Google Sheets MCP for AI. Manage every cell, tab, and piece of data conversationally.

Q: How does sheets.batchread work for multiple tabs?

sheets.batchread lets you list several ranges separated by commas (e.g., 'Sheet1!A1:B10, Sheet2!C1:D10'). It pulls all the data from those distinct locations in one single API call.

Q: Should I use sheets.write or sheets.append?

Use sheets.write when you need to completely overwrite a specific area of existing data. Use sheets.append only when you are adding new records and want to guarantee they go at the end.

Q: What if I need to know what sheets exist in my workbook?

You use sheets.info. This command fetches metadata for the entire file, giving you a full list of all sheet tabs and their dimensions so you know exactly what's inside.

Claude

ChatGPT

Cursor

Gemini

Windsurf

VS Code

JetBrains

Vercel

See Vinkius in Action

Works with every AI agent you already use

…and any MCP-compatible client

Connect to your AI in seconds.

Google Sheets (OAuth) lets your agent read, write, create, and manage any spreadsheet data directly from natural language conversation. You can pull data from multiple ranges across different tabs in one go, append new records without deleting old ones, or even audit the sheet's metadata—all without opening Google Drive.

It gives you full control over complex, multi-tab datasets.

What your AI can do

Sheets.info

Retrieves metadata about the entire spreadsheet, including its title, timezone, and all sheet tabs present.

Sheets.read

Pulls cell values from a single, defined range using A1 notation (e.g., Sheet1!A1:D10).

Sheets.batch read

Reads content from multiple, separate ranges across different sheets in one efficient call.

+ 4 more capabilities included

Create new spreadsheets

Starts a blank Google Sheets document instantly using only a title.

Read specific cell values

Pulls data from precise ranges across the sheet, allowing you to focus on exactly what you need.

Batch read multiple sheets

Retrieves content from several different sections or tabs in one efficient request.

Overwrite data ranges

Writes new values into a specific area of the sheet, replacing whatever was there before.

Append new rows

Adds new rows to the bottom of existing data without deleting or overwriting anything above it.

Clear cell contents

Wipes out values from a specified range while keeping all formatting and formulas intact.

Audit sheet details

Gathers metadata like the title, timezone, and list of all tabs within the spreadsheet.

Ask an AI about this

Included with Plan

Waiting for input…

AI Agent

Google Sheets (OAuth) with 7 Tools

These tools give your agent granular control over every aspect of a spreadsheet, from simple reading to complex batch operations.

Make your AI actually useful.

Add this MCP to Claude, Cursor, or Windsurf and your AI stops guessing. It gets real tools to look things up, take action, and handle the stuff you keep doing by hand.

Start using Google Sheets (OAuth) on Vinkius

Sheets.info

Retrieves metadata about the entire spreadsheet, including its title, timezone, and all sheet tabs present.

Sheets.read

Pulls cell values from a single, defined range using A1 notation (e.g....

Sheets.batch Read

Reads content from multiple, separate ranges across different sheets in one...

Sheets.write

Updates existing data in a specified sheet range, replacing the old content with new...

Sheets.append

Adds new rows of data to the bottom of a sheet table without deleting any existing...

Sheets.clear

Removes all values within a specified range, keeping the formatting and formulas structure untouched.

Sheets.create

Generates a brand-new Google Sheets file instantly with just a title you provide.

Security and governance baked right in.

Pick your AI client below to get set up. Just create a Vinkius account, subscribe, and you're instantly up and running. We handle the entire backend infrastructure, delivering out-of-the-box support for HTTPS Streamable, SSE, and OAuth2—zero messy routing required.

Claude AI

Open Claude Settings

Go to claude.ai, click your profile icon, then navigate to Customize → Connectors.

Add Custom Connector

Click the "+" button and select Add custom connector. Paste your Vinkius endpoint URL:

https://edge.vinkius.com/[YOUR_TOKEN_HERE]/mcp

Replace [YOUR_TOKEN_HERE] with your token from cloud.vinkius.com. For OAuth-protected servers, expand Advanced settings to add credentials.

Start a conversation

Open a new chat. The Google Sheets integration is available immediately — no restart needed.

Antigravity

Configure Agent Environment

Open your Antigravity agent's workspace configuration or mcp-servers.json file.

Bind the Endpoint

Add the Vinkius endpoint URL to your agent's MCP connections list:

"mcp_servers": {
  "google-sheets-oauth": {
    "serverUrl": "https://edge.vinkius.com/[YOUR_TOKEN_HERE]/mcp"
  }
}

Provide your secure token in place of [YOUR_TOKEN_HERE] to ensure your agent requests are authenticated.

