Automate With Marc This workflow corresponds to n8n.io template #7506 — we link there as the canonical source.
This workflow follows the Agent → OpenAI Embeddings recipe pattern — see all workflows that pair these two integrations.
The workflow JSON
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{
"id": "mB32fQ5OyrLgbIIZ",
"name": "Slack Project Update RAG Agent",
"tags": [],
"nodes": [
{
"id": "44bc7fc6-9736-48e9-90dc-3098047abdc7",
"name": "Slack Trigger",
"type": "n8n-nodes-base.slackTrigger",
"position": [
880,
160
],
"parameters": {
"options": {
"userIds": "==[\"User_ID\"]"
},
"trigger": [
"any_event",
"app_mention"
],
"watchWorkspace": true
},
"typeVersion": 1
},
{
"id": "aabbb277-80f5-4316-8845-f34bce33261b",
"name": "OpenAI Chat Model",
"type": "@n8n/n8n-nodes-langchain.lmChatOpenAi",
"position": [
1100,
380
],
"parameters": {
"model": {
"__rl": true,
"mode": "list",
"value": "gpt-5",
"cachedResultName": "gpt-5"
},
"options": {}
},
"typeVersion": 1.2
},
{
"id": "14cb0538-fe7e-4739-9de9-129723400e44",
"name": "Simple Memory",
"type": "@n8n/n8n-nodes-langchain.memoryBufferWindow",
"position": [
1280,
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],
"parameters": {
"sessionKey": "={{ $json.channel }}",
"sessionIdType": "customKey"
},
"typeVersion": 1.3
},
{
"id": "92db15e1-3228-476f-a3da-1736e8f34d53",
"name": "Send a message",
"type": "n8n-nodes-base.slack",
"position": [
1840,
160
],
"parameters": {
"text": "={{ $json.output }}",
"select": "channel",
"channelId": {
"__rl": true,
"mode": "id",
"value": "={{ $('Slack Trigger').item.json.channel }}"
},
"otherOptions": {
"sendAsUser": "Jacob",
"includeLinkToWorkflow": false
}
},
"typeVersion": 2.3
},
{
"id": "24714547-eecf-4b11-a58f-c394dc7bc9e4",
"name": "Sticky Note",
"type": "n8n-nodes-base.stickyNote",
"position": [
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],
"parameters": {
"color": 3,
"width": 304,
"height": 624,
"content": "Slack Respond as a User"
},
"typeVersion": 1
},
{
"id": "387b6478-c255-42ba-b456-8b90d889e261",
"name": "Sticky Note1",
"type": "n8n-nodes-base.stickyNote",
"position": [
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],
"parameters": {
"color": 4,
"width": 704,
"height": 624,
"content": "GPT-5 Agent"
},
"typeVersion": 1
},
{
"id": "d4e0c080-fdcc-45b9-89ac-da6ff9d1de4e",
"name": "GPT 5 Slack Agent",
"type": "@n8n/n8n-nodes-langchain.agent",
"position": [
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],
"parameters": {
"text": "={{ $json.text }}",
"options": {
"systemMessage": "You are Jacob, an Engineer at Purple Unicorn IT Solutions. Respond to your members' message on Jacob's behalf on Slack. Sound friendly and natural in a typical tech working environment. \n\n##Tool\nUse the Pinecone Vector Store Tool when asked about Project Updates"
},
"promptType": "define"
},
"typeVersion": 2
},
{
"id": "7070bd4b-bc9e-426b-a6d9-074d386d86dd",
"name": "Sticky Note2",
"type": "n8n-nodes-base.stickyNote",
"position": [
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],
"parameters": {
"color": 5,
"height": 624,
"content": "Slack Trigger"
},
"typeVersion": 1
},
{
"id": "d8e65fda-3927-4404-accf-300c30ebef8e",
"name": "Pinecone Vector Store",
"type": "@n8n/n8n-nodes-langchain.vectorStorePinecone",
"position": [
1440,
340
],
"parameters": {
"mode": "retrieve-as-tool",
"options": {},
"pineconeIndex": {
"__rl": true,
"mode": "list",
"value": "test",
"cachedResultName": "test"
},
"toolDescription": "Refer to Database for Work Related Information"
},
"typeVersion": 1.3
},
{
"id": "fe5ef41c-9496-461a-b44a-5bb34aca4967",
"name": "Embeddings OpenAI",
"type": "@n8n/n8n-nodes-langchain.embeddingsOpenAi",
"position": [
