"How to work with Google Sheets" matching MCP servers:

A write-only MCP server for Google Sheets with safety features including whitelist, dry-run, snapshot, and audit logging.

A comprehensive Google Sheets MCP server offering 26 tools for read/write, structural updates, Drive search, and an escape hatch for executing arbitrary Node.js code with pre-authenticated Sheets and Drive clients.

A Model Context Protocol server that integrates with Google Drive and Google Sheets, enabling users to create, read, update, and manage spreadsheets through natural language commands.

Enables AI assistants to access, search, and analyze Google Spreadsheets through the Model Context Protocol. Supports both OAuth 2.0 for private sheets and API key authentication for public sheets, with tools for listing, reading, and searching spreadsheet data.

A locally running MCP server that provides cell-level and formatting-level control over Google Sheets via the Sheets API v4, enabling reading, writing, formatting, and managing spreadsheets through natural language.

Read and write Google Sheets, Docs, Drive, and Apps Script from any MCP client. 82 tools with OAuth2 auth, tested against live Google APIs.

Integrates with Google Drive to enable listing, searching, and reading files, plus reading and writing to Google Sheets.

Provides a secure bridge for AI assistants to interact with the Google Sheets API via 31 tools for spreadsheet management, data manipulation, and table-level operations. It supports both Service Account and OAuth 2.0 authentication for tasks including batch updates, CSV imports, and conditional formatting.

Demonstrates how to create a simple MCP server with streamable HTTP transport, featuring tools, prompts, and resources.

Enables AI assistants to perform CRUD operations on a SQLite database, with all tools protected by Google OAuth 2.0 authentication.

Provides comprehensive Google Sheets integration for creating, reading, updating, and managing spreadsheets programmatically via tools like batch updates and range operations. It enables automated workflows for data analysis, project management, and synchronization within the Model Context Protocol.

Converts AI Skills (following Claude Skills format) into MCP server resources, enabling LLM applications to discover, access, and utilize self-contained skill directories through the Model Context Protocol. Provides tools to list available skills, retrieve skill details and content, and read supporting files with security protections.

Self-improving, verifiable memory for AI coding agents. Learns how you work, stops repeating mistakes, models each project, recalls the right lesson at the right moment. Every memory is signed and tamper-evident. Local-first.

An educational MCP server example demonstrating how to build a server that integrates with LLM clients like Claude Desktop.

Enables AI assistants to create and modify Google Apps Script projects, manage versions and deployments, run functions, and inspect execution history through natural language.

A simple MCP server that provides a basic greeting tool and serves as a starter template for AWS Lambda deployment. Demonstrates how to build and deploy MCP servers with both local development and cloud deployment capabilities.

Converts a Figma file into a React project using Ant Design, AG Grid, ApexCharts, and Tailwind CSS, with optional export of mobile screens as a React Native (Expo) app.

This MCP server enables AI assistants to search the Google Fonts catalogue, retrieve detailed font metadata, generate live HTML text previews, and obtain embed code for use on web pages.

MCP server for searching Google Fonts and generating complete CSS/Tailwind typographic systems with font pairings and modular scales.

MCP server for the Google Tag Manager API v2, enabling natural-language management of containers, workspaces, tags, triggers, variables, and publishing. It handles OAuth authentication and built-in rate limiting for the strict GTM API quota.