Research involved to set up

Web Content Ingestion and RAG Chat

Ingests URLs into a vector database for accurate, cited Q&A using AI retrieval and reranking.

Verified 2026-07-07

Developer-EngineeringData-Analyst

What it does

You get instant access to any website's content through a chat interface that answers your questions with accurate citations. This agent scrapes the specified URL, stores its knowledge securely, and uses AI retrieval to provide high-quality responses tailored to your queries.

How it works

When it runs: Triggered by an event · Event · on webhook URL submission
How hands-off: Assists you, you do the final step
Setup: A bigger project · a few focused days
Works with: n8n, Firecrawl, Supabase, OpenAI, Cohere

Tools that fit

Services

n8n : Workflow orchestration and chat interface

Supabase : Vector storage and database management

api

Firecrawl : Web scraping to markdown

LLM

OpenAI : Generating vector embeddings

Cohere : Reranking retrieval results

Watch out for

Firecrawl may block requests from data centers, so configure a residential proxy or use their enterprise API key.
Supabase vector dimensions must match the OpenAI embedding model output size exactly to avoid insertion errors.
Cohere reranking adds latency to each query, so implement caching for frequent similar questions to improve response times.
Webhook payloads can be large if scraping deep pages, so increase n8n's payload limit or stream data in chunks.

Seen in the wild

n8n: Scrape and ingest web content into Supabase pgvector with Firecrawl template

Want this running in your business?

This is what I do. I design and build AI agents like this one, and keep them running. If you want it set up for your team instead of doing it yourself, get in touch.

Get in touch

Who it's for

Built for developers who want the busywork around code automated, not the code itself.

Analysts get a ready-made pattern for turning raw numbers into a report someone will actually read.

Frequently asked questions

Who is this for?

developers and engineers and data analysts, or anyone doing research work who wants this handled automatically rather than manually.

How long does it take to set up?

A bigger project: plan for a few focused days to get it running end to end.

Related use cases

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