AutomationFlows › Recipes › Chat Trigger → Supabase

Chat Trigger → Supabase

When you need Chat Trigger and Supabase talking to each other, here are the 64 n8n workflows in the catalog that already do it. Each is integration-tagged and privacy-stripped — copy the JSON and import.

Workflows that pair Chat Trigger with Supabase

AI & RAG
Google Drive to Supabase Contextual Vector Database Sync for RAG Applications

• Create a Google Drive folder to watch. • Connect your Google Drive account in n8n and authorize access. • Point the Google Drive Trigger node to this folder (new/modified files trigger the flow).

Agent, Chat Trigger, Memory Buffer Window +14
AI & RAG
Chat with Docs - 5minai New Version

Chat with docs - 5minAI New version. Uses httpRequest, documentDefaultDataLoader, textSplitterRecursiveCharacterTextSplitter, embeddingsOpenAi. Event-driven trigger; 62 nodes.

HTTP Request, Document Default Data Loader, Text Splitter Recursive Character Text Splitter +10
AI & RAG
AI Agent to Chat with Files in Supabase Storage and Google Drive

I prepared a detailed guide that illustrates the entire process of building an AI agent using Supabase and Google Drive within N8N workflows.

HTTP Request, Document Default Data Loader, Text Splitter Recursive Character Text Splitter +10
AI & RAG
Youtube Agent

YouTube Agent. Uses supabase, agent, lmChatAnthropic, outputParserStructured. Webhook trigger; 56 nodes.

Supabase, Agent, Anthropic Chat +10
AI & RAG
🤖 Create a Documentation Expert Bot with Rag, Gemini, and Supabase

This template is a complete, hands-on tutorial for building a RAG (Retrieval-Augmented Generation) pipeline. In simple terms, you'll teach an AI to become an expert on a specific topic—in this case, t

Memory Buffer Window, Supabase Vector Store, Document Default Data Loader +8
AI & RAG
My Workflow 2529

My workflow 2529. Uses lmChatOpenAi, documentDefaultDataLoader, embeddingsOpenAi, googleDrive. Event-driven trigger; 54 nodes.

OpenAI Chat, Document Default Data Loader, OpenAI Embeddings +11
AI & RAG
Base_to_copy

05. Base_To_Copy. Uses lmChatOpenAi, documentDefaultDataLoader, embeddingsOpenAi, googleDrive. Event-driven trigger; 54 nodes.

OpenAI Chat, Document Default Data Loader, OpenAI Embeddings +11
AI & RAG
Wordpress AI Chatbot to Enhance User Experience with Supabase and Openai

Wordpress Ai Chatbot To Enhance User Experience With Supabase And Openai. Uses manualTrigger, embeddingsOpenAi, documentDefaultDataLoader, textSplitterTokenSplitter. Event-driven trigger; 53 nodes.

OpenAI Embeddings, Document Default Data Loader, Text Splitter Token Splitter +9
AI & RAG
RAG & Genai App with Wordpress Content

RAG & GenAI App With WordPress Content. Uses manualTrigger, embeddingsOpenAi, documentDefaultDataLoader, textSplitterTokenSplitter. Event-driven trigger; 53 nodes.

OpenAI Embeddings, Document Default Data Loader, Text Splitter Token Splitter +9
AI & RAG
RAG & Genai App with Wordpress Content (embeddings Open Ai)

RAG & GenAI App With WordPress Content. Uses manualTrigger, embeddingsOpenAi, documentDefaultDataLoader, textSplitterTokenSplitter. Event-driven trigger; 53 nodes.

OpenAI Embeddings, Document Default Data Loader, Text Splitter Token Splitter +9
AI & RAG
Agente_rag

Agente_RAG. Uses supabase, embeddingsOpenAi, documentDefaultDataLoader, textSplitterCharacterTextSplitter. Chat trigger; 50 nodes.

Supabase, OpenAI Embeddings, Document Default Data Loader +9
AI & RAG
Interactive Knowledge Base Chat with Supabase RAG Using AI 📚💬

This n8n workflow automates the process of ingesting files from Google Drive into a Supabase database, preparing them for a knowledge base system. It supports text-based files (PDF, DOCX, TXT, etc.) a

Google Drive Trigger, Postgres, Supabase +11
AI & RAG
Create a Self-updating RAG Chatbot with Google Drive, Gemini, and Supabase

This template creates a comprehensive, production-ready Retrieval-Augmented Generation (RAG) system. It builds a sophisticated AI agent that can answer questions based on documents stored in a specifi

Reranker Cohere, Supabase Vector Store, Agent +10
AI & RAG
Yt Processing Updated

YT Processing UPDATED. Uses googleSheets, youTube, httpRequest, googleDrive. Event-driven trigger; 44 nodes.

