henilcalagiya/google-sheets-mcp

Overview

A lightweight connector that gives your AI assistant read and write access to Google Sheets, so you can check figures, update cells, or automate a spreadsheet update from a plain-English request. It is a smaller, more minimal package than some alternatives, covering the core read and write actions without extra features. Useful for a small business that keeps simple tracking in Sheets and wants a quick way to update it.

Best for

Best for
Small businesses with simple spreadsheet tracking who want quick updates via chat

Use cases

• Check a figure or cell value in a spreadsheet
• Update a row as part of a recurring workflow
• Pull a quick summary of spreadsheet data into a conversation
• Automate a repetitive data entry task

How to use

Install

uvx google-sheets-mcp@latest

Tools exposed

• uvx

Tested with

Continue.dev, Claude Desktop, Perplexity

Example client config

{\n  "mcpServers": {\n    "google-sheets-mcp": {\n      "command": "uvx",\n      "args": ["google-sheets-mcp@latest"],\n      "env": {\n        "project_id": "your-project-id",\n        "private_key_id": "your-private-key-id",\n        "private_key": "-----BEGIN PRIVATE KEY-----\n...\n-----END PRIVATE KEY-----\n",\n        "client_email": "your-service@your-project.iam.gserviceaccount.com",\n        "client_id": "your-client-id",\n        "client_x509_cert_url": "https://www.googleapis.com/robot/v1/metadata/x509/your-service%40your-project.iam.gserviceaccount.com"\n      }\n    }\n  }\n}

Notes

A Python package that implements a Model Context Protocol (MCP) server for Google Sheets, enabling AI agents to read, write, and manipulate spreadsheet data through a standardized interface. It wraps the Google Sheets API into MCP tools that can be called by any MCP-compatible client.

14 stars on GitHub. Last updated 2025-09-11.

Use cases

• Reading and writing cell values in Google Sheets from an AI agent
• Automating spreadsheet updates as part of a data pipeline or workflow
• Integrating Google Sheets as a data source or destination for AI assistants

Pros

• Lightweight Python package with minimal dependencies
• Works with any MCP-compatible client, offering flexibility
• Open source with a straightforward implementation

Cons

• Small community (14 stars) may mean limited support and slower updates
• Requires Google API credentials and OAuth setup, adding initial overhead
• Basic functionality; advanced features like formatting or pivot tables are not covered

Indexed from awesome-mcp-servers-punkpeye and enriched against its public facts.