Google Sheets MCP Server for AI Agents

Tools your data agent reaches for on Google Sheets, scoped per user.

CALL ANY TOOL

Read and write cell ranges, append rows, list sheets, and apply batch structural updates.

googlesheets_add_banding

Add banding

Apply alternating row colors (banding) to a range in a Google Sheet, using explicit hex colors for the two alternating bands and an optional header row color.

Parameters

Name

Type

Required

Description

end_column_index

integer

Required

Zero-based end column index of the range (exclusive).

end_row_index

integer

Required

Zero-based end row index of the range (exclusive).

first_band_color_hex

string

Required

Hex color for odd-numbered rows in the band.

second_band_color_hex

string

Required

Hex color for even-numbered rows in the band.

sheet_id

integer

Required

The ID of the sheet (tab) containing the range to band.

spreadsheet_id

string

Required

The ID of the Google Sheet to modify

start_column_index

integer

Required

Zero-based start column index of the range (inclusive).

start_row_index

integer

Required

Zero-based start row index of the range (inclusive).

header_color_hex

string

Optional

Optional hex color for the first (header) row of the range, drawn distinct from the alternating bands.

googlesheets_add_chart

Add chart

googlesheets_add_named_range

Add named range

googlesheets_add_protected_range

Add protected range

googlesheets_append_values

Append values

googlesheets_batch_clear_values

Batch clear values

googlesheets_batch_get_values

Batch get values

googlesheets_batch_get_values_by_data_filter

Batch get values by data filter

googlesheets_batch_update_values

Batch update values

googlesheets_batch_update_values_by_data_filter

Batch update values by data filter

googlesheets_clear_basic_filter

Clear basic filter

googlesheets_copy_sheet_to

Copy sheet to

googlesheets_create_developer_metadata

Create developer metadata

googlesheets_delete_banding

Delete banding

googlesheets_delete_conditional_format_rule

Delete conditional format rule

googlesheets_delete_dimension

Delete dimension

googlesheets_delete_embedded_object

Delete embedded object

googlesheets_delete_protected_range

Delete protected range

googlesheets_delete_range

Delete range

googlesheets_find_and_replace

Find and replace

googlesheets_freeze_panes

Freeze panes

googlesheets_get_spreadsheet_by_data_filter

Get spreadsheet by data filter

googlesheets_insert_dimension

Insert dimension

googlesheets_merge_cells

Merge cells

googlesheets_read_spreadsheet

Read spreadsheet

googlesheets_rename_sheet

Rename sheet

googlesheets_search_developer_metadata

Search developer metadata

googlesheets_set_basic_filter

Set basic filter

googlesheets_text_to_columns

Text to columns

googlesheets_update_spreadsheet_properties

Update spreadsheet properties

For more tools, view docs.

Build your Agent

Drop the toolkit in, point it at the user, and your data agent can use Google Sheets from the first run.

import { ScalekitClient } from "@scalekit-sdk/node";
import { DynamicStructuredTool } from "@langchain/core/tools";
import { createReactAgent } from "@langchain/langgraph/prebuilt";
import { z } from "zod";

const sk = new ScalekitClient(envUrl, clientId, clientSecret);

const { tools } = await sk.tools.listScopedTools("user_123", {
  filter: { connectionNames: ["googlesheets"], toolNames: ["gsheets_spreadsheet_get", "gsheets_values_get", "gsheets_values_update"] },
  pageSize: 100,
});

const lcTools = tools.map((t) => new DynamicStructuredTool({
  name: t.tool.definition.name,
  description: t.tool.definition.description,
  schema: z.object({}).passthrough(),
  func: async (args) => {
    const { data } = await sk.tools.executeTool({
      toolName: t.tool.definition.name,
      identifier: "user_123",
      params: args,
    });
    return JSON.stringify(data);
  },
}));

const agent = createReactAgent({ llm, tools: lcTools });

import { ScalekitClient } from "@scalekit-sdk/node";
import OpenAI from "openai";

const sk = new ScalekitClient(envUrl, clientId, clientSecret);
const openai = new OpenAI();

const { tools } = await sk.tools.listScopedTools("user_123", {
  filter: { connectionNames: ["googlesheets"], toolNames: ["gsheets_spreadsheet_get", "gsheets_values_get", "gsheets_values_update"] },
  pageSize: 100,
});

const llmTools = tools.map((t) => ({
  type: "function",
  function: {
    name: t.tool.definition.name,
    description: t.tool.definition.description,
    parameters: t.tool.definition.input_schema,
  },
}));

const resp = await openai.responses.create({
  model: "gpt-4o", input: prompt, tools: llmTools,
});

import { ScalekitClient } from "@scalekit-sdk/node";
import Anthropic from "@anthropic-ai/sdk";

const sk = new ScalekitClient(envUrl, clientId, clientSecret);
const anthropic = new Anthropic();

const { tools } = await sk.tools.listScopedTools("user_123", {
  filter: { connectionNames: ["googlesheets"], toolNames: ["gsheets_spreadsheet_get", "gsheets_values_get", "gsheets_values_update"] },
  pageSize: 100,
});

const llmTools = tools.map((t) => ({
  name: t.tool.definition.name,
  description: t.tool.definition.description,
  input_schema: t.tool.definition.input_schema,
}));

const msg = await anthropic.messages.create({
  model: "claude-sonnet-4-6", max_tokens: 1024,
  tools: llmTools,
  messages: [{ role: "user", content: prompt }],
});

import { Agent } from "@google/adk/agents";
import {
  MCPToolset, StreamableHTTPConnectionParams,
} from "@google/adk/tools/mcp";

const toolset = new MCPToolset({
  connectionParams: new StreamableHTTPConnectionParams({
    url: "https://mcp.scalekit.com/googlesheets",
    headers: { Authorization: `Bearer ${userScopedToken}` },
  }),
});

const agent = new Agent({
  name: "agent", model: "gemini-2.0-flash",
  tools: await toolset.getTools(),
});

Try these prompts

Paste any prompt into your agent to start using Google Sheets.

