Query MySQL database with natural language using GPT AI

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Important notice

This workflow is provided as-is. Please review and test before using in production.

1. Workflow Overview

This workflow contains community nodes that are only compatible with the self hosted version of n8n. How it works Using chat node, ask a question pertaining to information stored in your MySQL data...

Best for

Engineering automation workflows
AI RAG automation workflows
intermediate n8n builders looking for reusable templates

Tools used

@n8n/n8n-nodes-langchain.chattrigger, @n8n/n8n-nodes-langchain.agent, @n8n/n8n-nodes-langchain.lmchatopenai, @n8n/n8n-nodes-langchain.memorybufferwindow, n8n-nodes-base.mysqltool, n8n-nodes-base.stickynote

Source and attribution

This workflow is cataloged by N8N Workflows and links back to its original n8n.io source page by Moe Ahad.

Original n8n.io source

1.1 Workflow description

Title: Query MySQL database with natural language using GPT AI
Workflow name: Query MySQL database with natural language using GPT AI

This workflow contains community nodes that are only compatible with the self-hosted version of n8n.

How it works

Using chat node, ask a question pertaining to information stored in your MySQL database
AI Agent converts your question to a SQL query
AI Agent executes the SQL query and returns a result
AI Agent can remember the previous 5 questions

How to set up:

Add your OpenAI API Key in "OpenAI Chat Model" node
Add your MySQL credentials in the "SQL DB - List Tables and Schema" and "Execute a SQL Query in MySQL nodes"
Update the database name in "SQL DB - List Tables and Schema" node. Replace "your_query_name" under the Query field with your actual database name
After the above steps are completed, use the "When chat message received" node to ask a question about your data using plain English

1.2 Logical Blocks

This catalog entry is organized from the workflow JSON. The node-level section below shows the executable blocks available for review before importing the template.

2. Block-by-Block Analysis

Block 1 - When chat message received

Type / Role: @n8n/n8n-nodes-langchain.chatTrigger - chatTrigger
Config choices: Version 1.1

Block 2 - AI Agent

Type / Role: @n8n/n8n-nodes-langchain.agent - agent
Config choices: Version 2.1

Block 3 - OpenAI Chat Model

Type / Role: @n8n/n8n-nodes-langchain.lmChatOpenAi - lmChatOpenAi
Config choices: Version 1.2

Block 4 - Simple Memory

Type / Role: @n8n/n8n-nodes-langchain.memoryBufferWindow - memoryBufferWindow
Config choices: Version 1.3

Block 5 - SQL DB - List Tables and Schema

Type / Role: n8n-nodes-base.mySqlTool - mySqlTool
Config choices: Version 2.4

Block 6 - Execute a SQL query in MySQL

Type / Role: n8n-nodes-base.mySqlTool - mySqlTool
Config choices: Version 2.4

Block 7 - Sticky Note

Type / Role: n8n-nodes-base.stickyNote - stickyNote
Config choices: Version 1

Block 8 - Sticky Note1

Type / Role: n8n-nodes-base.stickyNote - stickyNote
Config choices: Version 1

3. Summary Table

Workflow	Query MySQL database with natural language using GPT AI
Complexity	intermediate
Nodes	8
Categories	Engineering, AI RAG
Author	Moe Ahad
Published	22 Jul 2025

4. Reproducing the Workflow from Scratch

1. Download the workflow JSON

Use the JSON export at /data/workflows/6291/6291.json as the source template for this automation.
2. Import the template into n8n

Open n8n, import the downloaded JSON, and review each node before activating the workflow.
3. Configure credentials and variables

Replace placeholder credentials, API keys, webhook URLs, account IDs, and environment-specific values with your own settings.
4. Test with sample data

Run the workflow manually or in a staging workspace, inspect node output, and confirm downstream systems receive the expected data.
5. Activate and monitor

Enable the workflow only after testing, then monitor executions, errors, and rate limits during the first production runs.

5. General Notes & Resources

Review imported nodes carefully before activation. This catalog entry is intended to help you inspect the workflow structure, understand required services, and find related templates faster.

Node names, credentials, schedules, webhook paths, and external service limits may need adjustment for your workspace.

Download workflow JSON Original n8n.io source Engineering workflows AI RAG workflows

Frequently asked questions

What does Query MySQL database with natural language using GPT AI do?

What do I need before importing this workflow?

Review the workflow JSON, configure any required credentials in n8n, and test the automation in a safe workspace before using it in production.

Can I customize this workflow?

Yes. Use the block-by-block analysis and the downloadable JSON to inspect each node, then adjust credentials, prompts, schedules, filters, or destinations for your Engineering, AI RAG use case.

Moe Ahad

3 workflows

Nodes

@n8n/n8n-nodes-langchain.chattrigger @n8n/n8n-nodes-langchain.agent @n8n/n8n-nodes-langchain.lmchatopenai @n8n/n8n-nodes-langchain.memorybufferwindow n8n-nodes-base.mysqltool n8n-nodes-base.stickynote

Complexity

intermediate

Published 22 Jul 2025

Likes 0

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Install path: /data/workflows/6291/6291.json

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Query MySQL database with natural language using GPT AI

Workflow preview

Important notice

1. Workflow Overview

Best for

Tools used

Source and attribution

1.1 Workflow description

How it works

How to set up:

1.2 Logical Blocks

2. Block-by-Block Analysis

Block 1 - When chat message received

Block 2 - AI Agent

Block 3 - OpenAI Chat Model

Block 4 - Simple Memory

Block 5 - SQL DB - List Tables and Schema

Block 6 - Execute a SQL query in MySQL

Block 7 - Sticky Note

Block 8 - Sticky Note1

3. Summary Table

4. Reproducing the Workflow from Scratch

1. Download the workflow JSON

2. Import the template into n8n

3. Configure credentials and variables

4. Test with sample data

5. Activate and monitor

5. General Notes & Resources

Frequently asked questions