sheets-mcp-server

sheets-mcp-server

An MCP server that lets AI agents read and write Google Sheets using the Google Sheets API v4.

Category
Visit Server

README

sheets-mcp-server

An MCP server that lets AI agents read and write Google Sheets. Built with the Model Context Protocol and the Google Sheets API v4.

Tools

Tool Description
sheets_read Read data from a range in a Google Sheet
sheets_write Write a 2D array of values to a range
sheets_append Append rows to the end of a sheet
sheets_create Create a new spreadsheet with custom tabs
sheets_info Get spreadsheet metadata (title, sheets, dimensions)
sheets_format Apply bold, background color, or text color to a range

Setup

1. Create a Google Cloud project

  1. Go to the Google Cloud Console.
  2. Click Select a project > New Project.
  3. Give it a name and click Create.

2. Enable the Google Sheets API

  1. In the Cloud Console, go to APIs & Services > Library.
  2. Search for Google Sheets API and click Enable.

3. Create a service account

  1. Go to APIs & Services > Credentials.
  2. Click Create Credentials > Service account.
  3. Give it a name (e.g. sheets-mcp) and click Done.
  4. Click the new service account, go to the Keys tab.
  5. Click Add Key > Create new key > JSON and download the file.
  6. Save the JSON key file somewhere secure (e.g. ~/.config/sheets-mcp/service-account.json).

4. Share your spreadsheets

Open any Google Sheet you want the server to access, click Share, and add the service account email address (found in the JSON key file under client_email). Grant Editor access.

5. Set the environment variable

export GOOGLE_SERVICE_ACCOUNT_KEY=/path/to/service-account.json

Or create a .env file in the project directory:

GOOGLE_SERVICE_ACCOUNT_KEY=/path/to/service-account.json

Installation

# With pip
pip install .

# Or with uv
uv pip install .

Claude Desktop configuration

Add this to your Claude Desktop config file (~/Library/Application Support/Claude/claude_desktop_config.json on macOS):

{
  "mcpServers": {
    "sheets": {
      "command": "sheets-mcp",
      "env": {
        "GOOGLE_SERVICE_ACCOUNT_KEY": "/path/to/service-account.json"
      }
    }
  }
}

Or if running from the source directory with uv:

{
  "mcpServers": {
    "sheets": {
      "command": "uv",
      "args": ["run", "--directory", "/path/to/sheets-mcp", "sheets-mcp"],
      "env": {
        "GOOGLE_SERVICE_ACCOUNT_KEY": "/path/to/service-account.json"
      }
    }
  }
}

Example usage

Once connected, an AI agent can use the tools like this:

Read data:

Read cells A1 through D10 from spreadsheet 1BxiMVs0XRA5nFMdKvBdBZjgmUUqptlbs74OgVE2upms

Write data:

Write these sales figures to Sheet1!A1:C3: [["Product", "Q1", "Q2"], ["Widget", 150, 230], ["Gadget", 320, 180]]

Create a new spreadsheet:

Create a new spreadsheet called "Project Tracker" with tabs "Tasks", "Timeline", and "Budget"

Format headers:

Bold the header row A1:E1 and give it a blue background (#4285F4) with white text (#FFFFFF)

Append rows:

Append these new entries to the bottom of the log in Sheet1: [["2026-03-13", "Completed review", "Alice"]]

License

MIT

Recommended Servers

playwright-mcp

playwright-mcp

A Model Context Protocol server that enables LLMs to interact with web pages through structured accessibility snapshots without requiring vision models or screenshots.

Official
Featured
TypeScript
Magic Component Platform (MCP)

Magic Component Platform (MCP)

An AI-powered tool that generates modern UI components from natural language descriptions, integrating with popular IDEs to streamline UI development workflow.

Official
Featured
Local
TypeScript
Audiense Insights MCP Server

Audiense Insights MCP Server

Enables interaction with Audiense Insights accounts via the Model Context Protocol, facilitating the extraction and analysis of marketing insights and audience data including demographics, behavior, and influencer engagement.

Official
Featured
Local
TypeScript
VeyraX MCP

VeyraX MCP

Single MCP tool to connect all your favorite tools: Gmail, Calendar and 40 more.

Official
Featured
Local
graphlit-mcp-server

graphlit-mcp-server

The Model Context Protocol (MCP) Server enables integration between MCP clients and the Graphlit service. Ingest anything from Slack to Gmail to podcast feeds, in addition to web crawling, into a Graphlit project - and then retrieve relevant contents from the MCP client.

Official
Featured
TypeScript
Kagi MCP Server

Kagi MCP Server

An MCP server that integrates Kagi search capabilities with Claude AI, enabling Claude to perform real-time web searches when answering questions that require up-to-date information.

Official
Featured
Python
E2B

E2B

Using MCP to run code via e2b.

Official
Featured
Neon Database

Neon Database

MCP server for interacting with Neon Management API and databases

Official
Featured
Exa Search

Exa Search

A Model Context Protocol (MCP) server lets AI assistants like Claude use the Exa AI Search API for web searches. This setup allows AI models to get real-time web information in a safe and controlled way.

Official
Featured
Qdrant Server

Qdrant Server

This repository is an example of how to create a MCP server for Qdrant, a vector search engine.

Official
Featured