Execute

Start your Antigravity session. The agent will autonomously discover and utilize the Google Sheets tools with full Vinkius guardrails applied.

VS Code Copilot

⚡

One-Click Install (Recommended)

In your Vinkius Dashboard, simply click the Add to VS Code button for this server. We'll automatically configure your local workspace.

Or configure manually

Open MCP Settings

Open VS Code, press Ctrl/Cmd + Shift + P, and search for GitHub Copilot: MCP Servers.

Add Server Config

Add the Vinkius endpoint configuration to your mcp-servers.json file:

"google-sheets-oauth": {
  "url": "https://edge.vinkius.com/[YOUR_TOKEN_HERE]/mcp"
}

Ensure you replace [YOUR_TOKEN_HERE] with your token from cloud.vinkius.com.

LangChain

Install Dependencies

Install the LangChain MCP adapters for your environment:

pip install langchain-mcp-adapters

Connect the Server

Use the SSEClient in LangChain to connect to the Vinkius managed endpoint:

from langchain_mcp_adapters.client import SSEClient

# Connect to Vinkius
client = SSEClient(url="https://edge.vinkius.com/[YOUR_TOKEN_HERE]/mcp")
tools = client.get_tools()

CrewAI

Define the Tool

Load the Vinkius MCP tools into your CrewAI agents:

from crewai import Agent
from mcp_crewai import MCPTool

# Connect securely to Vinkius
vinkius_tools = MCPTool(url="https://edge.vinkius.com/[YOUR_TOKEN_HERE]/mcp")

# Assign to Agent
researcher = Agent(
    role='Data Researcher',
    tools=vinkius_tools.get_all()
)

Execute Task

Run your CrewAI process. The agent will autonomously route tasks to the Vinkius managed server.

Choose How to Get Started

Build a custom MCP for your own tools, or connect a ready-made integration from our catalog.

Build Your Own

Turn any API into an MCP. Import a spec, define Agent Skills, or deploy with MCPFusion.

Import from OpenAPI, Swagger, or YAML specs
Create Agent Skills with progressive disclosure
Deploy to edge with MCPFusion framework
Built in DLP, auth, and compliance on every call
Real time usage dashboard and cost metering
Publish to catalog or keep private

Start building

Make Your AI Do More

Start with Google Sheets (OAuth), then connect any of our 5,100+ other servers whenever your AI needs more. One click, no limits.

Use this MCP plus 5,100+ others, all in one place
Add new capabilities to your AI anytime you want
Every connection is secured and compliant automatically
Track usage and costs across all your servers
Works with Claude, ChatGPT, Cursor, and more
New servers added to the catalog every week

Independent Platform Disclaimer: Vinkius is an independent platform and is not affiliated with, endorsed by, sponsored by, verified by, or otherwise authorized by Google Sheets. All third-party trademarks, logos, and brand names are the property of their respective owners. Their use on this website is strictly for informational purposes to identify service compatibility and interoperability.

VINKIUS INFRASTRUCTURE

Cloud Hosted

Managed infra

V8 Isolated

Sandboxed per request

Zero-Trust Proxy

No stored credentials

DLP Enforced

Policy on every call

GDPR Compliant

EU data residency

Token Compression

~60% cost reduction

Your data is protected. See how we built it.

Works with Claude, ChatGPT, Cursor, and more

The Model Context Protocol standardizes how applications expose capabilities to LLMs. Instead of operating in isolation, your AI gains direct access to external platforms, live data, and real-world actions through secure, standardized connections.

This connection provides 7 powerful capabilities that interface natively with Claude, ChatGPT, Cursor, and other compatible AI platforms. No middleware. No custom integration required.

The Pain of Manual Spreadsheet Data Management

Right now, updating a complex report means opening Google Sheets and manually jumping between tabs. You copy numbers from one section to paste them into another, then you have to scroll up, find the right spot, and paste again. If you're cross-referencing multiple data sets, this is hours of clicking through interfaces and dealing with version control headaches.

With this MCP, that process disappears. You tell your agent what data you need—say, 'The sales numbers from Q2 and the marketing spend from last month.' The agent executes a single command, pulling all necessary ranges instantly, and returns the structured comparison right to your chat window.

Writing Data Directly into Sheets with sheets.write

Today, if you want to update a sheet, you have to open it, find the cell, and manually type or paste the new value. If you're writing complex formulas or multiple rows of data, the risk of placing it in the wrong spot is high.

