Amazon Products & Search Scraper

Export public Amazon search results or look up ASINs and product URLs across ten marketplaces. This Amazon products scraper returns ASINs, titles, visible prices, ratings, review counts, images, and source information for assortment research and product discovery. Optional details add available seller, availability, and variant fields.

Provide at least one query, URL, or ASIN, then start with a small product limit. Amazon can restrict access, and optional fields are not available for every product.

Quick start

Start with the small input below, run the Actor and inspect its results.

{
  "queries": [
    "wireless headphones"
  ],
  "marketplace": "US",
  "sort": "relevance",
  "maxItems": 20,
  "enrichDetails": false,
  "detailCacheMaxAgeMinutes": 60,
  "proxyMode": "auto"
}

Prefer a video guide? This short Apify walkthrough shows you how to set up and run an Actor. It uses a different Actor, but the setup steps are the same.

What you get

Each dataset row represents one Amazon product listing:

• Search provenance: observed listing position (including sponsored placements), sponsored status, source query, and marketplace. rank is a page-based estimate, not an organic-only rank or a guaranteed global position.
• Product identity: ASIN, parent and variant ASINs, title, brand, categories, URL, and image URLs.
• Commercial signals: numeric/display/list price, currency, deal, savings, Prime, shipping, availability, seller, and Buy Box seller.
• Social proof: numeric rating and review count.
• Provenance: source type/query, marketplace, page number, enrichment status, and scrape timestamp.

Fields	Meaning
asin, productTitle, url	Product identity and public source link.
rank, sponsored, sourceQuery	Search position estimate and placement context. Position/query are null for direct product inputs.
price, priceDisplay, currency, rating, reviewCount, prime	Available listing signals. currency is a displayed symbol, not an ISO code.
brand, parentAsin, categoryBreadcrumb, listPrice, deal, savingsPercent	Optional detail fields. Unavailable values remain null or empty.
shipping, availability, seller, buyBoxSoldBy, variants, imageUrls	Visible detail fields and variant ASINs, when available.
sourceType, marketplace, scrapedAt, diagnostics	Input provenance, collection time, and optional detail source/time.

Search-only rows do not contain review text or full product descriptions. Detail extraction is best-effort, not a promise that every field will be populated.

Who is it for?

This Actor is designed for ecommerce analysts, marketplace sellers, brand-protection teams, pricing researchers, retail agencies, and developers building product intelligence workflows.

How you can use the data

• Build a focused assortment sheet. Search wireless headphones on the US marketplace with a small product cap. Export asin, productTitle, url, priceDisplay, currency and available ratings for manual comparison.
• Review observed search placements. Keep sourceQuery, rank and sponsored together. The rank includes sponsored placements and is a page-based estimate. Deduplication keeps one row per ASIN rather than every occurrence of a product across queries, so the export is not a full placement-measurement log.
• Research selected products in more detail. Supply known ASINs or product URLs when you need available brand, seller, variant or shipping fields. Check the detail source and fetched time before treating reused detail fields as a fresh observation.
• Compare consistent observations downstream. Keep marketplace, source query and collection time with each export, then join by ASIN in your own spreadsheet or database. Inspect the actual currency symbol and enrichment freshness before comparing prices or placement estimates.

Input settings

{
  "queries": ["wireless headphones"],
  "marketplace": "US",
  "sort": "relevance",
  "maxItems": 20,
  "enrichDetails": false,
  "detailCacheMaxAgeMinutes": 60,
  "proxyMode": "auto"
}

More input settings

Field	Type	Description
queries	string[]	Product names, brands, models, or keywords to search.
startUrls	request[]	HTTPS search/product URLs on the selected marketplace's exact www.amazon domain.
asins	string[]	Direct ten-character product ASINs.
marketplace	string	One of US, CA, UK, DE, FR, IT, ES, AU, IN, or JP.
sort	string	relevance, price-asc, price-desc, reviews, or newest. Generated queries only.
maxItems	integer	Global maximum unique products, from 1 to 1,000.
enrichDetails	boolean	Add optional details to search rows. ASINs and product URLs always request details.
detailCacheMaxAgeMinutes	integer	Reuse public product-detail fields from the previous 0–1,440 minutes. The default is 60. Set 0 for a fresh detail request.
proxyMode	string	Keep auto (default), or choose datacenter or residential. See field help for behavior and limitations.

