This workflow follows the Agent → OpenAI Chat 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 →
{
"meta": {
"templateCredsSetupCompleted": true
},
"nodes": [
{
"id": "12786b19-159f-45b0-8d15-d88de73c17e9",
"name": "Sticky Note",
"type": "n8n-nodes-base.stickyNote",
"position": [
-1540,
660
],
"parameters": {
"width": 483,
"height": 345,
"content": "### Slack POSTs to Webhook on every message so we need to filter-out bot messages"
},
"typeVersion": 1
},
{
"id": "3949be41-98b7-4414-84fd-819f4fccca35",
"name": "Sticky Note1",
"type": "n8n-nodes-base.stickyNote",
"position": [
-400,
1080
],
"parameters": {
"width": 293,
"height": 228,
"content": "### Tools which Agent can use to accomplish the task\n"
},
"typeVersion": 1
},
{
"id": "76ce81d8-33e2-470a-9313-dd888acabed0",
"name": "Sticky Note2",
"type": "n8n-nodes-base.stickyNote",
"position": [
-720,
1080
],
"parameters": {
"width": 288,
"height": 233,
"content": "### Conversation history is stored in memory using channel id as key"
},
"typeVersion": 1
},
{
"id": "3682ffd3-7002-466a-bedf-9897067586c0",
"name": "Sticky Note3",
"type": "n8n-nodes-base.stickyNote",
"position": [
-1000,
1080
],
"parameters": {
"width": 260,
"height": 233,
"content": "### The chat LM to process the prompt"
},
"typeVersion": 1
},
{
"id": "92865916-e814-49d4-baaa-4122c1447c23",
"name": "Sticky Note4",
"type": "n8n-nodes-base.stickyNote",
"position": [
-280,
640
],
"parameters": {
"width": 280,
"height": 243,
"content": "### Send agent's output as Slack message\n"
},
"typeVersion": 1
},
{
"id": "edeab2bb-8177-42c7-bcf4-f8d99e193729",
"name": "AI Agent",
"type": "@n8n/n8n-nodes-langchain.agent",
"position": [
-820,
740
],
"parameters": {
"text": "={{ $json.body.event.text }}",
"options": {
"systemMessage": "You are Gilfoyle from Silicon Valley TV show. Amplify your bluntness and cynicism, tolerating zero incompetence. Be openly contemptuous when answering questions, and cut straight to the point with minimal regard for others' feelings. Your sarcasm should be razor-sharp, and humor should take a backseat to delivering cutting remarks.\\nDo your best to answer the questions. Feel free to use any tools available to look up relevant information, only if necessary. "
},
"promptType": "define"
},
"typeVersion": 1.8
},
{
"id": "275f8192-6da6-41b0-b892-c779f5d136e4",
"name": "OpenAI Chat Model",
"type": "@n8n/n8n-nodes-langchain.lmChatOpenAi",
"position": [
-920,
1180
],
"parameters": {
"model": {
"__rl": true,
"mode": "list",
"value": "gpt-4o-mini"
},
"options": {}
},
"credentials": {
"openAiApi": {
"name": "<your credential>"
}
},
"typeVersion": 1.2
},
{
"id": "776ce632-5c62-4ac6-a494-e23ef650ac48",
"name": "Simple Memory",
"type": "@n8n/n8n-nodes-langchain.memoryBufferWindow",
"position": [
-620,
1180
],
"parameters": {
"sessionKey": "={{ $('Webhook').first().json.body.event.channel }}__gilfoyle",
"sessionIdType": "customKey",
"contextWindowLength": 30
},
"typeVersion": 1.3
},
{
"id": "97989831-3fc6-4954-ac55-8e0950081b7a",
"name": "Is user message?",
"type": "n8n-nodes-base.if",
"position": [
-1480,
740
],
"parameters": {
"options": {},
"conditions": {
"options": {
"version": 2,
"leftValue": "",
"caseSensitive": true,
"typeValidation": "strict"
},
"combinator": "and",
"conditions": [
{
"id": "1def7344-ce55-450d-a85a-468f746fe31f",
"operator": {
"type": "string",
"operation": "notExists",
"singleValue": true
},
"leftValue": "={{ $json.body.event.bot_id }}",
"rightValue": ""
}
]
}
},
"typeVersion": 2.2
},
{
