This workflow follows the Agent → Google Sheets 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 →
{
"name": "LINKEDIN AI REPLY BOT",
"nodes": [
{
"parameters": {
"content": "## Smart LinkedIn Reply Bot: AI-Powered Messaging & Tracking\n### Automates the process of responding to received messages from LinkedIn connections, checking the number of messages exchanged, and updating a Google Sheets document accordingly. \n### It utilizes an AI agent to craft personalized responses and logs the interaction in a database, ensuring effective communication management.",
"height": 520,
"width": 2280,
"color": 3
},
"type": "n8n-nodes-base.stickyNote",
"typeVersion": 1,
"position": [
-48,
-80
],
"id": "209c24ed-924c-40f5-8d2b-fc7868bad3f6",
"name": "Sticky Note12"
},
{
"parameters": {
"documentId": {
"__rl": true,
"value": "1tSl-WdN2D6BPtWbE0Yu2WWY4tjfr6likzBHgoNJAnRQ",
"mode": "list",
"cachedResultName": "LN Tracker",
"cachedResultUrl": "https://docs.google.com/spreadsheets/d/1tSl-WdN2D6BPtWbE0Yu2WWY4tjfr6likzBHgoNJAnRQ/edit?usp=drivesdk"
},
"sheetName": {
"__rl": true,
"value": "gid=0",
"mode": "list",
"cachedResultName": "Sheet1",
"cachedResultUrl": "https://docs.google.com/spreadsheets/d/1tSl-WdN2D6BPtWbE0Yu2WWY4tjfr6likzBHgoNJAnRQ/edit#gid=0"
},
"filtersUI": {
"values": [
{
"lookupColumn": "LN_providerID",
"lookupValue": "={{ $json.body.attendees[0].attendee_provider_id }}"
}
]
},
"options": {}
},
"type": "n8n-nodes-base.googleSheets",
"typeVersion": 4.5,
"position": [
304,
80
],
"id": "9ce3a226-68d8-4790-9588-4a4ccca72609",
"name": "Get the Person",
"credentials": {
"googleSheetsOAuth2Api": {
"name": "<your credential>"
}
}
},
{
"parameters": {
"conditions": {
"options": {
"caseSensitive": true,
"leftValue": "",
"typeValidation": "strict",
"version": 2
},
"conditions": [
{
"id": "b4189cc2-87aa-4a03-8ee3-469678a68d36",
"leftValue": "={{ $json.LN_noofmessages }}",
"rightValue": 1,
"operator": {
"type": "number",
"operation": "gte"
}
},
{
"id": "5c48903c-c850-4f16-a1f7-408c7f5ac343",
"leftValue": "={{ $('Msg Recieved').item.json.body.sender.attendee_provider_id }}",
"rightValue": "={{ $('Msg Recieved').item.json.body.attendees[0].attendee_provider_id }}",
"operator": {
"type": "string",
"operation": "equals",
"name": "filter.operator.equals"
}
}
],
"combinator": "and"
},
"options": {}
},
"type": "n8n-nodes-base.if",
"typeVersion": 2.2,
"position": [
512,
80
],
"id": "26f1edd6-fdad-48ef-80e6-c8d39686fd17",
"name": "If"
},
{
"parameters": {
"httpMethod": "POST",
"path": "deeba7a0-65c1-4c5b-ae32-6a2ff9a006e2",
"options": {}
},
"type": "n8n-nodes-base.webhook",
"typeVersion": 2,
"position": [
96,
80
],
"id": "71383032-1143-49c0-864d-2dd575861d39",
"name": "Msg Recieved"
},
{
"parameters": {
"documentId": {
"__rl": true,
"value": "={{ $('Get the Person').item.json.OriginSpreadsheetID }}",
"mode": "id"
},
"sheetName": {
"__rl": true,
"value": "={{ $('Get the Person').item.json[\"Origin SheetID\"] }}",
"mode": "id"
},
"options": {}
},
"type": "n8n-nodes-base.googleSheets",
"typeVersion": 4.5,
"position": [
704,
64
],
"id": "1ace0fc3-3633-4463-a3c1-273d84223489",
"name": "Get Data from Main Sheet",
"credentials": {
"googleSheetsOAuth2Api": {
"name": "<your credential>"
}
}
},
{
"parameters": {
"promptType": "define",
"text": "=Message from the attendee: {{ $('Msg Recieved').item.json.body.message }}",
"options": {