Read & analyze

Copy the prompt

Copied

Read [range] from [sheet name].

Copy the prompt

Copied

Get all rows in [sheet] where [column] equals [value].

Copy the prompt

Copied

Sum column [name] in [sheet].

Copy the prompt

Copied

List all sheet tabs in [spreadsheet].

Write & update

Copy the prompt

Copied

Append a new row to [sheet]: [values].

Copy the prompt

Copied

Update cell [A1] in [sheet] to [value].

Copy the prompt

Copied

Write [data] to range [A1:D10] in [sheet].

Copy the prompt

Copied

Clear range [A2:Z100] in [sheet].

Reporting & sync

Copy the prompt

Copied

Read the pipeline tracker and list deals closing this month.

Copy the prompt

Copied

Export [sheet] data as a summary.

Copy the prompt

Copied

Find all rows where [column] is empty.

Copy the prompt

Copied

Compare [Sheet1] and [Sheet2] for differences.

SEE HOW AUTH WORKS

Users authorize Google Sheets once. Their credentials stay vaulted, every call is checked, and every action is logged.

Authorize

Your user connects

Google Sheets

once. We tie it to their identity and the meetings they approved — no shared bot account, no org-wide access

Who:

user ‘A’

when:

Once per user

access:

Limited to user

Store

Their

Google Sheets

token lives in a vault scoped to them. User A's meetings are never reachable by an agent acting for user B, even on the same connection

vault:

encrypted

scope:

per-user

tokens:

auto-refreshed

Resolve

When your agent calls a

Google Sheets

tool, we fetch the right token server-side. It never touches your agent, never appears in the LLM context, never shows up in your logs

speed:

~40ms

check:

before every call

seen by:

nobody

Audit

Every

Google Sheets

tool call is logged — who triggered it, which meeting was fetched, what came back. 90 days of history, tied to the user who authorized it

history:

90 days

export:

SIEM-ready

logged:

every call

Test other agents

Same per-user auth pattern across other data agents and MCP connectors. Working code, live demos, fork what fits.

GTM and RevOps Teams

Revenue forecast commentary

Pulls open pipeline from Salesforce and HubSpot, calculates coverage against quota, flags at-risk stages, posts commentary to Slack, and logs every snapshot to Google Sheets.

GTM and RevOps Teams

Outbound prospecting agent

Searches Apollo for prospects matching your ICP, scores and ranks them, drafts personalized outreach in Gmail, and logs every send to Google Sheets. Mail goes out as the rep, not from a shared inbox.

GTM and RevOps Teams

Competitive intelligence briefing agent

Scans Gong calls for competitor mentions, matches each one to its Notion battlecard, and DMs every affected rep a single Slack digest per cycle. Every call runs as the PMM who owns the briefing, never a shared bot.

GTM and RevOps Teams

Deal room sync

Pulls opportunity context from Salesforce, captures key decisions from Slack, and syncs a running summary to the deal room doc in Google Drive, but only when the deal actually changed.

Why Scalekit

Secure your agent's access. Connectors ship in minutes

01.

Shared tokens break per-user analytics

A shared token looks fine in a demo. In production every call looks like a service account. Scalekit resolves the real user credential so attribution, audit, and scope stay accurate.

// shared token
 audit → bot_service_account
 user_filter → broken

 // scalekit
 audit → user_abc
 scope → enforced ✓

02.

Authentication is not authorization

03.

Multi-tenancy is architectural

04.

Google Sheets today. Others tomorrow.

“Our agents act across Salesforce, Gong, Google Drive, and more, on behalf of every customer. Scalekit behind the scenes meant we can keep adding tools without ever rebuilding how credentials or tool calling work.”

Venu Madhav Kattagoni

Head of Engineering / Von

FAQs

Frequently Asked Questions

Does the agent access Google Sheets as the user or as a shared key?

As the user. Each workspace member authorizes once and Scalekit resolves their credential at request time. Audit logs attribute every action to that user, not a shared service account.

Where is the Google Sheets oauth 2.0 stored?

In Scalekit's managed AES-256 token vault, namespaced per tenant. Refresh is automatic. Revocation is a single dashboard action. Tokens never appear in prompts, logs, or LLM context.

Can I limit what the agent is allowed to do in Google Sheets?

Yes. Pass a tool name filter to listScopedTools so the data agent only sees the subset you authorize. Pre-API-call scope checks block out-of-policy actions before the request reaches Google Sheets.

What happens when a user revokes Google Sheets access?

The connection is invalidated on the next tool call. Subsequent requests for that user fail closed with a clear error. Other users in the tenant remain unaffected. The event is logged for audit.

Can the agent overwrite cells in a spreadsheet the user has view access to?

No. Write operations require editor access. View-only access blocks all updates and appends. The agent inherits the exact edit rights the user has on each spreadsheet.

What other MCP connectors does Scalekit support?

Scalekit runs the Google Slides MCP server, Notion MCP server, and Google Drive MCP server on the same per-user auth, token vault, and audit trail. Browse 500+ connectors in the MCP connector directory.

On this page

Tool and actions Framework Compatibility Starter Prompt Auth Lifecycle Try Other Agents Why Scalekit