This workflow follows the Agent → Chat Trigger recipe pattern — see all workflows that pair these two integrations.
The workflow JSON
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{
"name": "KI-Agent + Data Table (Praxis-Beispiel)",
"nodes": [
{
"parameters": {
"content": "## Chat \u2192 KI-Agent \u2192 in Tabelle speichern\n\nPraxisnah: Der **Chat-Agent** beantwortet eine Frage, und Frage + Antwort werden **dauerhaft in einer n8n Data Table** gespeichert.\n\nSo baust du z.B. ein einfaches FAQ-/Protokoll-System \u2014 **ohne externe Datenbank** (Data Tables sind in n8n eingebaut).\n\n\u25b6\ufe0f **Testen:** \u00fcber den **Chat** starten (Sub-Nodes laufen nur \u00fcber den Agent).",
"height": 240,
"width": 560,
"color": 4
},
"id": "da100000-0000-4000-8000-000000000001",
"name": "Doku: \u00dcberblick",
"type": "n8n-nodes-base.stickyNote",
"typeVersion": 1,
"position": [
-80,
-330
]
},
{
"parameters": {
"content": "## Vorbereitung (einmalig)\nLeg in n8n unter **Data Tables** eine Tabelle `chat_log` mit zwei Text-Spalten an:\n- **frage**\n- **antwort**\n\nW\u00e4hle sie dann im letzten Node (\u201eIn Tabelle speichern\") aus.",
"height": 240,
"width": 360,
"color": 6
},
"id": "da100000-0000-4000-8000-000000000002",
"name": "Doku: Vorbereitung",
"type": "n8n-nodes-base.stickyNote",
"typeVersion": 1,
"position": [
520,
-330
]
},
{
"parameters": {
"content": "## Chat Trigger\nStartet bei jeder Chat-Nachricht.\nDie Frage steht in `{{ $json.chatInput }}`.",
"height": 120,
"width": 230,
"color": 5
},
"id": "da100000-0000-4000-8000-000000000003",
"name": "Doku: Trigger",
"type": "n8n-nodes-base.stickyNote",
"typeVersion": 1,
"position": [
20,
-170
]
},
{
"parameters": {
"content": "## KI-Agent\nBeantwortet die Frage (Claude + Memory).\nDie Antwort steht danach in `{{ $json.output }}`.",
"height": 120,
"width": 230,
"color": 6
},
"id": "da100000-0000-4000-8000-000000000004",
"name": "Doku: Agent",
"type": "n8n-nodes-base.stickyNote",
"typeVersion": 1,
"position": [
300,
-170
]
},
{
"parameters": {
"content": "## Data Table (Insert)\nSpeichert **frage** + **antwort** als neue Zeile.\n**Eingebaut in n8n \u2014 keine externe DB n\u00f6tig.**",
"height": 120,
"width": 250,
"color": 3
},
"id": "da100000-0000-4000-8000-000000000005",
"name": "Doku: DataTable",
"type": "n8n-nodes-base.stickyNote",
"typeVersion": 1,
"position": [
600,
-170
]
},
{
"parameters": {
"content": "**Sprachmodell (Claude)**\nDas LLM \u2014 braucht Anthropic-Credential.",
"height": 90,
"width": 200,
"color": 7
},
"id": "da100000-0000-4000-8000-000000000006",
"name": "Doku: Modell",
"type": "n8n-nodes-base.stickyNote",
"typeVersion": 1,
"position": [
160,
150
]
},
{
"parameters": {
"content": "**Memory**\nMerkt sich den Gespr\u00e4chsverlauf.",
"height": 90,
"width": 200,
"color": 7
},
"id": "da100000-0000-4000-8000-000000000007",
"name": "Doku: Memory",
"type": "n8n-nodes-base.stickyNote",
"typeVersion": 1,
"position": [
380,
150
]
},
{
"parameters": {
"options": {}
},
"id": "da100000-0000-4000-8000-0000000000b1",
"name": "Chat-Nachricht (Trigger)",
"type": "@n8n/n8n-nodes-langchain.chatTrigger",
"typeVersion": 1.4,
"position": [
80,
0
]
},
{
"parameters": {
"promptType": "auto",
"options": {
"systemMessage": "Du bist ein hilfreicher Assistent f\u00fcr ein Hackathon-Team. Antworte freundlich und kurz auf Deutsch."
}
},
"id": "da100000-0000-4000-8000-0000000000b2",
"name": "KI-Agent",
"type": "@n8n/n8n-nodes-langchain.agent",
"typeVersion": 3.1,
"position": [
360,
0
]
},
{
"parameters": {
"options": {}
},
"id": "da100000-0000-4000-8000-0000000000b3",
"name": "Sprachmodell (Claude)",
"type": "@n8n/n8n-nodes-langchain.lmChatAnthropic",
"typeVersion": 1.5,
"position": [
200,
280
]
},
{
"parameters": {},
"id": "da100000-0000-4000-8000-0000000000b4",
"name": "Ged\u00e4chtnis (Memory)",
"type": "@n8n/n8n-nodes-langchain.memoryBufferWindow",
"typeVersion": 1.4,
"position": [
420,
280
]
},
{
"parameters": {
"resource": "row",
"operation": "insert",
"dataTableId": {
"__rl": true,
"mode": "list",
"value": ""
},
"columns": {
"mappingMode": "defineBelow",
"value": {
"frage": "={{ $('Chat-Nachricht (Trigger)').item.json.chatInput }}",
"antwort": "={{ $json.output }}"
},
"matchingColumns": [],
"schema": [],
"attemptToConvertTypes": false,
"convertFieldsToString": true
},
"options": {}
},
"id": "da100000-0000-4000-8000-0000000000b5",
"name": "In Tabelle speichern",
"type": "n8n-nodes-base.dataTable",
"typeVersion": 1.1,
"position": [
660,
0
]
}
],
"connections": {
"Chat-Nachricht (Trigger)": {
"main": [
[
{
"node": "KI-Agent",
"type": "main",
"index": 0
}
]
]
},
"Sprachmodell (Claude)": {
"ai_languageModel": [
[
{
"node": "KI-Agent",
"type": "ai_languageModel",
"index": 0
}
]
]
},
"Ged\u00e4chtnis (Memory)": {
"ai_memory": [
[
{
"node": "KI-Agent",
"type": "ai_memory",
"index": 0
}
]
]
},
"KI-Agent": {
"main": [
[
{
"node": "In Tabelle speichern",
"type": "main",
"index": 0
}
]
]
}
},
"settings": {
"executionOrder": "v1"
}
}
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About this workflow
KI-Agent + Data Table (Praxis-Beispiel). Uses chatTrigger, agent, lmChatAnthropic, memoryBufferWindow. Chat trigger; 12 nodes.
Source: https://github.com/freddy-schuetz/hackathon-n8n-starter/blob/c389e97515f8fee487299b0daed1f885f049178b/examples/workflows/ai-agent-datatable.json — original creator credit. Request a take-down →
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