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": "eOUewYsEzJmQixI6",
"meta": {
"templateCredsSetupCompleted": true
},
"name": "Chat with Postgresql Database",
"tags": [],
"nodes": [
{
"id": "6501a54f-a68c-452d-b353-d7e871ca3780",
"name": "When chat message received",
"type": "@n8n/n8n-nodes-langchain.chatTrigger",
"position": [
-300,
-80
],
"parameters": {
"options": {}
},
"typeVersion": 1.1
},
{
"id": "cd32221b-2a36-408d-b57e-8115fcd810c9",
"name": "AI Agent",
"type": "@n8n/n8n-nodes-langchain.agent",
"position": [
0,
-80
],
"parameters": {
"agent": "openAiFunctionsAgent",
"options": {
"systemMessage": "You are DB assistant. You need to run queries in DB aligned with user requests.\n\nRun custom SQL query to aggregate data and response to user. Make sure every table has schema prefix to it in sql query which you can get from `Get DB Schema and Tables List` tool.\n\nFetch all data to analyse it for response if needed.\n\n## Tools\n\n- Execute SQL query - Executes any sql query generated by AI\n- Get DB Schema and Tables List - Lists all the tables in database with its schema name\n- Get Table Definition - Gets the table definition from db using table name and schema name"
}
},
"typeVersion": 1.7
},
{
"id": "8accbeeb-7eaf-4e9e-aabc-de8ab3a0459b",
"name": "OpenAI Chat Model",
"type": "@n8n/n8n-nodes-langchain.lmChatOpenAi",
"position": [
-60,
160
],
"parameters": {
"model": {
"__rl": true,
"mode": "list",
"value": "gpt-4o-mini"
},
"options": {}
},
"credentials": {
"openAiApi": {
"name": "<your credential>"
}
},
"typeVersion": 1.2
},
{
"id": "11f2013f-a080-4c9e-8773-c90492e2c628",
"name": "Get Table Definition",
"type": "n8n-nodes-base.postgresTool",
"position": [
780,
140
],
"parameters": {
"query": "select\n c.column_name,\n c.data_type,\n c.is_nullable,\n c.column_default,\n tc.constraint_type,\n ccu.table_name AS referenced_table,\n ccu.column_name AS referenced_column\nfrom\n information_schema.columns c\nLEFT join\n information_schema.key_column_usage kcu\n ON c.table_name = kcu.table_name\n AND c.column_name = kcu.column_name\nLEFT join\n information_schema.table_constraints tc\n ON kcu.constraint_name = tc.constraint_name\n AND tc.constraint_type = 'FOREIGN KEY'\nLEFT join\n information_schema.constraint_column_usage ccu\n ON tc.constraint_name = ccu.constraint_name\nwhere\n c.table_name = '{{ $fromAI(\"table_name\") }}'\n AND c.table_schema = '{{ $fromAI(\"schema_name\") }}'\norder by\n c.ordinal_position",
"options": {},
"operation": "executeQuery",
"descriptionType": "manual",
"toolDescription": "Get table definition to find all columns and types"
},
"credentials": {
"postgres": {
"name": "<your credential>"
}
},
"typeVersion": 2.5
},
{
"id": "760bc9bc-0057-4088-b3f0-3ee37b3519df",
"name": "Sticky Note",
"type": "n8n-nodes-base.stickyNote",
"position": [
-300,
-240
],
"parameters": {
"color": 5,
"width": 560,
"height": 120,
"content": "### \ud83d\udc68\u200d\ud83c\udfa4 Setup\n1. Add your **postgresql** and **OpenAI** credentials.\n2. Click **Chat** button and start asking questions to your database.\n3. Activate the workflow and you can make the chat publicly available."
