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Chat agent that answers questions about one Google Sheet

by Mindketn8n workflowProductivity
Newversion 1 · updated
Nodes14Apps2Like

Overview

  1. Execute Workflow Trigger
  2. List columns tool
  3. Get customer tool
  4. Get column values tool
  5. OpenAI Chat Model
  6. Chat Trigger
  7. Set Google Sheet URL
  8. AI Agent
  9. Get Google sheet contents
  10. Check operation
  11. Get column names
  12. Prepare column data
  13. Filter
  14. Prepare output
Chat agent that answers questions about one Google Sheet, picture 1
‹2 / 2›

An n8n workflow with a chat box and an AI agent that answers questions about a customer table in one Google Sheet. It reads only the columns and rows it needs, through three small tools.

Chat agent that answers questions about one Google Sheet is an n8n workflow in the Productivity category, listed by Mindket. It is free. This is version 1, last updated on . Download it on this page or copy its JSON, then import it into an n8n canvas. Nothing runs until you activate it in n8n.

At a glance

Runs in
  • n8n Cloud: bring in the file, connect your accounts, save it and chat
  • Your own n8n server: the same file
  • A local install: it runs the same, because Google and OpenAI are reached over the internet
  • A public chat link: possible, but think first about who gets it

Platform

n8nWorkflow automation, in n8n’s cloud or on your own server
Connects 2 apps

How it works

Trigger

A chat message

It starts when someone types in the chat at the bottom of the canvas. Set first:

  • A Google Sheets credential
  • The sheet’s address in Set Google Sheet URL
  • An OpenAI credential

Actions

  1. The agent reads the question and picks a tool
  2. One tool lists the column names of the sheet
  3. A second tool returns one column for every row, with each row’s number
  4. A third tool returns every column of one row, picked by its number
  5. The agent turns the tool results into an answer in the chat

Result

An answer in the chat, built from the rows and columns of your sheet

Integrations

What you need before you start.

Google Sheets

Data source

Is read in full by each tool call, then cut down to the names, one column or one row.

NeedsGoogle Sheets credential and the sheet’s address

OpenAI

Language model

Runs the agent that picks the tools and writes the answer.

NeedsOpenAI API key

Workflow check

Checked by Mindket on 13 Nov 2026

Steps
10 steps, starting when another workflow calls it or on a chat message
AI
1 step calls an AI model: AI Agent
Sign-ins
Signs in to: Google Sheets and OpenAI
API keys
No API key is left in the file
Step types
Mindket’s checker reads all 8 of its step types

Read from the workflow’s file, not from a run.

About

What it is

This n8n workflow lets you question a table in a Google Sheet by typing in a chat box. An AI agent reads your question and picks one of three small tools. One lists the column names. One returns a single column for every row. One returns every column of one row. The agent joins what they return into an answer, so the model sees only the pieces it asks for. Fourteen nodes run it. Five sticky notes sit beside them.

Who it suits

Owners and teams who keep customers, orders or stock in a spreadsheet and want to ask it plain questions, such as who buys the most. It suits a table of a few hundred rows under one header row. Skip it for a huge sheet, because each call to a tool reads the whole tab again. Skip it too when you need sums you can trust to the cent, since a language model can slip on arithmetic.

Who uses it, and how
IndustryWho uses itHow they use itExample
Small businessShop ownersAsk which customers spend the mostAn owner asks which customer is the biggest and gets a name and a figure.
SalesAccount managersLook up one customer’s details without opening the sheetA manager asks for everything on row 14 before a call.
OperationsOffice managersCheck one value across a whole columnA manager asks which orders still show the status open.
EducationCourse administratorsQuestion a list of sign-upsAn administrator asks who signed up for the evening class.

You need an n8n, a Google account that can open your sheet and an OpenAI key.

Where to use it

Any n8n that can reach Google and OpenAI will run it. The chat opens inside the n8n editor, so it suits people who work there. To let others chat, turn on Make Chat Publicly Available in Chat Trigger. Anyone who then has the link can ask about your sheet.

  • n8n Cloud: bring in the file, connect your accounts, save it and chat
  • Your own n8n server: the same file
  • A local install: it runs the same, because Google and OpenAI are reached over the internet
  • A public chat link: possible, but think first about who gets it

Setup

Download saves a zip with workflow.json and Mindket’s setup notes in your downloads folder. Import the file, paste your sheet’s address, add two credentials and save the workflow before you chat. That is all.

