Google Sheets Analytics

Provides SQL-based analysis of Google Sheets data across multiple tabs with MCP compatibility.

python

2

GitHub Stars

python

Language

6 months ago

First Indexed

2 months ago

Catalog Refreshed

Documentation & install

Readme and setup notes from the catalogue, plus a client-ready config you can copy for your MCP host.

Installation

Add the following to your MCP client configuration file.

Configuration

View docs

{
  "mcpServers": {
    "talknerdytome-labs-google-sheet-analytics-mcp": {
      "command": "mcp",
      "args": [
        "install",
        "src/mcp_server.py",
        "--name",
        "google-sheets-analytics",
        "--with-editable",
        "."
      ]
    }
  }
}

This MCP server lets you analyze Google Sheets data with multi-tab support, offering smart syncing, cross-tab SQL queries, and quick previews. It’s designed to work with MCP-compatible clients to enable fast data analysis across multiple sheets while keeping performance under control through chunked syncing and result paging.

How to use

You connect a compatible MCP client and start by configuring a Google Sheets data source. Use smart_sync to pull data from one or more sheets with configurable row limits to prevent timeouts. Each sheet becomes a separate table in a local database, so you can write SQL that joins data across tabs.

How to install

Prerequisites you need before starting are Python 3.8 or later and a Google Cloud project with the Sheets API enabled.

Step-by-step setup options you can follow to get up and running quickly.

Option 1: One-Click Setup with Claude Code (recommended) includes guided OAuth setup and automatic environment handling. Follow on-screen prompts to obtain Google OAuth credentials and place credentials.json in the project root.

Option 2: Automated Installation (macOS/Linux) using a shell installer or cloning the project and running the installer.

Option 3: Manual Step-by-step installation to run on any platform with a virtual environment.

Additional setup and configuration

OAuth credentials are required to access Google Sheets. You’ll need to create a Google Cloud project, enable the Sheets API, and download credentials.json to the project root. The OAuth flow creates a token.json file used for authenticated requests.

First run may involve running an OAuth setup script to complete authentication and verify the connection. This step is performed once and enables all MCP tools to operate.

Security and data handling

OAuth2 authentication ensures secure access to Google Sheets. The local database stores queried data for fast responses, with read-only access to the source Sheets.

Troubleshooting

If you encounter issues during installation or authentication, re-run the setup steps, verify that credentials.json exists in the project root, and confirm that the token.json file is present after completing the OAuth flow. For runtime issues, ensure the Google Sheets API is enabled and the Sheets URL is accessible.

Notes

This server supports multi-tab queries, enabling SQL JOINs across sheets. It also provides a quick preview mode to inspect sheet data without performing a full sync.

Available tools

smart_sync

Synchronizes Google Sheets data with intelligent chunking to handle large datasets and prevent timeouts.

query_sheets

Runs SQL queries on the synced data, including JOINs across multiple sheets.

list_synced_sheets

Lists all sheets that have been synced and their corresponding table names.

analyze_sheets

Provides suggestions for cross-sheet SQL queries based on your data scenario.

get_sheet_preview

Returns a quick preview of a sheet without performing a full sync.