google-sheets-mcp
Connects Claude.ai to Google Sheets, allowing read, append, and update operations on spreadsheets directly from chat.
README
Google Sheets MCP for Claude.ai
Connect Claude.ai to your Google Sheets via a custom MCP (Model Context Protocol) server hosted on Vercel. Once set up, Claude can read, append, and update your spreadsheet directly from the chat.
What you get
read_sheet— read any range from your sheetappend_row— add a new rowupdate_cell— update a specific cell
Prerequisites
- A Vercel account
- A Google Cloud account
- A Google Sheet you want Claude to access
- Node.js 18+ installed locally
- Git
Step 1 — Clone and install
git clone <your-repo-url>
cd custom_mcp
npm install
Step 2 — Create a Google Cloud OAuth app
- Go to Google Cloud Console
- Create a new project (or use existing)
- Go to APIs & Services → Enable APIs → enable Google Sheets API
- Go to APIs & Services → Credentials → Create Credentials → OAuth 2.0 Client ID
- Application type: Web application
- Name it (e.g.
Claude MCP) - Under Authorized redirect URIs add:
Replacehttps://YOUR-VERCEL-APP.vercel.app/oauth/google/callbackYOUR-VERCEL-APPwith your actual Vercel app name. - Click Save — copy the Client ID and Client Secret
⚠️ Make sure the redirect URI matches your Vercel deployment URL exactly — no trailing slash, must be
https.
Step 3 — Configure OAuth consent screen
- Go to APIs & Services → OAuth consent screen
- User type: External
- Fill in app name, support email
- Add scope:
https://www.googleapis.com/auth/spreadsheets - Under Audience → Test users add your Gmail address
- Click Publish app → Confirm
⚠️ You must publish the app (even unverified) or Google will block the login. When you see the "unverified app" warning during login, click Advanced → Go to app.
Step 4 — Deploy to Vercel
Option A — Via Vercel CLI
npm install -g vercel
vercel login
vercel --prod
Option B — Via GitHub
Push to GitHub → import project in Vercel dashboard → it auto-deploys.
Step 5 — Set environment variables in Vercel
Go to Vercel Dashboard → Your Project → Settings → Environment Variables and add:
JWT secret is a private random string only your server knows — it's used to sign and verify tokens so Claude can't be impersonated. It must be at least 32 characters, completely random, and never shared or committed to Git. Generate one with:
bashnode -e "console.log(require('crypto').randomBytes(32).toString('hex'))"
This outputs 64 random hex characters like a3f8c2... — copy that output directly as your JWT_SECRET value in Vercel. Never use a human-readable phrase like "mysecret123" — it's trivially guessable.|
| Variable | Value |
|---|---|
GOOGLE_CLIENT_ID |
From Google Cloud Console OAuth client |
GOOGLE_CLIENT_SECRET |
From Google Cloud Console OAuth client |
GOOGLE_REDIRECT_URI |
https://YOUR-VERCEL-APP.vercel.app/oauth/google/callback |
JWT_SECRET |
A long random string (generate below) |
SPREADSHEET_ID |
Your Google Sheet ID (from the URL) |
Generate a secure JWT secret:
node -e "console.log(require('crypto').randomBytes(32).toString('hex'))"
Get your Spreadsheet ID from the sheet URL:
https://docs.google.com/spreadsheets/d/SPREADSHEET_ID_IS_HERE/edit
⚠️ After adding env vars, you must redeploy for them to take effect:
vercel --prod
Step 6 — Verify deployment
Hit your health endpoint:
https://YOUR-VERCEL-APP.vercel.app/health
Should return:
{ "status": "ok", "message": "Google Sheets MCP OAuth Server" }
Step 7 — Connect to Claude.ai
- Go to claude.ai → Settings → Connectors
- Click Add connector
- Enter:
- Name:
Google Sheets MCP - URL:
https://YOUR-VERCEL-APP.vercel.app
- Name:
- Click Connect
- Google login screen appears → sign in with the account you whitelisted
- Authorize the Sheets scope
- Done — Claude now has access to your sheet ✅
Usage examples
Once connected, just ask Claude naturally:
Read the data in Sheet1!A1:D10
Append a row with ["John", "Doe", "john@example.com"] to Sheet1!A:Z
Update cell Sheet1!B3 to "Completed"
Project structure
├── api/
│ └── oauth.cjs ← Main server (Vercel entry point)
├── public/
│ └── index.html ← Dashboard UI
├── vercel.json ← Vercel routing config
└── package.json
How it works
Claude.ai → POST / (tools/list) → Your Vercel server → returns tool definitions
Claude.ai → GET /oauth/authorize → Redirects to Google login
Google → GET /oauth/google/callback → Issues JWT token back to Claude
Claude.ai → POST / (tools/call) + JWT → Your server → Google Sheets API → data
Troubleshooting
500 FUNCTION_INVOCATION_FAILED
Your package.json likely has "type": "module" — remove it. The server uses CommonJS (require).
"This connector has no tools available"
The tools/list method is behind auth middleware. Make sure it's handled in the unauthenticated first handler.
Error 400: redirect_uri_mismatch
- Check
GOOGLE_REDIRECT_URIin Vercel matches exactly what's registered in Google Console - Make sure you're using the OAuth Client ID, not a service account ID
- Publish your OAuth app in Google Console (Testing mode blocks logins)
"Authorization with the MCP server failed" Disconnect and reconnect the Claude connector to force a fresh token. Cached tokens from failed attempts won't work.
POST returning 404
All JSON-RPC errors must return HTTP 200, not 404. Check that unknown methods return res.status(200).json(...).
Security notes
- Change
MCP_API_KEYfrom any placeholder value before sharing the deployment JWT_SECRETshould be at least 32 random characters- The Spreadsheet ID and OAuth credentials are tied to your Vercel deployment — don't commit
.envfiles - For production use, replace in-memory
pkceStore/tokenStoreMaps with a database (Redis, Upstash, etc.) — they reset on cold starts
License
MIT
Recommended Servers
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.
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.
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.
VeyraX MCP
Single MCP tool to connect all your favorite tools: Gmail, Calendar and 40 more.
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.
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.
E2B
Using MCP to run code via e2b.
Neon Database
MCP server for interacting with Neon Management API and databases
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.
Qdrant Server
This repository is an example of how to create a MCP server for Qdrant, a vector search engine.