Input recipes

US product research

{ "queries": ["standing desk"], "marketplace": "US", "maxItems": 20 }

UK brand monitoring

{ "queries": ["Sony headphones"], "marketplace": "UK", "maxItems": 10, "enrichDetails": true }

Output data

Illustrative shape only, not a captured product. Fields vary by listing and enrichment availability.

{
  "rank": 1,
  "sponsored": true,
  "asin": "B012345678",
  "productTitle": "Wireless noise-cancelling headphones",
  "brand": null,
  "price": 79.99,
  "priceDisplay": "$79.99",
  "currency": "$",
  "prime": true,
  "rating": 4.5,
  "reviewCount": 1234,
  "imageUrls": ["https://m.media-amazon.com/images/I/example.jpg"],
  "sourceType": "search",
  "sourceQuery": "wireless headphones",
  "marketplace": "US",
  "url": "https://www.amazon.com/dp/B012345678",
  "scrapedAt": "2026-07-10T12:00:00.000Z",
  "diagnostics": { "detailEnriched": false, "pageNumber": 1 }
}

Download your results

Open your run's dataset, choose Export and select JSON, CSV or Excel. JSON keeps nested fields together. CSV and Excel are useful when you want to review the records in a spreadsheet.

See Apify's download and export guide for the available formats and field options.

Pricing

The Actor uses pay-per-event pricing: start is charged once per started run, item for each product row saved, and detail for successful search-detail enrichment or a saved direct product lookup. Reused details can also receive a detail event.

A failed optional enrichment still leaves an item event when the search row is saved, but no detail event. Failed products without saved rows do not receive an item event. No paid status/error rows are emitted.

Input is validated before start. A started run can still incur start if extraction fails. Keep maxItems small and enable enrichDetails only when product-page fields are needed.

See the live Pricing tab for current rates and applicable platform usage.

Tips for best results

• Begin with 10 products. Inspect the available fields before enabling a larger export or optional detail enrichment.
• Use a specific brand or model. Keep the selected marketplace and query consistent when comparing repeated search observations.
• Check detail freshness before comparing fields. Use diagnostics.detailSource and diagnostics.detailFetchedAt alongside the row's collection time.
• Use a fresh detail request when needed. Setting detailCacheMaxAgeMinutes to 0 requests fresh details, but does not guarantee every optional field exists.
• Keep the default connection setting unless a supported alternative is needed. Consult the input help before choosing a proxy-only option.
• Choose the right export for the next step. JSON keeps nested data together, while CSV or Excel suits a review sheet.

Limits and caveats

Amazon can vary products, prices, delivery promises, and placements by time and location. Results are deduplicated by ASIN, so a repeated product is not a separate row for every query. Live detail enrichment can replace search prices. Cached detail enrichment retains available search prices and fills missing values. Optional details may be reused within detailCacheMaxAgeMinutes. diagnostics.detailSource and diagnostics.detailFetchedAt identify detail freshness, while scrapedAt identifies the row's collection time.

The Actor does not require an Amazon account and is not an official Amazon API. Some requests can be blocked or unavailable. A later source failure can preserve already saved products. Check RUN_SUMMARY for partial completion. A run with no saved products currently fails, including a completed search with no matches. A product cap is an upper bound, not a guarantee that Amazon supplies that many products.

Automation and integrations

Save your settings for next time

Once you have an input that works for you, save it as an Apify task. This keeps your settings together so you can use them again without filling in the form from scratch.

Run on a schedule

Need fresh results regularly? You can schedule the Actor or a saved task to run at a time that suits you.

Each scheduled run collects the data again. If you want to compare results or highlight changes, add that step in your own workflow.

Send results to your other tools

Use n8n, Make or Zapier to connect this scraper to the rest of your workflow. For example, you could pass its results to an AI assistant or add records to a spreadsheet. Follow the Apify integration guides for your chosen tool.