Now, you simply tell your agent to write the values, providing the two-dimensional array. The MCP handles the precise placement into the target range, keeping everything locked down and accurate.

Support 24/7 support@vinkius.com ↗

Security Vinkius Trust Center ↗

SLA Service Level Agreement ↗

Report Listing Send Report ↗

What your AI can actually do with this

Managing spreadsheets usually means clicking through dozens of tabs and copy-pasting data sets until you find what you need. This MCP changes that. You connect your Google Sheets account via OAuth2 to any agent and treat the entire spreadsheet as a single database. Need to pull sales figures from 'Q1' and compare them against inventory levels in 'Stock'? Your agent handles it, pulling both datasets simultaneously so you can analyze complex dependencies right away.

Want to log ten new records at once? You just tell your agent what needs appending; it adds the data cleanly to the bottom of the table without messing up anything already there. If you're working with Vinkius, this MCP gives your client immediate access to all that sheet power, making data manipulation a simple conversation.

Beyond reading and writing, you can command it to create brand-new spreadsheets for specific projects or simply audit the file—checking its timezone, locale, or listing every sheet tab inside. It handles everything from basic data entry to complex batch processing with precision.

Built · Hosted · Managed by Vinkius Google Sheets MCP - Read, Write, Append Data

Server ID 019eb900-82d7-7208-a05b-3447b5994b69

Vinkius Inspector

Compliance Grade A+

Score 100/100

Report View Report ↗

What Changes When You Connect

Stop reading single ranges manually. Use sheets.batch_read to pull necessary data from multiple tabs or sections in one go, speeding up cross-sheet analysis dramatically.

Need to log new records? Instead of risking overwriting old data with sheets.write, use sheets.append to safely add rows to the bottom of your table every time.

Start a fresh project instantly. Use sheets.create when you need a clean slate, giving you a brand-new spreadsheet ID and edit link immediately.

Before running any big update, check the file's health using sheets.info. This lets you audit critical metadata like timezones or sheet tabs without opening anything.

Accidentally wrote over data? Use sheets.clear to zero out values in a specific area without touching the underlying formulas or formatting.

See it in action

01 01

The Monthly Financial Reconciliation

A financial analyst needs to pull the current month's sales data (Sheet 1: A2:Z50) and compare it against last year’s budget figures (Sheet 3: B2:K40). Instead of running two separate API calls, they tell their agent to sheets.batch_read both ranges simultaneously, getting a unified dataset for comparison.

02 02

The Project Tracker Update

A product manager has 15 new project milestones and needs to log them into the master tracker. They instruct their agent to sheets.append these records; the MCP ensures they are added cleanly to the bottom of the 'Milestones' tab without disrupting existing data.

03 03

The Clean-Up Job

An ops engineer needs to reset a reporting sheet before starting fresh, but must keep the formulas. They tell their agent to use sheets.clear on the main data block, which removes values while preserving all formatting and structure.

04 04

The Audit Check

A team needs to know if the master spreadsheet is using the right time zone for reporting. They ask their agent to use sheets.info on the file ID, instantly confirming the locale and timezone without opening the file.

The honest tradeoffs

Overwriting data when you should be adding it.

Anti-pattern

Trying to dump a list of 20 new customer IDs into A1, but using sheets.write on the entire column range. This wipes out all the old data that was in there.

The Fix

If your goal is simply to add rows at the end of the table, you must use sheets.append. This tool adds records without touching anything already written.

Trying to read complex data across multiple sources.

Anti-pattern

Calling sheets.read once for Sheet 1 and then calling it again for Sheet 2, requiring the agent to run two separate commands just to get a comparison set of data.

The Fix

Use sheets.batch_read. This single command allows you to define multiple ranges (e.g., 'Sheet1!A:B, Sheet2!C:D') and retrieve all the necessary content in one go.

Deleting a whole sheet when only some values need clearing.

Anti-pattern

The user mistakenly tells the agent to clear the entire sheet name ('Sheet1'), which might wipe out useful formulas or headers that were meant to stay.

The Fix

To safely remove content, use sheets.clear and specify a precise range (e.g., 'A2:Z50'). This removes only the values while protecting surrounding structure.