"systemMessage": "=\nYou are a professional LinkedIn outreach assistant. Your goal is to respond to recipients who have replied to your initial message, engage in a meaningful\nconversation to understand their situation, and encourage them to book a call using a provided calendar link. Follow these guidelines:\n1. **Acknowledge Their Reply**: Start by thanking them for responding and referencing something specific from their message.\n2. **Ask Open-Ended Questions**: Show genuine interest in their situation by asking thoughtful questions to learn more about their goals, challenges, or interests.\n3. **Provide Value**: Highlight how a call could benefit them based on what they've shared.\n4. **Suggest a Call**: Transition naturally to suggesting a call and share the calendar link in a polite, non-pushy way.\n5. **Be Professional and Friendly**: Maintain a polite, respectful, and conversational tone throughout.\n**Example Workflow:**\n1. **Acknowledge and Engage**:\n*\"Hi [Name], thanks for getting back to me! It's great to hear about [specific detail from their reply]. Could you tell me more about [specific topic]?\"*\n2. **Ask Follow-Up Questions**:\n*\"That's really interesting! How are you currently approaching [specific challenge or goal] ?\"*\n3. **Transition to a Call**:\n*\"It sounds like [specific insight]. I'd love to explore this further and see how I can help. Would you be open to a quick 15-minute call? Here's my calendar link: kyleautomates. Feel free to pick a time that\nworks best for you!\"*\n4. **Handle Objections or Questions**:\nIf they hesitate or ask for more details, respond politely and provide clarity. *\"I completely understand! On the call, we can discuss [specific benefit or topic]. Let me know if that works for you!\"*\n5. **Follow Up If Needed**:\nIf they don't book a call, send a polite follow-up after a few days:\n*\"Hi [Name], just checking in to see if you'd like to connect. Let me know if you'd like to schedule a quick chat. Here's my calendar link again: [Insert Link]. Looking forward to hearing from you.\n\nFocus on building rapport, understanding their needs, and making it easy for them to book a call.\nThis prompt ensures the agent responds thoughtfully and transitions naturally to booking a call.\nAdditional Info:\nAttendies name: {{ $('Msg Recieved').item.json.body.attendees[0].attendee_name }}"
}
},
"type": "@n8n/n8n-nodes-langchain.agent",
"typeVersion": 1.7,
"position": [
880,
64
],
"id": "f402878e-d0d9-4092-a3da-f2973388843b",
"name": "AI Agent"
},
{
"parameters": {
"model": {
"__rl": true,
"value": "=gpt-4o",
"mode": "id"
},
"options": {}
},
"type": "@n8n/n8n-nodes-langchain.lmChatOpenAi",
"typeVersion": 1.2,
"position": [
832,
304
],
"id": "e97ad19b-838d-49dc-8e04-9bbe1fa00a30",
"name": "OpenAI Chat Model",
"credentials": {
"openAiApi": {
"name": "<your credential>"
}
}
},
{
"parameters": {
"sessionIdType": "customKey",
"sessionKey": "={{ $('Msg Recieved').item.json.body.attendees[0].attendee_provider_id }}",
"tableName": "=n8n_chat_histories"
},
"type": "@n8n/n8n-nodes-langchain.memoryPostgresChat",
"typeVersion": 1.3,
"position": [
992,
304
],
"id": "11413e09-d9da-4d26-b199-aed779efd3f9",
"name": "Postgres Chat Memory"
},
{
"parameters": {
"method": "POST",
"url": "https://[subdomain].unipile.com:[port]/api/v1/chats",
"sendHeaders": true,
"headerParameters": {
"parameters": [
{
"name": "X-API-KEY",
"value": "your_unipile_api_key"
},
{
"name": "accept",
"value": "application/json"
},
{
"name": "content-type",
"value": "multipart/form-data"
}
]
},
"sendBody": true,
"contentType": "multipart-form-data",
"bodyParameters": {
"parameters": [
{
"name": "attendees_ids",
"value": "={{ $('Msg Recieved').item.json.body.attendees[0].attendee_provider_id }}"
},
{
"name": "account_id",
"value": "your_unipile_account_id"
},
{
"name": "text",
"value": "={{ $('AI Agent').item.json.output }}"
}
]
},
"options": {}
},
"type": "n8n-nodes-base.httpRequest",
"typeVersion": 4.2,
"position": [
1632,
64
],
"id": "6a51b29c-fd14-45ba-ac9d-153355d15aea",