},
"typeVersion": 1
},
{
"id": "0df33341-c859-4a54-b6d9-a99670e8d76d",
"name": "Chat History",
"type": "@n8n/n8n-nodes-langchain.memoryBufferWindow",
"position": [
120,
160
],
"parameters": {},
"typeVersion": 1.3
},
{
"id": "4938b22e-f187-4ca0-b9f1-60835e823799",
"name": "Sticky Note3",
"type": "n8n-nodes-base.stickyNote",
"position": [
360,
300
],
"parameters": {
"color": 7,
"width": 562,
"height": 156,
"content": "\ud83d\udee0\ufe0f Tools Used:\n1. Execute SQL Query: Used to execute any query generated by the agent.\n2. Get DB Schema and Tables List: It returns the list of all the tables with its schema name.\n3. Get Table Definition: It returns table details like column names, foreign keys and more of a particular table in a schema."
},
"typeVersion": 1
},
{
"id": "39780c78-4fbc-403e-a220-aa6a4b06df8c",
"name": "Sticky Note1",
"type": "n8n-nodes-base.stickyNote",
"position": [
-100,
300
],
"parameters": {
"color": 7,
"width": 162,
"height": 99,
"content": "\ud83d\udc46 You can exchange this with any other chat model of your choice."
},
"typeVersion": 1
},
{
"id": "28a5692c-5003-46cb-9a09-b7867734f446",
"name": "Sticky Note2",
"type": "n8n-nodes-base.stickyNote",
"position": [
100,
300
],
"parameters": {
"color": 7,
"width": 162,
"height": 159,
"content": "\ud83d\udc46 You can change how many number of messages to keep using `Context Window Length` option. It's 5 by default."
},
"typeVersion": 1
},
{
"id": "c18ced71-6330-4ba0-9c52-1bb5852b3039",
"name": "Execute SQL Query",
"type": "n8n-nodes-base.postgresTool",
"position": [
380,
140
],
"parameters": {
"query": "{{ $fromAI(\"sql_query\", \"SQL Query\") }}",
"options": {},
"operation": "executeQuery",
"descriptionType": "manual",
"toolDescription": "Get all the data from Postgres, make sure you append the tables with correct schema. Every table is associated with some schema in the database."
},
"credentials": {
"postgres": {
"name": "<your credential>"
}
},
"typeVersion": 2.5
},
{
"id": "557623c6-e499-48a6-a066-744f64f8b6f3",
"name": "Get DB Schema and Tables List",
"type": "n8n-nodes-base.postgresTool",
"position": [
580,
140
],
"parameters": {
"query": "SELECT \n table_schema,\n table_name\nFROM information_schema.tables\nWHERE table_type = 'BASE TABLE'\n AND table_schema NOT IN ('pg_catalog', 'information_schema')\nORDER BY table_schema, table_name;",
"options": {},
"operation": "executeQuery",
"descriptionType": "manual",
"toolDescription": "Get list of all tables with their schema in the database"
},
"credentials": {
"postgres": {
"name": "<your credential>"
}
},
"typeVersion": 2.5
}
],
"active": false,
"settings": {
"executionOrder": "v1"
},
"versionId": "10c7c74e-b383-4ac7-8cb2-c9a15a2818fe",
"connections": {
"Chat History": {
"ai_memory": [
[
{
"node": "AI Agent",
"type": "ai_memory",
"index": 0
}
]
]
},
"Execute SQL Query": {
"ai_tool": [
[
{
"node": "AI Agent",
"type": "ai_tool",
"index": 0
}
]
]
},
"OpenAI Chat Model": {
"ai_languageModel": [
[
{
"node": "AI Agent",
"type": "ai_languageModel",
"index": 0
}
]
]
},
"Get Table Definition": {
"ai_tool": [
[
{
"node": "AI Agent",
"type": "ai_tool",
"index": 0
}
]
]
},
"When chat message received": {
"main": [
[
{
"node": "AI Agent",
"type": "main",
"index": 0
}
]
]
},
"Get DB Schema and Tables List": {
"ai_tool": [
[
{
"node": "AI Agent",
"type": "ai_tool",
"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.
openAiApipostgres
Pro
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About this workflow
Chat with Postgresql Database. Uses chatTrigger, agent, lmChatOpenAi, postgresTool. Chat trigger; 11 nodes.
Source: https://github.com/Zie619/n8n-workflows — original creator credit. Request a take-down →
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