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Chat with Postgresql Database

11 nodes · chat, agent, lmChatOpenAi, postgresTool, memoryBufferWindow

Engine
n8n
Nodes
11
Trigger
scheduled/triggered
Source file
1848_Postgrestool_Stickynote_Automation_Triggered.json

Workflow flow

IntegrationsChatAgentLmChatOpenAiPostgresToolMemoryBufferWindow@n8n/n8n-nodes-langchain.chat@n8n/n8n-nodes-langchain.agent@n8n/n8n-nodes-langchain.lmChatOpenAi@n8n/n8n-nodes-langchain.memoryBufferWindow
100%
TRIGGER

When chat message received

@n8n/n8n-nodes-langchain.chat

OpenAI Chat Model

@n8n/n8n-nodes-langchain.lmChatOpenAi

Get Table Definition

PostgresTool

Chat History

@n8n/n8n-nodes-langchain.memoryBufferWindow

Execute SQL Query

PostgresTool

Get DB Schema and Tables List

PostgresTool

AI Agent

@n8n/n8n-nodes-langchain.agent

7 steps · flows top to bottom, branches left to right

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chatagentlmChatOpenAipostgresToolmemoryBufferWindow
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Download n8n JSONDownload sanitized JSONDownload flow graph

Import into n8n

  1. Download the n8n JSON file (full or sanitized).
  2. In n8n: Workflows → Import from file.
  3. Open each node and reconnect credentials to your accounts.
  4. Test with manual execution before enabling triggers.

Sanitized JSON removes credential IDs — safer for sharing. Flow graph JSON is OpenRuna's lightweight format for diagrams and other tools, not n8n import.

View source corpus ↗

Overview

Free n8n workflow: Chat with Postgresql Database. 11 nodes across chat, agent, lmChatOpenAi, postgresTool, memoryBufferWindow, with a downloadable JSON and a visual flow diagram on OpenRuna.

What this workflow does

"Chat with Postgresql Database" automates a chat-to-agent flow in n8n across 11 nodes. 11 nodes · chat, agent, lmChatOpenAi, postgresTool, memoryBufferWindow It starts from a scheduled/triggered trigger and routes data through every node in order. OpenRuna renders the node graph and offers the JSON export so you can import and adapt it in minutes. Use it to learn integration patterns, fork it for your own use case, or deploy it quickly after reconnecting credentials.

Use cases

  • Share it with your team as a documented reference for scheduled/triggered automations in the chat stack.
  • Study how data moves from chat to agent before building your own variant.
  • Use it as a starting template when wiring chat, agent, lmChatOpenAi, postgresTool, memoryBufferWindow — adjust node parameters to your accounts and record IDs.
  • Import "Chat with Postgresql Database" into n8n, reconnect credentials for chat, agent, lmChatOpenAi, postgresTool, memoryBufferWindow, and run the same automation in your own workspace.

Example output

Imported into n8n, "Chat with Postgresql Database" exposes 11 configured nodes. Trigger type: scheduled/triggered. Integrations: chat, agent, lmChatOpenAi, postgresTool, memoryBufferWindow. Open each node after import to map credentials to your own chat and agent accounts. Run it once in test mode to verify any branch logic (Switch/IF nodes) before enabling production triggers.

Tips by platform

Claude

Paste the exported JSON for "Chat with Postgresql Database" into Claude and ask it to explain each of the 11 nodes. Claude is good at suggesting credential mappings for chat, agent, lmChatOpenAi, postgresTool, memoryBufferWindow, plus error-handling and idempotency improvements before you run it in production.

ChatGPT

Have ChatGPT generate a checklist for adapting "Chat with Postgresql Database" to your accounts — which chat, agent, lmChatOpenAi, postgresTool, memoryBufferWindow credentials to create and which node parameters to change first.

Cursor

Open the downloaded JSON in Cursor and use Agent mode to refactor hard-coded URLs into env vars, or to generate tests for any Code nodes. Keep the OpenRuna flow diagram open so you do not break connection order across the 11 nodes.

Frequently asked questions

How do I import "Chat with Postgresql Database" into n8n?
Click Download n8n JSON on this page, then in n8n choose Workflows → Import from file and select the downloaded file. Reconnect credentials on each node — the export carries credential IDs from the original author's instance, not working secrets.
Which integrations does "Chat with Postgresql Database" use?
It uses: chat, agent, lmChatOpenAi, postgresTool, memoryBufferWindow. The flow diagram above shows how each service connects across the 11 nodes. Filter OpenRuna by integration to find related workflows and tools.
Can I import a sanitized export without credentials?
Yes. Use "Download sanitized JSON" to strip credential references before sharing internally. You will still add your own chat and agent credentials in n8n after import.
What trigger type does "Chat with Postgresql Database" use?
Trigger type: scheduled/triggered. After import, confirm the trigger node (webhook, schedule, or app event) matches your environment, then activate the workflow when you are ready to run it.
Is "Chat with Postgresql Database" free to use?
OpenRuna catalogs community n8n workflows under open licenses. Check the source corpus link for the original license; commercial use may require verifying the third-party API terms for chat, agent, lmChatOpenAi, postgresTool, memoryBufferWindow.

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