This workflow follows the Agent → Chat Trigger recipe pattern — see all workflows that pair these two integrations.
The workflow JSON
Copy or download the full n8n JSON below. Paste it into a new n8n workflow, add your credentials, activate. Full import guide →
{
"id": "ZVUQL1bUQ8gBCZTl",
"name": "Chat with Google Sheet",
"tags": [],
"nodes": [
{
"id": "89af21df-1125-4df6-9d43-a643e02bb53f",
"name": "Execute Workflow Trigger",
"type": "n8n-nodes-base.executeWorkflowTrigger",
"position": [
540,
1240
],
"parameters": {},
"typeVersion": 1
},
{
"id": "f571d0cc-eb43-46c9-bdd5-45abc51dfbe7",
"name": "Sticky Note1",
"type": "n8n-nodes-base.stickyNote",
"position": [
461.9740563285368,
970.616715060075
],
"parameters": {
"color": 7,
"width": 1449.2963504228514,
"height": 612.0936015224503,
"content": "### Sub-workflow: Custom tool\nThis can be called by the agent above. It returns three different types of data from the Google Sheet, which can be used together for more complex queries without returning the whole sheet (which might be too big for GPT to handle)"
},
"typeVersion": 1
},
{
"id": "8761e314-c1f2-4edd-88ea-bfeb02dc8f1a",
"name": "Sticky Note2",
"type": "n8n-nodes-base.stickyNote",
"position": [
460,
460
],
"parameters": {
"color": 7,
"width": 927.5,
"height": 486.5625,
"content": "### Main workflow: AI agent using custom tool"
},
"typeVersion": 1
},
{
"id": "e793b816-68d9-42ef-b9b0-6fe22aa375e8",
"name": "Sticky Note3",
"type": "n8n-nodes-base.stickyNote",
"position": [
300,
540
],
"parameters": {
"width": 185.9375,
"height": 183.85014518022527,
"content": "## Try me out\n\nClick the 'Chat' button at the bottom and enter:\n\n_Which is our biggest customer?_"
},
"typeVersion": 1
},
{
"id": "f895d926-0f70-415b-9492-c3ecf186e761",
"name": "Get Google sheet contents",
"type": "n8n-nodes-base.googleSheets",
"position": [
980,
1240
],
"parameters": {
"options": {},
"sheetName": {
"__rl": true,
"mode": "url",
"value": "={{ $json.sheetUrl }}"
},
"documentId": {
"__rl": true,
"mode": "url",
"value": "={{ $json.sheetUrl }}"
}
},
"credentials": {
"googleSheetsOAuth2Api": {
"name": "<your credential>"
}
},
"typeVersion": 4.2
},
{
"id": "daca1624-6c35-473a-bf3a-5fa0686a0a62",
"name": "Set Google Sheet URL",
"type": "n8n-nodes-base.set",
"position": [
760,
1240
],
"parameters": {
"fields": {
"values": [
{
"name": "sheetUrl",
"stringValue": "https://docs.google.com/spreadsheets/d/1GjFBV8HpraNWG_JyuaQAgTb3zUGguh0S_25nO0CMd8A/edit#gid=736425281"
}
]
},
"options": {}
},
"typeVersion": 3.2
},
{
"id": "68edca41-0196-47d8-9378-31fed0a70918",
"name": "Get column names",
"type": "n8n-nodes-base.set",
"position": [
1460,
1060
],
"parameters": {
"fields": {
"values": [
{
"name": "response",
"stringValue": "={{ Object.keys($json) }}"
}
]
},
"include": "none",
"options": {}
},
"executeOnce": true,
"typeVersion": 3.2
},
{
"id": "7a9dea08-f9e9-4139-842a-9066a9cf04ea",
"name": "Prepare output",
"type": "n8n-nodes-base.code",
"position": [
1720,
1240
],
"parameters": {
"jsCode": "return {\n 'response': JSON.stringify($input.all().map(x => x.json))\n}"
},
"typeVersion": 2
},
{
"id": "616eebc5-5c5c-4fa1-b13f-61a477742c72",
"name": "List columns tool",
"type": "@n8n/n8n-nodes-langchain.toolWorkflow",
"position": [
940,
780
],
"parameters": {
"name": "list_columns",
"fields": {
"values": [
{
"name": "operation",
"stringValue": "column_names"
}
]
},
"workflowId": "={{ $workflow.id }}",
"description": "=List all column names in customer data\n\nCall this tool to find out what data is available for each customer. It should be called first at the beginning to understand which columns are available for querying."
},
"typeVersion": 1
},
{
"id": "891ad3a8-72f0-45ad-8777-1647a7342c00",
"name": "Get customer tool",
"type": "@n8n/n8n-nodes-langchain.toolWorkflow",
"position": [
1220,
780
],
"parameters": {
"name": "get_customer",
"fields": {
"values": [
{
"name": "operation",
"stringValue": "row"
}
]
},
"workflowId": "={{ $workflow.id }}",
"description": "=Get all columns for a given customer\n\nThe input should be a stringified row number of the customer to fetch; only single string inputs are allowed. Returns a JSON object with all the column names and their values."