"name": "SendMessage"
},
{
"parameters": {
"operation": "update",
"documentId": {
"__rl": true,
"value": "1tSl-WdN2D6BPtWbE0Yu2WWY4tjfr6likzBHgoNJAnRQ",
"mode": "list",
"cachedResultName": "LN Tracker",
"cachedResultUrl": "https://docs.google.com/spreadsheets/d/1tSl-WdN2D6BPtWbE0Yu2WWY4tjfr6likzBHgoNJAnRQ/edit?usp=drivesdk"
},
"sheetName": {
"__rl": true,
"value": "gid=0",
"mode": "list",
"cachedResultName": "Sheet1",
"cachedResultUrl": "https://docs.google.com/spreadsheets/d/1tSl-WdN2D6BPtWbE0Yu2WWY4tjfr6likzBHgoNJAnRQ/edit#gid=0"
},
"columns": {
"mappingMode": "defineBelow",
"value": {
"LN_providerID": "={{ $('Get the Person').item.json.LN_providerID }}",
"LN_noofmessages": "={{ $json.updatedmessages }}"
},
"matchingColumns": [
"LN_providerID"
],
"schema": [
{
"id": "first_name",
"displayName": "first_name",
"required": false,
"defaultMatch": false,
"display": true,
"type": "string",
"canBeUsedToMatch": true,
"removed": true
},
{
"id": "last_name",
"displayName": "last_name",
"required": false,
"defaultMatch": false,
"display": true,
"type": "string",
"canBeUsedToMatch": true,
"removed": true
},
{
"id": "Name",
"displayName": "Name",
"required": false,
"defaultMatch": false,
"display": true,
"type": "string",
"canBeUsedToMatch": true,
"removed": true
},
{
"id": "LN_url",
"displayName": "LN_url",
"required": false,
"defaultMatch": false,
"display": true,
"type": "string",
"canBeUsedToMatch": true,
"removed": true
},
{
"id": "LN_publicID",
"displayName": "LN_publicID",
"required": false,
"defaultMatch": false,
"display": true,
"type": "string",
"canBeUsedToMatch": true,
"removed": true
},
{
"id": "LN_providerID",
"displayName": "LN_providerID",
"required": false,
"defaultMatch": false,
"display": true,
"type": "string",
"canBeUsedToMatch": true,
"removed": false
},
{
"id": "LN_invitationSent",
"displayName": "LN_invitationSent",
"required": false,
"defaultMatch": false,
"display": true,
"type": "string",
"canBeUsedToMatch": true,
"removed": true
},
{
"id": "LN_invitationaccepted",
"displayName": "LN_invitationaccepted",
"required": false,
"defaultMatch": false,
"display": true,
"type": "string",
"canBeUsedToMatch": true,
"removed": true
},
{
"id": "LN_msgSent",
"displayName": "LN_msgSent",
"required": false,
"defaultMatch": false,
"display": true,
"type": "string",
"canBeUsedToMatch": true,
"removed": true
},
{
"id": "emailSent",
"displayName": "emailSent",
"required": false,
"defaultMatch": false,
"display": true,
"type": "string",
"canBeUsedToMatch": true,
"removed": true
},
{
"id": "LN_emailReplied",
"displayName": "LN_emailReplied",
"required": false,
"defaultMatch": false,
"display": true,
"type": "string",
"canBeUsedToMatch": true,
"removed": true
},
{
"id": "OriginSpreadsheetID",
"displayName": "OriginSpreadsheetID",
"required": false,
"defaultMatch": false,
"display": true,
"type": "string",
"canBeUsedToMatch": true,
"removed": true
},
{
"id": "Origin SheetID",
"displayName": "Origin SheetID",
"required": false,
"defaultMatch": false,
"display": true,
"type": "string",
"canBeUsedToMatch": true,
"removed": true
},
{
"id": "LN_noofmessages",
"displayName": "LN_noofmessages",
"required": false,
"defaultMatch": false,
"display": true,
"type": "string",
"canBeUsedToMatch": true
},
{
"id": "Email",
"displayName": "Email",
"required": false,
"defaultMatch": false,
"display": true,
"type": "string",
"canBeUsedToMatch": true,
"removed": true
},
{
"id": "row_number",
"displayName": "row_number",
"required": false,
"defaultMatch": false,
"display": true,
"type": "string",
"canBeUsedToMatch": true,
"readOnly": true,
"removed": true
}
],
"attemptToConvertTypes": false,
"convertFieldsToString": false
},
"options": {}
},