1580,
500
],
"parameters": {
"options": {}
},
"typeVersion": 1.2
},
{
"id": "c11871c8-557c-42f6-ab82-f287b1178798",
"name": "Sticky Note3",
"type": "n8n-nodes-base.stickyNote",
"position": [
0,
0
],
"parameters": {
"color": 2,
"width": 752,
"height": 1008,
"content": "\ud83d\udee0 GPT-5 + Pinecone-Powered Slack Auto-Responder \u2014 Real-Time, Context-Aware Replies for IT & Engineering Teams\n\nDescription\nCut down on context-switching and keep your Slack threads moving with an AI agent that responds on your behalf, pulling real-time knowledge from a Pinecone vector database. Built for IT, DevOps, and engineering environments, this n8n workflow ensures every reply is accurate, context-aware, and instantly available\u2014without you lifting a finger.\n\nCheck out step-by-step video build of workflows like these here:\nhttps://www.youtube.com/@automatewithmarc\n\nHow It Works\n\nSlack Listener: Triggers when you\u2019re mentioned or messaged in relevant channels.\n\nPinecone RAG Retrieval: Pulls the most relevant technical details from your indexed documents, architecture notes, or runbooks.\n\nGPT-5 Processing: Formats the retrieved data into a clear, concise, and technically accurate reply.\n\nThread-Aware Memory: Maintains the conversation state to avoid repeating answers.\n\nSlack Send-as-User: Posts the message under your identity for seamless integration into team workflows.\n\nWhy IT Teams Will Love It\n\n\ud83d\udcda Always up-to-date \u2014 If your Pinecone index is refreshed with system docs, runbooks, or KB articles, the bot will always deliver the latest info.\n\n\ud83c\udfd7 Technical context retention \u2014 Perfect for answering ongoing infrastructure or incident threads.\n\n\u23f1 Reduced interruption time \u2014 No more breaking focus to answer \u201cquick questions.\u201d\n\n\ud83d\udd10 Controlled outputs \u2014 Tune GPT-5 to deliver fact-based, low-fluff responses for critical environments.\n\nCommon Use Cases\n\nDevOps: Automated responses to common CI/CD, deployment, or incident queries.\n\nSupport Engineering: Pulling troubleshooting steps directly from KB entries.\n\nProject Coordination: Instant status updates pulled from sprint or release notes.\n\nPro Tips for Deployment\n\nKeep your Pinecone vector DB updated with the latest architecture diagrams, release notes, and SOPs.\n\nUse embeddings tuned for technical documentation to improve retrieval accuracy.\n\nAdd channel-specific prompts if different teams require different response styles (e.g., #devops vs #product)."
},
"typeVersion": 1
}
],
"active": false,
"settings": {
"executionOrder": "v1"
},
"versionId": "5a498f5f-a962-44c6-ada3-7426d2cb62c3",
"connections": {
"Simple Memory": {
"ai_memory": [
[
{
"node": "GPT 5 Slack Agent",
"type": "ai_memory",
"index": 0
}
]
]
},
"Slack Trigger": {
"main": [
[
{
"node": "GPT 5 Slack Agent",
"type": "main",
"index": 0
}
]
]
},
"Embeddings OpenAI": {
"ai_embedding": [
[
{
"node": "Pinecone Vector Store",
"type": "ai_embedding",
"index": 0
}
]
]
},
"GPT 5 Slack Agent": {
"main": [
[
{
"node": "Send a message",
"type": "main",
"index": 0
}
]
]
},
"OpenAI Chat Model": {
"ai_languageModel": [
[
{
"node": "GPT 5 Slack Agent",
"type": "ai_languageModel",
"index": 0
}
]
]
},
"Pinecone Vector Store": {
"ai_tool": [
[
{
"node": "GPT 5 Slack Agent",
"type": "ai_tool",
"index": 0
}
]
]
}
}
}
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About this workflow
🛠 GPT-5 + Pinecone-Powered Slack Auto-Responder — Real-Time, Context-Aware Replies for IT & Engineering Teams
Source: https://n8n.io/workflows/7506/ — original creator credit. Request a take-down →
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