Google Sheets, YouTube, HTTP Request +11
AI & RAG
Ultimate Agentic RAG AI Agent Template

Ultimate Agentic RAG AI Agent Template. Uses lmChatOpenAi, documentDefaultDataLoader, embeddingsOpenAi, stickyNote. Event-driven trigger; 42 nodes.

OpenAI Chat, Document Default Data Loader, OpenAI Embeddings +10
AI & RAG
N8n RAG AI Agent

n8n RAG AI Agent. Uses lmChatOpenAi, documentDefaultDataLoader, embeddingsOpenAi, googleDrive. Event-driven trigger; 41 nodes.

OpenAI Chat, Document Default Data Loader, OpenAI Embeddings +10
AI & RAG
Index Google Drive Files Into a Supabase Vector Store with Openai Embeddings

📺 Full walkthrough video: https://youtu.be/r5kN_la0O7I

Document Default Data Loader, OpenAI Embeddings, Google Drive +6
AI & RAG
Document-based RAG Chat Assistant with Google Drive, Supabase & Openai

This RAG workflow allows you to build a smart chat assistant that can answer user questions based on any collection of documents you provide. It automatically imports and processes files from Google D

Agent, OpenAI Chat, Supabase Vector Store +7
AI & RAG
Indoor Farming Agent

Indoor Farming Agent. Uses lmChatOpenAi, documentDefaultDataLoader, embeddingsOpenAi, toolVectorStore. Webhook trigger; 36 nodes.

OpenAI Chat, Document Default Data Loader, OpenAI Embeddings +16
AI & RAG
Outreach for Your Product Using Apollo, Linkedin, Gpt-4.1 and Sendgrid

> 💛 Sticky Note: > This Hyperpersonalized Outreach n8n template automates AI‑powered B2B email campaigns by combining Apollo.io lead scraping, LinkedIn enrichment, GPT‑4 generation, and SendGrid

HTTP Request, Supabase, Output Parser Structured +4
AI & RAG
Google Drive to Pinecone Vector Storage Workflow

This workflow creates a conversational assistant that can answer questions based on your Google Drive documents. It automatically processes various file types and uses Retrieval-Augmented Generation (

OpenAI Chat, Document Default Data Loader, OpenAI Embeddings +9
AI & RAG
Upsert Huge Documents in a Vector Store with Supabase and Notion

Upsert Huge Documents In A Vector Store With Supabase And Notion. Uses embeddingsOpenAi, textSplitterTokenSplitter, splitInBatches, chainRetrievalQa. Chat trigger; 34 nodes.

OpenAI Embeddings, Text Splitter Token Splitter, Chain Retrieval Qa +8
AI & RAG
RAG on Living Data

RAG on living data. Uses embeddingsOpenAi, textSplitterTokenSplitter, splitInBatches, chainRetrievalQa. Chat trigger; 34 nodes.

OpenAI Embeddings, Text Splitter Token Splitter, Chain Retrieval Qa +8
AI & RAG
Upsert Huge Documents in a Vector Store with Supabase and Notion (embeddings Open Ai)

This workflow adds the capability to build a RAG on living data. In this case Notion is used as a Knowledge Base. Whenever a page is updated, the embeddings get upserted in a Supabase Vector Store.

OpenAI Embeddings, Text Splitter Token Splitter, Chain Retrieval Qa +8

See more Chat Trigger workflows · Supabase workflows

FAQ

How do I trigger a Supabase action from Chat Trigger?

Most workflows in this list use either a Chat Trigger webhook trigger (real-time) or a polling trigger (every N minutes). From there, downstream Supabase nodes handle the action. Open any workflow's detail page to see the exact node graph.

Do I need both a Chat Trigger and a Supabase account?

Yes — n8n connects to each integration via your own credentials. AutomationFlows strips credential IDs before publishing, so you'll add your own.

Are these Chat Trigger → Supabase workflows free?

Yes — every workflow on AutomationFlows is free to browse and copy. Pro adds a multi-signal QualityScore on every workflow plus bulk JSON download.