What you need first
NeedDetail
n8nOn n8n Cloud or on a server of your own
Google SheetsA Google account that can open the sheet, with an OAuth2 credential
SheetOne header row, then one customer per row
OpenAIAn API key
  1. In n8n, create a workflow, open its menu, choose Import from File and pick workflow.json.
  2. In Set Google Sheet URL, replace <YOUR_GOOGLE_SHEET_URL> with the address of your sheet as your browser shows it, with the #gid= part, so the right tab is read.
  3. Add a Google Sheets OAuth2 credential to Get Google sheet contents.
  4. Add an OpenAI credential to OpenAI Chat Model.
  5. Save the workflow before you chat. The three tools call this same workflow by its saved id, and a copy that was never saved has none.
  6. Open the chat at the bottom of the canvas and ask a question, such as which customer is the biggest.

How to use it

Open the chat and type a question. The agent starts by listing the columns, then fetches only the columns and rows that your question needs. Use the same words as your column names. Short questions work best. Each message is answered alone, so name the customer again when you ask a follow-up.

What to change for a different result
To changeWhere
The sheetsheetUrl in Set Google Sheet URL
How the agent answersThe system message in AI Agent
The modelOpenAI Chat Model
What each tool is forThe description in each of the three tool nodes
Who can chatMake Chat Publicly Available in Chat Trigger

Example

A shop owner keeps her customers in a sheet with columns for name, city and total spent. She types which customer spent the most.

The agent lists the columns, asks for the total spent column across all rows and finds the highest figure. It then fetches that customer’s row by its number and answers with the name, the city and the amount. It takes seconds. When she asks where another customer lives, she must name that customer, because the chat keeps no memory of the last answer.

For newcomers and experts

If you are new. n8n draws a workflow as boxes joined by lines, and each box, a node, does one job. An agent is a model that decides which tool to use. A tool here is a small workflow that the agent can call. A row number is the number printed at the left edge of the sheet. Nothing here is hard.

For experts. The three tools are one sub-workflow called three times, each with its own operation field. Nothing else changes between them.

Where to look closer
NodeWhat it doesWhat to know
Get customer toolCalls this same workflow with operation set to rowThe workflow is called by its id, so it must be saved first. The agent passes one text input as query
Get Google sheet contentsReads the tab with Get Row(s)It adds row_number, the row’s place in the tab, so the first customer is row 2
Check operationSwitches on the operation fieldThree outputs: col names, col values and rows
FilterKeeps the row whose row_number equals the queryThe comparison is loose, so the text 14 matches the number 14
Prepare outputJoins every item into one JSON text in responseA large table gives a large text, which counts against the model’s context

Good to know

Each question reads the sheet again. The agent knows only what the tools hand back.

  • Size: the tab is read in full on each call. A few hundred rows are fine. column_values sends back one column of every row
  • Column list: Get column names runs once per row, so the list comes back once per row. The agent gets the same list many times on a long sheet
  • Row numbers: row_number is a row’s place in the tab, not a customer number. The agent learns it from column_values, then asks get_customer for that row
  • No memory: the agent has no memory node, so every message stands alone
  • Repairs: the original copy ran gpt-3.5-turbo-0125 in a ReAct agent. OpenAI shut gpt-3.5-turbo down on 23 October 2026 and names gpt-5.6-terra as the replacement. Mindket’s copy uses gpt-5.6-terra in a Tools Agent, because OpenAI’s page for it lists function calling but no stop setting, and it drops the temperature setting for the same reason. The sheet address became a placeholder
  • Cost: gpt-5.6-terra costs USD 2 per million tokens in and USD 12 per million out on OpenAI’s page of 12 November 2026. Each message can trigger several tool calls
  • Not run: nothing was run against a live sheet or against OpenAI. The notes come from n8n’s source and OpenAI’s pages
  • Your data: the column names and the rows the tools return go to OpenAI as part of the chat
  • Credentials: the JSON holds none

README and files

README

Chat agent that answers questions about one Google Sheet

An n8n workflow with a chat box and an AI agent that answers questions about a customer table kept in one Google Sheet.
The agent reads the table through three small tools, so it asks for only the columns and rows it needs.