For a custom connection, an Apify webhook can notify your app when a run finishes or fails. Your app can then fetch the results or handle the failure.

Slack + n8n research workflow

Use Amazon Products & Search Scraper as a research input when a teammate asks a bounded question in Slack. Connect an MCP-compatible assistant through the hosted Apify MCP server, using the same documented queries, marketplace, maxItems, and enrichment inputs. Keep maxItems small for an interactive brief. The batch run writes structured results to its Apify dataset. Use n8n or an Apify webhook to send a comparison with source URLs to Slack, Sheets, Notion, or your CRM.

Research prompt: “Search Amazon US for standing desk. Return 20 results with sponsored status, price, rating, and review count.”

This Actor returns data and does not install or operate a Slack bot. Review the dataset and source URLs before acting on an AI-generated summary. See the shared Slack research brief recipes with Apify MCP + n8n.

API usage

Want to collect this data from your own app or automation? The examples below send input to the scraper and show how to collect its results.

The Node.js and Python examples wait for the run to finish before reading its results. The cURL example starts the run and returns its details. Wait for that run to finish, then use its defaultDatasetId to fetch the results.

For setup instructions, see Apify's JavaScript client guide, Python client guide and Actor runs API reference.

cURL

curl -X POST 'https://api.apify.com/v2/acts/fetch_cat~amazon-products-search-scraper/runs' \
  -H "Authorization: Bearer $APIFY_TOKEN" \
  -H 'Content-Type: application/json' \
  --data @- <<'JSON'
{
  "queries": [
    "wireless headphones"
  ],
  "marketplace": "US",
  "sort": "relevance",
  "maxItems": 20,
  "enrichDetails": false,
  "detailCacheMaxAgeMinutes": 60,
  "proxyMode": "auto"
}
JSON

Node.js

import { ApifyClient } from 'apify-client';

const client = new ApifyClient({ token: process.env.APIFY_TOKEN });
const run = await client.actor('fetch_cat/amazon-products-search-scraper').call({
  "queries": [
    "wireless headphones"
  ],
  "marketplace": "US",
  "sort": "relevance",
  "maxItems": 20,
  "enrichDetails": false,
  "detailCacheMaxAgeMinutes": 60,
  "proxyMode": "auto"
});
const { items } = await client.dataset(run.defaultDatasetId).listItems();
console.log(items);

Python

import os
from apify_client import ApifyClient

client = ApifyClient(os.environ['APIFY_TOKEN'])
run = client.actor('fetch_cat/amazon-products-search-scraper').call(run_input={'queries': ['wireless headphones'], 'marketplace': 'US', 'sort': 'relevance', 'maxItems': 20, 'enrichDetails': False, 'detailCacheMaxAgeMinutes': 60, 'proxyMode': 'auto'})
print(client.dataset(run['defaultDatasetId']).list_items().items)

MCP and agents notes

Use the hosted server's configurator and the official Apify MCP setup guide for your client. Authenticate privately. Never paste tokens into prompts. Bound maxItems, specify a supported marketplace, and retrieve the completed run's dataset. MCP discovery does not guarantee that Amazon will return usable results.

MCP and AI agents

You can ask your AI assistant to collect data with Amazon Products & Search Scraper and help you work with the results. The scraper returns the data, and your assistant can then summarize it, compare records or prepare notes.

Connect your assistant through the Apify MCP server. MCP gives your assistant a way to find this scraper, run it and read the results. Follow the official setup and sign-in guide for your app.

Easier setup with an Apify plugin

If you use a supported coding assistant, the official Apify plugin can set up the connection for you. It connects your assistant to Apify and includes instructions for common tasks. Follow the guide for your particular app.

Use Apify AI in Console

Prefer to keep everything in Apify? Open Apify AI in Console and ask it to find Fetch Cat's Amazon Products & Search Scraper. You can describe the data you want and ask questions about the results.

Apify AI is currently in beta. It asks for confirmation before starting an Actor, and normal run charges apply.

