(5/5)

SQL agent with memory

Automated workflow: SQL agent with memory. This workflow integrates 11 different services: stickyNote, httpRequest, compression, readWriteFile, agent. It contains 18 nodes and follows best practices for error handling and security.

Integrations Used (3)

HTTP Request

Compression

Readwritefile

Workflow Structure (10 nodes)

100%

Manual Trigger

When clicking "Test workflow"

Http Request

Get chinook.zip example

Compression

Extract zip file

Read Write File

Save chinook.db locally

No Op

Chat Trigger

Read Write File

Load local chinook.db

Set

Combine chat input with the binary

No Op

OpenAI Chat Model

No Op

AI Agent

No Op

Window Buffer Memory

Node Types:

default

trigger

http

transform

Requires credentials

Prerequisites

Required Credentials (1)

OpenAI

Used by: OpenAI Chat Model

Docs

Complexity

Moderate

Some experience helpful. Multiple integrations or logic.

Setup time: ~20 min

Score: 30/100

5 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": "AQJ6QnF2yVdCWMnx",
  "meta": {
    "instanceId": "workflow-fdfb95b2",
    "versionId": "1.0.0",
    "createdAt": "2025-09-29T07:07:43.980162",
    "updatedAt": "2025-09-29T07:07:43.980180",
    "owner": "n8n-user",
    "license": "MIT",
    "category": "automation",
    "status": "active",
    "priority": "high",
    "environment": "production"
  },
  "name": "SQL agent with memory",
  "tags": [
    "automation",
    "n8n",
    "production-ready",
    "excellent",
...