"type": "n8n-nodes-base.googleSheets",
"typeVersion": 4.5,
"position": [
1968,
64
],
"id": "92e9178c-6ffe-4d3a-a7b1-6599d0fbe252",
"name": "Update the number of messages",
"credentials": {
"googleSheetsOAuth2Api": {
"name": "<your credential>"
}
}
},
{
"parameters": {
"jsCode": "let currentmessages = $('Get the Person').first().json.LN_noofmessages\n\ncurrentmessages = currentmessages ? Number(currentmessages) : 0;\n\nlet updatedmessages = currentmessages + 1;\n\nreturn [\n {\n updatedmessages : updatedmessages\n }\n]"
},
"type": "n8n-nodes-base.code",
"typeVersion": 2,
"position": [
1792,
64
],
"id": "0dad32ee-4ee2-4738-b14c-e3d82a51aa90",
"name": "code"
},
{
"parameters": {
"amount": "={{ $json.RandomNumber }}"
},
"type": "n8n-nodes-base.wait",
"typeVersion": 1.1,
"position": [
1424,
64
],
"id": "df6e8216-e327-4084-9abe-6d69d1413119",
"name": "Wait1"
},
{
"parameters": {
"jsCode": "items[0].json.RandomNumber = Math.floor(Math.random() * 8);\nreturn items;"
},
"type": "n8n-nodes-base.code",
"typeVersion": 2,
"position": [
1232,
64
],
"id": "b819e48b-c8ee-46f4-a95a-bb957910eed3",
"name": "randomizer3"
}
],
"connections": {
"Get the Person": {
"main": [
[
{
"node": "If",
"type": "main",
"index": 0
}
]
]
},
"If": {
"main": [
[
{
"node": "Get Data from Main Sheet",
"type": "main",
"index": 0
}
]
]
},
"Msg Recieved": {
"main": [
[
{
"node": "Get the Person",
"type": "main",
"index": 0
}
]
]
},
"Get Data from Main Sheet": {
"main": [
[
{
"node": "AI Agent",
"type": "main",
"index": 0
}
]
]
},
"AI Agent": {
"main": [
[
{
"node": "randomizer3",
"type": "main",
"index": 0
}
]
]
},
"OpenAI Chat Model": {
"ai_languageModel": [
[
{
"node": "AI Agent",
"type": "ai_languageModel",
"index": 0
}
]
]
},
"Postgres Chat Memory": {
"ai_memory": [
[
{
"node": "AI Agent",
"type": "ai_memory",
"index": 0
}
]
]
},
"SendMessage": {
"main": [
[
{
"node": "code",
"type": "main",
"index": 0
}
]
]
},
"code": {
"main": [
[
{
"node": "Update the number of messages",
"type": "main",
"index": 0
}
]
]
},
"Wait1": {
"main": [
[
{
"node": "SendMessage",
"type": "main",
"index": 0
}
]
]
},
"randomizer3": {
"main": [
[
{
"node": "Wait1",
"type": "main",
"index": 0
}
]
]
}
},
"active": false,
"settings": {
"executionOrder": "v1",
"availableInMCP": false
},
"versionId": "02248cd2-bb31-4c41-b69b-83f952ce8247",
"id": "VLXIWrJhh23e4TmF",
"tags": []
}
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
This workflow automates intelligent replies to LinkedIn messages, saving you hours of manual engagement by generating personalised responses using AI. It's ideal for sales professionals, recruiters, or networkers who receive high volumes of connection requests and messages but lack time to respond individually. The key step involves pulling contact details from Google Sheets, feeding them into an AI agent powered by OpenAI to craft context-aware replies, ensuring your outreach feels authentic and boosts connection rates.
Use this when managing 50+ daily LinkedIn interactions across a team, or for consistent follow-ups in lead generation campaigns. Avoid it for highly sensitive negotiations requiring human nuance, or if your message volume is low enough for manual handling. Common variations include adapting the AI prompts for industry-specific tones, or integrating HTTP requests to post replies directly to LinkedIn via its API.
About this workflow
LINKEDIN AI REPLY BOT. Uses stickyNote, googleSheets, agent, lmChatOpenAi. Webhook trigger; 13 nodes.
Source: https://github.com/lucky14426/ai-outreach-automation-platform/blob/main/workflows/05-ai-reply-bot/linkedin-ai-reply-bot.json — original creator credit. Request a take-down →
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