Choose your assistant

• Claude and Claude Code (Anthropic): Apify setup guide.
• ChatGPT and Codex (OpenAI): Apify setup guides.
• Grok Bot (xAI): Apify plugin guide.
• Gemini CLI (Google): MCP server setup guide. Use the server URL below with the HTTP configuration supported by Gemini CLI.

Connect just this scraper

To keep your setup focused on this scraper, add this server configuration to a compatible MCP client:

{
  "mcpServers": {
    "apify": {
      "url": "https://mcp.apify.com?tools=fetch_cat/amazon-products-search-scraper"
    }
  }
}

Sign in to Apify when your client asks. If your client uses a Bearer token instead, follow its setup guide and keep the token in its secure configuration. Configuration formats vary by app, so use the linked guide if your client needs a different format.

Use Apify's general server

Already connected to the general Apify MCP server at https://mcp.apify.com? You can use it to find this scraper without adding another server. Ask your assistant to use Amazon Products & Search Scraper by Fetch Cat, or give it the identifier fetch_cat/amazon-products-search-scraper.

Your assistant can check the available settings and retrieve the results from the returned run. If the run is still working, it should follow that run rather than start it again. Both connection options use Apify's hosted service.

Example requests

• “Use Fetch Cat’s Amazon Products & Search Scraper to collect up to 5 wireless-headphone products on the US marketplace, without optional detail enrichment. Make a table of ASINs, titles, displayed prices, currency symbols and product links.”
• “Collect up to 5 Sony-headphone products on the UK marketplace with available product details. Keep observed search positions and sponsored flags, and show the detail source and fetched time where provided.”
• “Retrieve product details for the three Amazon ASINs I provide on the US marketplace. Show available brand, seller and shipping information, marking missing fields and keeping the original product links.”

Normal Apify charges apply. Check the live Pricing tab before asking your assistant to run a larger batch.

Pay with x402

If your AI agent has a funded wallet, it can pay for Apify usage through x402. This experimental option lets an agent use Apify without a conventional account.

Apify AGI provides a prepaid API token with a spending cap after payment. Your agent can use that token to run this scraper through the Apify API or an authenticated MCP connection.

Some MCP setups also support paying for each request directly. That is a different payment option, so check the official guide for its availability.

Follow the official guide for wallet setup, supported payment options and current terms. Apify handles the payments. Keep wallet keys and payment tokens in your agent's secure configuration.

Other ways for agents to pay

Apify also supports MPP for prepaid access through AGI and Skyfire for eligible Actors. If your agent already uses one of these, see the agentic payment guide to choose the right setup.

FAQ

Does it require an Amazon login?

No. It collects publicly visible search listings.

Why can results change between runs?

Amazon rankings and sponsored placements are dynamic and may vary by marketplace, time, inventory, and delivery location.

What happens when Amazon returns a challenge page?

The run fails with a clear error instead of reporting a misleading successful zero-item dataset.

Can I export Amazon products without an Amazon API account?

Yes. Run this Actor with public search inputs or product identifiers, then export its dataset as JSON, CSV, or Excel. This is not Amazon's Product Advertising API and does not provide private account data.

Does the rating include customer review text?

No. rating and reviewCount describe visible aggregate signals, not individual reviews.

Related Actors

• Amazon Bestsellers Scraper for category bestseller discovery.
• Amazon Seller Profiles Scraper for seller research.
• Google Shopping Results Scraper for cross-channel product discovery.
• eBay Marketplace Scraper for marketplace comparisons.
• AliExpress Reviews Scraper for product-review analysis on another marketplace.

Support and feedback

For custom additions or integrations, email hello@fetchcat.dev.

Found an error or have a feature request? Open an issue with the run URL, a non-sensitive input example and what you expected.

Need help sharing it? See Apify’s guide to sharing a run when reporting an issue. Sharing a run can give the developer access to its input, logs and results, so use a run that contains no sensitive data. Please leave out API tokens, passwords, cookies, private documents and personal data. Use a public sample URL or a redacted example instead.

Tried this scraper? We'd love to hear how it worked for you. Leave a review to help others choose the right tool and help us improve it. Your feedback means a lot to us.

Made with care for curious people, AI agents and the possibilities in data. ♥