Amazon product search scraper with BrightData, GPT-4, and Google Sheets
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 10 nodes and runs manually, when you click “Execute workflow”. Along the way it connects OpenRouter Chat Model and Google Sheets. It also calls api.brightdata.com over HTTP.
How it runs
Trigger: Manually, when you click “Execute workflow”.
- get urls to scrape (Google Sheets): uses Google Sheets
- url (Loop Over Items (Split in Batches)): loops over the items in batches
- scrap url (HTTP Request): calls api.brightdata.com (POST)
- clean html (Code): runs custom JavaScript code
- extract data (Basic LLM Chain): sends a prompt to an LLM, with model: OpenRouter Chat Model; output parser: Structured Output Parser
- Split items (Split Out): splits a list into separate items
- add results (Google Sheets): append
Services it uses
HTTP calls to: api.brightdata.com
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 (9)
- OpenRouter Chat Model
@n8n/n8n-nodes-langchain.lmChatOpenRouter - Structured Output Parser
@n8n/n8n-nodes-langchain.outputParserStructured - HTTP Request
n8n-nodes-base.httpRequest - Manual Trigger
n8n-nodes-base.manualTrigger - Loop Over Items (Split in Batches)
n8n-nodes-base.splitInBatches - Google Sheets
n8n-nodes-base.googleSheets - Code
n8n-nodes-base.code - Basic LLM Chain
@n8n/n8n-nodes-langchain.chainLlm - Split Out
n8n-nodes-base.splitOut
From the author
This workflow automates web scraping of Amazon search result pages by retrieving raw HTML, cleaning it to retain only the relevant product elements, and then using an LLM to extract structured product data (name, description, rating, reviews, and price),…