re - syncing of changed data.
• Memory Efficient: Streaming data processing.

Example Use Cases

Multi - tab Analysis

-- Combine sales data with customer information
SELECT 
  s.product_name, 
  s.sales_amount, 
  c.customer_name, 
  c.customer_segment
FROM sales_data s 
JOIN customer_data c ON s.customer_id = c.id
WHERE s.sales_amount > 1000

Cross - sheet Aggregation

-- Total revenue by region from multiple sheets
SELECT 
  region, 
  SUM(amount) as total_revenue
FROM (
  SELECT region, amount FROM q1_sales
  UNION ALL
  SELECT region, amount FROM q2_sales
)
GROUP BY region
ORDER BY total_revenue DESC

Security

• OAuth2 authentication with Google.
• Credentials stored locally (never committed to repo).
• Read - only access to Google Sheets.
• Local SQLite database (no external data transmission).

Troubleshooting

Common Issues

OAuth Troubleshooting

• Check status: venv/bin/python src/auth/oauth_setup.py --status
• Test auth: venv/bin/python src/auth/oauth_setup.py --test
• Reset OAuth: venv/bin/python src/auth/oauth_setup.py --reset
• Manual setup: venv/bin/python src/auth/oauth_setup.py --manual

MCP Server Not Appearing

1. Ensure Claude Desktop is fully closed.
2. Verify config: cat ~/Library/Application\ Support/Claude/claude_desktop_config.json.
3. Check that the config includes the google - sheets - analytics server.
4. Restart Claude Desktop.
5. Check the developer console for errors.

Database Issues

• Database location: data/sheets_data.sqlite
• Reset database: Delete the file and re - sync.
• Check synced sheets: Use the list_synced_sheets tool.

🤝 Contributing

1. Fork the repository.
2. Create a feature branch (git checkout -b feature/amazing-feature).
3. Commit your changes (git commit -m 'Add amazing feature').
4. Push to the branch (git push origin feature/amazing-feature).
5. Open a Pull Request.

📄 License

This project is licensed under the MIT License - see the LICENSE file for details.

🙏 Acknowledgments

• Built for the Model Context Protocol.
• Designed for Claude Desktop.
• Uses Google Sheets API.

⚠️ Important Note

Need help? Open an issue on GitHub or check the troubleshooting section above.