},
"typeVersion": 1
},
{
"id": "0f3ca6ff-fc01-4f33-b1a7-cb82a0ec5c88",
"name": "Get column values tool",
"type": "@n8n/n8n-nodes-langchain.toolWorkflow",
"position": [
1080,
780
],
"parameters": {
"name": "column_values",
"fields": {
"values": [
{
"name": "operation",
"stringValue": "column_values"
}
]
},
"workflowId": "={{ $workflow.id }}",
"description": "=Get the specified column value for all customers\n\nUse this tool to find out which customers have a certain value for a given column. Returns an array of JSON objects, one per customer. Each JSON object includes the column being requested plus the row_number column. Input should be a single string representing the name of the column to fetch.\n"
},
"typeVersion": 1
},
{
"id": "deef6eb4-2a11-4490-ad56-bc1ea9077843",
"name": "Sticky Note",
"type": "n8n-nodes-base.stickyNote",
"position": [
900,
740.8693557231958
],
"parameters": {
"color": 7,
"width": 432.3271051132649,
"height": 179.21380662202682,
"content": "These tools all call the sub-workflow below"
},
"typeVersion": 1
},
{
"id": "94e4dbe5-dc41-4879-bffc-ec8f5341f3b5",
"name": "Sticky Note4",
"type": "n8n-nodes-base.stickyNote",
"position": [
723,
1172
],
"parameters": {
"width": 179.99762227826224,
"height": 226.64416053838073,
"content": "Change the URL of the Google Sheet here"
},
"typeVersion": 1
},
{
"id": "dbb887f0-93a7-466e-9c9f-8aa4e7da935d",
"name": "Prepare column data",
"type": "n8n-nodes-base.set",
"position": [
1460,
1240
],
"parameters": {
"fields": {
"values": [
{
"name": "={{ $('Execute Workflow Trigger').item.json.query }}",
"stringValue": "={{ $json[$('Execute Workflow Trigger').item.json.query] }}"
},
{
"name": "row_number",
"stringValue": "={{ $json.row_number }}"
}
]
},
"include": "none",
"options": {}
},
"typeVersion": 3.2
},
{
"id": "041d32ca-e59a-4b67-a3e6-4e2f19e3de72",
"name": "Filter",
"type": "n8n-nodes-base.filter",
"position": [
1460,
1400
],
"parameters": {
"options": {
"looseTypeValidation": true
},
"conditions": {
"options": {
"leftValue": "",
"caseSensitive": true,
"typeValidation": "loose"
},
"combinator": "and",
"conditions": [
{
"id": "bf712098-97e4-42cb-8e08-2ee32d19d3e7",
"operator": {
"type": "number",
"operation": "equals"
},
"leftValue": "={{ $json.row_number }}",
"rightValue": "={{ $('Execute Workflow Trigger').item.json.query }}"
}
]
}
},
"typeVersion": 2,
"alwaysOutputData": true
},
{
"id": "69b9e70a-9104-4731-9f16-8324a3f7e423",
"name": "Check operation",
"type": "n8n-nodes-base.switch",
"position": [
1200,
1240
],
"parameters": {
"rules": {
"values": [
{
"outputKey": "col names",
"conditions": {
"options": {
"leftValue": "",
"caseSensitive": true,
"typeValidation": "strict"
},
"combinator": "and",
"conditions": [
{
"operator": {
"type": "string",
"operation": "equals"
},
"leftValue": "={{ $('Execute Workflow Trigger').item.json.operation }}",
"rightValue": "column_names"
}
]
},
"renameOutput": true
},
{
"outputKey": "col values",
"conditions": {
"options": {
"leftValue": "",
"caseSensitive": true,
"typeValidation": "strict"
},
"combinator": "and",
"conditions": [
{
"id": "b7968ce7-0d20-43d0-bcca-7b66e0aec715",
"operator": {
"name": "filter.operator.equals",
"type": "string",
"operation": "equals"
},
"leftValue": "={{ $('Execute Workflow Trigger').item.json.operation }}",
"rightValue": "column_values"
}
]
},
"renameOutput": true
},
{
"outputKey": "rows",
"conditions": {
"options": {
"leftValue": "",
"caseSensitive": true,
"typeValidation": "strict"
},
"combinator": "and",
"conditions": [
{
"id": "de3bb9b5-edc6-4448-839e-eda07b72144a",
"operator": {
"name": "filter.operator.equals",
"type": "string",
"operation": "equals"
},
"leftValue": "={{ $('Execute Workflow Trigger').item.json.operation }}",
"rightValue": "row"
}
]
},
"renameOutput": true
}
]
},
"options": {}
},
"typeVersion": 3
},
{
"id": "d955e499-5a3e-45a3-9fc8-266e2f687ecc",
"name": "OpenAI Chat Model",
"type": "@n8n/n8n-nodes-langchain.lmChatOpenAi",
"position": [
800,
780
],
"parameters": {
"model": "gpt-3.5-turbo-0125",
"options": {
"temperature": 0
}
},
"credentials": {
"openAiApi": {
"name": "<your credential>"
}
},
"typeVersion": 1
},
{
"id": "28fbda0b-1e01-4f59-af5b-fe02eba899b1",
"name": "Chat Trigger",
"type": "@n8n/n8n-nodes-langchain.chatTrigger",
"position": [
620,
560
],
"parameters": {},
"typeVersion": 1
},
{
"id": "c89614f4-d8b1-4f7b-9e7c-856e3f89eadb",
"name": "AI Agent",
"type": "@n8n/n8n-nodes-langchain.agent",
