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Chat with Postgresql Database

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

Engine
n8n
Nodes
11
Trigger
scheduled/triggered
Source file
1377_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

Chat with Postgresql Database is a free n8n workflow on OpenRuna — 11 nodes connecting chat, agent, lmChatOpenAi, postgresTool, memoryBufferWindow. Download the JSON, view the flow diagram, and import it into your n8n instance.

What this workflow does

This n8n workflow, "Chat with Postgresql Database", wires together chat, agent, lmChatOpenAi, postgresTool, memoryBufferWindow in 11 nodes. 11 nodes · chat, agent, lmChatOpenAi, postgresTool, memoryBufferWindow A scheduled/triggered entry point kicks it off, and each node passes data to the next until the run completes. OpenRuna shows the full flow diagram, an integration breakdown, and a one-click JSON export for n8n's "Import from file". Use it to learn integration patterns, fork it for your own use case, or deploy it quickly after reconnecting credentials.

Use cases

  • Fork it to add error handling, retries, or a notification step without designing the 11-node flow from scratch.
  • Benchmark it against your current chat integration to spot missing steps or redundant nodes.
  • Import "Chat with Postgresql Database" into n8n, reconnect credentials for chat, agent, lmChatOpenAi, postgresTool, memoryBufferWindow, and run the same automation in your own workspace.
  • Use it as a starting template when wiring chat, agent, lmChatOpenAi, postgresTool, memoryBufferWindow — adjust node parameters to your accounts and record IDs.

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

Ask Claude to turn the "Chat with Postgresql Database" JSON into a plain-English runbook, node by node. It can flag where chat rate limits or missing retries might bite before you go live.

ChatGPT

Drop the workflow JSON or this OpenRuna page URL into ChatGPT and ask for a step-by-step runbook: triggers, branches, and which fields to customise for chat, agent, lmChatOpenAi, postgresTool, memoryBufferWindow. Handy for onboarding teammates new to n8n.

Cursor

In Cursor, ask Agent mode to parameterise "Chat with Postgresql Database" — extract chat IDs and secrets into environment variables without changing the 11-node structure.

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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