(5/5)

Chat with Postgresql Database

Automated workflow: Chat with Postgresql Database. This workflow integrates 7 different services: postgresTool, stickyNote, agent, stopAndError, lmChatOpenAi. It contains 12 nodes and follows best practices for error handling and security.

Integrations Used (1)

Postgrestool

Workflow Structure (9 nodes)

100%

No Op

When chat message received

No Op

AI Agent

Manual Trigger

No Op

OpenAI Chat Model

No Op

Chat History

Postgres Tool

Execute SQL Query

Postgres Tool

Get DB Schema and Tables List

Postgres Tool

Get Table Definition

Stop And Error

Error Handler

Node Types:

trigger

default

action

Requires credentials

Prerequisites

Required Credentials (2)

OpenAI

Used by: OpenAI Chat Model

Docs

Postgres

Used by: Get Table Definition, Execute SQL Query +1 more

Docs

Complexity

Moderate

Some experience helpful. Multiple integrations or logic.

Setup time: ~25 min

Score: 33/100

4 Integrations

When to Use This Workflow

Real-time Response

React instantly when events happen - new orders, form submissions, or API calls.

Zero delay between trigger and action for time-sensitive workflows.

Time Savings

Replace repetitive manual tasks with reliable automation.

Reclaim hours every week for higher-value work.

Error Reduction

Eliminate human error from routine processes with consistent automation.

Improve accuracy and reliability across your workflows.

workflow.json

{
  "id": "eOUewYsEzJmQixI6",
  "meta": {
    "instanceId": "workflow-9636cd46",
    "versionId": "1.0.0",
    "createdAt": "2025-09-29T07:07:51.494758",
    "updatedAt": "2025-09-29T07:07:51.494774",
    "owner": "n8n-user",
    "license": "MIT",
    "category": "automation",
    "status": "active",
    "priority": "high",
    "environment": "production"
  },
  "name": "Chat with Postgresql Database",
  "tags": [
    "automation",
    "n8n",
    "production-ready",
    "excellent",
...