"position": [
900,
560
],
"parameters": {
"agent": "reActAgent",
"options": {
"suffix": "Begin! Use `list_columns` tool first to determine which columns are available.\n\n\tQuestion: {input}\n\tThought:{agent_scratchpad}",
"returnIntermediateSteps": false
}
},
"typeVersion": 1.3
}
],
"active": false,
"settings": {
"executionOrder": "v1"
},
"versionId": "94885609-92bb-498c-9628-35d9044593e7",
"connections": {
"Filter": {
"main": [
[
{
"node": "Prepare output",
"type": "main",
"index": 0
}
]
]
},
"Chat Trigger": {
"main": [
[
{
"node": "AI Agent",
"type": "main",
"index": 0
}
]
]
},
"Check operation": {
"main": [
[
{
"node": "Get column names",
"type": "main",
"index": 0
}
],
[
{
"node": "Prepare column data",
"type": "main",
"index": 0
}
],
[
{
"node": "Filter",
"type": "main",
"index": 0
}
]
]
},
"Get column names": {
"main": [
[
{
"node": "Prepare output",
"type": "main",
"index": 0
}
]
]
},
"Get customer tool": {
"ai_tool": [
[
{
"node": "AI Agent",
"type": "ai_tool",
"index": 0
}
]
]
},
"List columns tool": {
"ai_tool": [
[
{
"node": "AI Agent",
"type": "ai_tool",
"index": 0
}
]
]
},
"OpenAI Chat Model": {
"ai_languageModel": [
[
{
"node": "AI Agent",
"type": "ai_languageModel",
"index": 0
}
]
]
},
"Prepare column data": {
"main": [
[
{
"node": "Prepare output",
"type": "main",
"index": 0
}
]
]
},
"Set Google Sheet URL": {
"main": [
[
{
"node": "Get Google sheet contents",
"type": "main",
"index": 0
}
]
]
},
"Get column values tool": {
"ai_tool": [
[
{
"node": "AI Agent",
"type": "ai_tool",
"index": 0
}
]
]
},
"Execute Workflow Trigger": {
"main": [
[
{
"node": "Set Google Sheet URL",
"type": "main",
"index": 0
}
]
]
},
"Get Google sheet contents": {
"main": [
[
{
"node": "Check operation",
"type": "main",
"index": 0
}
]
]
}
}
}
Credentials you'll need
Each integration node will prompt for credentials when you import. We strip credential IDs before publishing — you'll add your own.
googleSheetsOAuth2ApiopenAiApi
Pro
For the full experience including quality scoring and batch install features for each workflow upgrade to Pro
How this works
Easily query and interact with your Google Sheets data through natural language conversations, saving time on manual data retrieval and analysis. This workflow is ideal for business analysts, marketers, or teams managing spreadsheets who need quick insights without technical expertise. It leverages OpenAI's chat capabilities to interpret your questions, fetches relevant data from Google Sheets, and delivers structured responses, with the key step being the AI agent that processes queries and executes targeted sheet operations.
Use this workflow when you want an intuitive chat interface for exploring spreadsheet data in real-time, such as summarising sales figures or filtering customer lists on demand. Avoid it for high-volume processing or when data privacy demands fully offline solutions, as it relies on cloud-based AI. Common variations include integrating additional tools like email notifications for query results or adapting it for other databases beyond Google Sheets.
About this workflow
Chat with Google Sheet. Uses executeWorkflowTrigger, stickyNote, googleSheets, toolWorkflow. Event-driven trigger; 19 nodes.
Source: https://github.com/Zie619/n8n-workflows — original creator credit. Request a take-down →
Related workflows
Workflows that share integrations, category, or trigger type with this one. All free to copy and import.
Code Noop. Uses informationExtractor, lmChatOpenAi, googleSheets, splitInBatches. Event-driven trigger; 19 nodes.
Information Extractor, OpenAI Chat, Google Sheets +5
This workflow automates the restaurant POS (Point of Sale) data management process, facilitating seamless order handling, customer tracking, inventory management, and sales reporting. It retrieves ord
Information Extractor, OpenAI Chat, Google Sheets +5
Chat to write or reword a blog post. The workflow stores each result in Google Sheets and uses a sub-workflow “Google tool” to count rows per session (your running context). If a session exceeds a row
Output Parser Structured, OpenAI Chat, Memory Buffer Window +5
Agent Nodes. Uses lmChatOpenAi, slack, stopAndError, errorTrigger. Event-driven trigger; 72 nodes.
OpenAI Chat, Slack, Stop And Error +12
Splitout Redis. Uses executeWorkflowTrigger, n8n, redis, splitOut. Event-driven trigger; 46 nodes.
Execute Workflow Trigger, n8n, Redis +7