"id": "afa6b192-1e25-46b6-8fdc-81dff9a37e74",
"name": "No Operation, do nothing",
"type": "n8n-nodes-base.noOp",
"position": [
-1280,
820
],
"parameters": {},
"typeVersion": 1
},
{
"id": "eab68a99-cdd6-4ea1-8d6f-053c2a96303c",
"name": "SerpAPI",
"type": "@n8n/n8n-nodes-langchain.toolSerpApi",
"position": [
-360,
1180
],
"parameters": {
"options": {}
},
"credentials": {
"serpApi": {
"name": "<your credential>"
}
},
"typeVersion": 1
},
{
"id": "717117f5-5f34-4189-b92a-df2155e367ac",
"name": "Wikipedia",
"type": "@n8n/n8n-nodes-langchain.toolWikipedia",
"position": [
-220,
1180
],
"parameters": {},
"typeVersion": 1
},
{
"id": "1914f623-66c0-4547-bf3e-b4932d0c2a9b",
"name": "Slack",
"type": "n8n-nodes-base.slack",
"position": [
-200,
720
],
"parameters": {
"text": "={{ $json.output }}",
"user": {
"__rl": true,
"mode": "id",
"value": "={{ $('Webhook').first().json.body.event.user }}"
},
"select": "user",
"otherOptions": {}
},
"credentials": {
"slackApi": {
"name": "<your credential>"
}
},
"typeVersion": 2.3
},
{
"id": "4a7ec607-1706-4357-aa89-4c44faa98fb8",
"name": "Webhook",
"type": "n8n-nodes-base.webhook",
"position": [
-1780,
740
],
"parameters": {
"path": "slack-gilfoyle",
"options": {},
"httpMethod": "POST"
},
"typeVersion": 2
}
],
"connections": {
"SerpAPI": {
"ai_tool": [
[
{
"node": "AI Agent",
"type": "ai_tool",
"index": 0
}
]
]
},
"Webhook": {
"main": [
[
{
"node": "Is user message?",
"type": "main",
"index": 0
}
]
]
},
"AI Agent": {
"main": [
[
{
"node": "Slack",
"type": "main",
"index": 0
}
]
]
},
"Wikipedia": {
"ai_tool": [
[
{
"node": "AI Agent",
"type": "ai_tool",
"index": 0
}
]
]
},
"Simple Memory": {
"ai_memory": [
[
{
"node": "AI Agent",
"type": "ai_memory",
"index": 0
}
]
]
},
"Is user message?": {
"main": [
[
{
"node": "AI Agent",
"type": "main",
"index": 0
}
],
[
{
"node": "No Operation, do nothing",
"type": "main",
"index": 0
}
]
]
},
"OpenAI Chat Model": {
"ai_languageModel": [
[
{
"node": "AI Agent",
"type": "ai_languageModel",
"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.
openAiApiserpApislackApi
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How this works
This workflow enables seamless AI-powered conversations in Slack, allowing users to interact with an intelligent agent that responds contextually to queries without executing any real actions, making it ideal for testing and development teams refining chatbot logic. It delivers value by simulating realistic chat flows, helping you iterate on prompts and memory handling before deploying to production, all triggered effortlessly via a webhook. The key step involves the AI Agent node, which leverages the OpenAI Chat Model and a memory buffer to maintain conversation history, ensuring coherent and relevant replies within Slack.
Use this workflow when prototyping AI chatbots for Slack or validating response accuracy in a no-risk environment, such as during initial setup or debugging prompt variations. Avoid it for production systems requiring actual task execution, like sending emails or updating databases, as it focuses solely on simulation. Common variations include swapping the OpenAI model for another LLM or adding tools like SERP API for enhanced query handling in test scenarios.
About this workflow
Noop Slack. Uses stickyNote, agent, lmChatOpenAi, memoryBufferWindow. Webhook trigger; 14 nodes.
Source: https://github.com/Zie619/n8n-workflows — original creator credit. Request a take-down →
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