When It Fits, When It Doesn't

Use this MCP if your workflow involves manipulating data inside Google Sheets, and you want to do that purely through conversational commands. It's perfect for structured CRUD tasks—you need to read ranges (sheets.read), add new rows (sheets.append), or update specific cells (sheets.write). Don't use it if you are trying to build a whole database from scratch; Sheets is an analysis tool, not a primary data store. Also, don't rely on it for complex logic that needs validation (like checking cross-field dependencies). That requires external code after the agent pulls the raw data using sheets.batch_read. If you just need to know basic file info, sheets.info is your quick check.

Questions you might have

How does sheets.batch_read work for multiple tabs? +

sheets.batch_read lets you list several ranges separated by commas (e.g., 'Sheet1!A1:B10, Sheet2!C1:D10'). It pulls all the data from those distinct locations in one single API call.

Should I use sheets.write or sheets.append? +

Use sheets.write when you need to completely overwrite a specific area of existing data. Use sheets.append only when you are adding new records and want to guarantee they go at the end.

What if I need to know what sheets exist in my workbook? +

You use sheets.info. This command fetches metadata for the entire file, giving you a full list of all sheet tabs and their dimensions so you know exactly what's inside.

Can I create new sheets using sheets.create? +

Yes. You just tell your agent the desired title for the new spreadsheet, and it generates the file ID and a direct link for you to use immediately.

How do I use sheets.write to update a specific cell range without affecting other data? +

sheets.write overwrites existing values in a defined A1 range. You must provide the exact coordinates (e.g., 'Sheet1!B5:C7') and the new data array. Always confirm with your user before running this, as it deletes whatever content was previously there.

If I only need to read a small section of a sheet, should I use sheets.read or sheets.batch_read? +

Use sheets.read for single ranges and specific coordinates; it's simpler than batch reading. Specify the range using standard A1 notation (e.g., 'SheetName!A1:B5'). If you need data from multiple, non-contiguous areas, then sheets.batch_read is better.

What are the safety precautions before running sheets.clear? +

sheets.clear removes cell contents but preserves formatting and formulas. Because this action is irreversible, you must confirm with your user first. You can target a specific range or clear an entire sheet by providing just the sheet name.

What kind of general metadata can I pull using sheets.info? +

sheets.info pulls core spreadsheet details, including the title, locale, and timezone. It's useful for auditing or setting up context before manipulating data. You pass either a full URL or just the ID to get this system information.

How do I get a Google OAuth2 access token for this server? +

You can use the Google OAuth Playground (select Sheets API v4 and authorize) or run 'gcloud auth print-access-token' in your terminal. Note that these tokens are typically valid for 1 hour.

Can my agent create a new spreadsheet and add data to it in one go? +

Yes. The agent can orchestrate multiple operations. First, use 'create_spreadsheet' to get the new ID, and then use 'write_data' or 'append_data' to populate it with your JSON arrays natively.

What is the benefit of batch reading through the agent? +

Batch reading allowing your agent to retrieve data from multiple non-contiguous ranges (e.g., 'Sheet1!A1:B10' and 'Sheet2!C5:D15') in a single request, improving context efficiency and reasoning accuracy flawlessly.

Connect to your AI in seconds.

Sheets.info

Sheets.read

Sheets.batch read

Google Sheets (OAuth) with 7 Tools

Make your AI actually useful.

Sheets.info

Sheets.read

Sheets.batch Read

Sheets.write

Sheets.append

Sheets.clear

Sheets.create

Security and governance baked right in.

Claude AI

Open Claude Settings

Add Custom Connector

Start a conversation

Claude Code

Open your terminal

Add the MCP Server

Start coding

Cursor

One-Click Install (Recommended)

Open Cursor Settings

Add New Server

Use in Composer

Antigravity

Configure Agent Environment

Bind the Endpoint

Execute

VS Code Copilot

One-Click Install (Recommended)

Open MCP Settings

Add Server Config

Windsurf

One-Click Install (Recommended)

Open Windsurf Settings

Add Server Endpoint

LangChain

Install Dependencies

Connect the Server

CrewAI

Define the Tool

Execute Task

Choose How to Get Started

Build Your Own

Make Your AI Do More

Works with Claude, ChatGPT, Cursor, and more

The Pain of Manual Spreadsheet Data Management

Writing Data Directly into Sheets with sheets.write

What your AI can actually do with this

Here's how it actually works

Who is this actually for?

What Changes When You Connect

See it in action

The Monthly Financial Reconciliation

The Project Tracker Update

The Clean-Up Job

The Audit Check

The honest tradeoffs

Overwriting data when you should be adding it.

Trying to read complex data across multiple sources.

Deleting a whole sheet when only some values need clearing.

When It Fits, When It Doesn't

Questions you might have