RAG chat assistant with Claude, Supabase vector store, and Postgres memory
Ready for 3.0Ready for 3.0. This template uses no nodes that n8n 3.0 removes. No removed nodes, versions or helpers found. Static check, last run 2026-10-19.
What this workflow does
This AI workflow has 6 nodes and runs when a chat message arrives. Along the way it connects Postgres Chat Memory, Supabase Vector Store, Embeddings OpenAI and Anthropic Chat Model.
How it runs
Trigger: When a chat message arrives.
- Chat Assistant Agent (AI Agent): runs an AI agent, with model: Claude Sonnet 4.6 Model; 1 tool (Retrieve from Supabase Vectors); memory: Store Chat History in Postgres
Services it uses
Before you upgrade to n8n 3.0
Nothing in this workflow is removed in n8n 3.0, so it should import and run after the upgrade.
Nodes used (6)
- AI Agent
@n8n/n8n-nodes-langchain.agent - Postgres Chat Memory
@n8n/n8n-nodes-langchain.memoryPostgresChat - Supabase Vector Store
@n8n/n8n-nodes-langchain.vectorStoreSupabase - Embeddings OpenAI
@n8n/n8n-nodes-langchain.embeddingsOpenAi - Chat Trigger
@n8n/n8n-nodes-langchain.chatTrigger - Anthropic Chat Model
@n8n/n8n-nodes-langchain.lmChatAnthropic
From the author
📺 Full walkthrough video: https://youtu.be/ZlT22px3U Who it's for This workflow is for developers and AI builders who want to deploy a context-aware chat assistant powered by a private knowledge base. It suits teams that need persistent conversation memory…