What is inside

  • workflow.json: the workflow as n8n exports it, 14 nodes and 5 sticky notes. It holds no credential.
  • README.md: these notes.

What we changed from the original copy

  • The agent ran gpt-3.5-turbo-0125 with its temperature at 0. OpenAI shut gpt-3.5-turbo down on 23 October 2026 and
    names gpt-5.6-terra as the replacement. The model node now runs gpt-5.6-terra, and the temperature setting is
    gone, because OpenAI's page for that model lists no temperature setting.
  • The agent was a ReAct agent, which asks the model to stop at a marker word. OpenAI's page for gpt-5.6-terra lists
    function calling but no stop setting, so the agent is now a Tools Agent. The line that told the old agent to call
    list_columns first moved into its system message.
  • Set Google Sheet URL held the original author's sheet address. It now reads <YOUR_GOOGLE_SHEET_URL>.

Before you start

  • An n8n instance, on n8n Cloud or your own server.
  • A Google account that can open your sheet, and a Google Sheets OAuth2 credential in n8n.
  • An OpenAI API key.
  • A sheet with one header row and one customer per row. Any other kind of table works too, because the tools read column
    names, not fixed fields.

Set it up

  1. In n8n, create a workflow, open its menu, choose Import from File and pick workflow.json.
  2. In Set Google Sheet URL, replace <YOUR_GOOGLE_SHEET_URL> with the address of your sheet as your browser shows it,
    with the #gid= part, so the right tab is read.
  3. Add a Google Sheets OAuth2 credential to Get Google sheet contents.
  4. Add an OpenAI credential to OpenAI Chat Model.
  5. Save the workflow before you chat. The three tools call this same workflow by its saved ID, and a copy that was
    never saved has none.
  6. Open the chat at the bottom of the canvas and ask a question, such as which customer is the biggest.

How a run goes

  1. Chat Trigger passes each chat message to AI Agent, which runs on OpenAI Chat Model. The agent has no memory, so
    every message is answered alone.
  2. The agent has three tools: list_columns, get_customer and column_values. Each one is a Call n8n Workflow Tool
    that calls this same workflow. It sends the agent's text as query and its own fixed operation field.
  3. A tool call starts at Execute Workflow Trigger. Set Google Sheet URL sets sheetUrl, and `Get Google sheet
    contents reads the tab. That node uses the Get Row(s) operation, which is its default, and adds a row_number`
    column. Row 1 is the header, so the first customer is row 2.
  4. Check operation sends the call down one of three branches.
    - col names: Get column names returns the names of the columns.
    - col values: Prepare column data keeps the column the agent asked for, plus row_number, for every row.
    - rows: Filter keeps the one row whose row_number equals the query.
  5. Prepare output turns what is left into one JSON text in response, which goes back to the agent as the tool's answer.

Change the look

  • The sheet: sheetUrl in Set Google Sheet URL.
  • What the agent knows and how it answers: the system message in AI Agent.
  • The model: OpenAI Chat Model.
  • What each tool is for: the description in each of the three tool nodes. The agent reads them to choose a tool.
  • Who can chat: only you, in the editor, until you turn on Make Chat Publicly Available in Chat Trigger.

Good to know

  • The facts below come from n8n source and OpenAI pages read on 12 November 2026. Nothing was run against a live sheet
    or against OpenAI.
  • Every tool call reads the whole tab again. That suits a table of a few hundred rows. A sheet of many thousand rows is slow,
    and column_values sends back one column of every row.
  • The column list is returned once per row, because Get column names runs for each row. On a long sheet the agent
    gets the same list many times.
  • row_number is the row's place in the tab, not a customer number. The agent learns it from column_values, then asks
    get_customer for that row.
  • gpt-5.6-terra costs USD 2 per million tokens in and USD 12 per million out on OpenAI's page. Reasoning tokens count
    as output. Each chat message can trigger several tool calls, and each reads the sheet.
  • Your data: the column names and the rows the tools return go to OpenAI as part of the chat.
  • Credentials: the JSON holds none.
Files
NOTICE.md  600 B
README.md  5 KB
workflow.json  15 KB

3 files, 20 KB, downloaded as a zip.

What’s new

  • Version 1 · 2026-11-12

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