Chat with Postgresql database

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Important notice

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

1. Workflow Overview

Who is this template for? This workflow template is designed for any professionals seeking relevent data from database using natural language. How it works Each time user ask's question using the n...

Best for

Internal Wiki automation workflows
AI Chatbot 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-nodes-base.postgrestool, n8n-nodes-base.stickynote, @n8n/n8n-nodes-langchain.memorybufferwindow

Source and attribution

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

Original n8n.io source

1.1 Workflow description

Title: Chat with Postgresql database
Workflow name: Chat with Postgresql database

Who is this template for?

This workflow template is designed for any professionals seeking relevent data from database using natural language.

How it works

Each time user ask's question using the n8n chat interface, the workflow runs.
Then the message is processed by AI Agent using relevent tools - Execute SQL Query, Get DB Schema and Tables List and Get Table Definition, if required. Agent uses these tool to form and run sql query which are necessary to answer the questions.
Once AI Agent has the data, it uses it to form answer and returns it to the user.

Set up instructions

Complete the Set up credentials step when you first open the workflow. You'll need a Postgresql Credentials, and OpenAI api key.

Template was created in n8n v1.77.0

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 1.7

Block 3 - OpenAI Chat Model

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

Block 4 - Get Table Definition

Type / Role: n8n-nodes-base.postgresTool - postgresTool
Config choices: Version 2.5

Block 5 - Sticky Note

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

Block 6 - Chat History

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

Block 7 - Sticky Note3

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

Block 9 - Sticky Note2

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

Block 10 - Execute SQL Query

Type / Role: n8n-nodes-base.postgresTool - postgresTool
Config choices: Version 2.5

Block 11 - Get DB Schema and Tables List

Type / Role: n8n-nodes-base.postgresTool - postgresTool
Config choices: Version 2.5

3. Summary Table

Workflow	Chat with Postgresql database
Complexity	intermediate
Nodes	11
Categories	Internal Wiki, AI Chatbot
Author	KumoHQ
Published	07 Feb 2025

4. Reproducing the Workflow from Scratch

1. Download the workflow JSON

Use the JSON export at /data/workflows/2859/2859.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 Internal Wiki workflows AI Chatbot workflows

Frequently asked questions

What does Chat with Postgresql database 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 Internal Wiki, AI Chatbot use case.

KumoHQ

1 workflow

Nodes

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

Complexity

intermediate

Published 07 Feb 2025

Likes 0

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Install path: /data/workflows/2859/2859.json

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Chat with Postgresql database

Workflow preview

Important notice

1. Workflow Overview

Best for

Tools used

Source and attribution

1.1 Workflow description

Who is this template for?

How it works

Set up instructions

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 - Get Table Definition

Block 5 - Sticky Note

Block 6 - Chat History

Block 7 - Sticky Note3

Block 8 - Sticky Note1

Block 9 - Sticky Note2

Block 10 - Execute SQL Query

Block 11 - Get DB Schema and Tables List

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