Shopify Products Scraper for Catalogs & Variants

Export public Shopify product catalogs with Shopify Products Scraper. Collect product titles, URLs, vendors, tags, prices, availability, variants and image details from one or more storefronts for catalog research, merchandising audits and your own comparison workflows.

No Shopify API key is needed. Stores must expose a readable public catalog. Currency is always null, and inaccessible stores produce error rows rather than product records.

Quick start

1. Open the Actor and enter a public Shopify storefront homepage.
2. Start with a small product limit and run the Actor.
3. Open the dataset to review product rows and any store-level errors.

{
  "storeUrls": [{ "url": "https://www.deathwishcoffee.com" }],
  "maxProductsPerStore": 20,
  "includeVariants": true,
  "includeImages": true,
  "includeRawProduct": false
}

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.

Ready-to-run examples

Choose an example to start with a preconfigured input.

• Export Products from a Shopify Coffee Store — Collect up to 50 products with variants and images from a coffee storefront.
• Compare Product Catalogs Across Shopify Stores — Collect up to 25 products per store from two storefronts for your own comparison.
• Build a Shopify Product Image Dataset — Collect up to 50 products with image URLs and dimensions, without detailed variants.

What you get

• Product records: Titles, handles, product URLs, vendors, product types and normalized tags.
• Prices and availability: Variant price ranges, compare-at prices and whether any variant is marked available.
• Optional detail: Variant SKUs and options, image URLs and dimensions, or the original product object.
• Multi-store results: Successful products stay in the dataset alongside any store-level error rows. Run records help you inspect partial work and resume unfinished stores.

Who is it for?

Team	Useful workflow
Ecommerce analysts	Compare product assortments across brands.
Merchandising teams	Audit variant prices, tags, images and availability.
Agencies and researchers	Prepare structured catalog exports.
Automation teams	Feed product records into spreadsheets or databases.

Input settings

Use storefront homepages or domains. A product or collection path is normalized to the storefront origin, not used as a filter.

Setting	JSON key	Purpose
Store URLs	storeUrls	Storefronts to read, as URL objects or strings.
Maximum products per store	maxProductsPerStore	Cap each store at 1–10,000 products. Form default: 20. Omitted API input: 100.
Include variants	includeVariants	Include variant detail, enabled by default.
Include images	includeImages	Include image detail, enabled by default.
Include raw product JSON	includeRawProduct	Include the original object, disabled by default.
Maximum run time	maxRunSeconds	Work budget up to 270 seconds.
Resume store URLs	resumeStoreUrls	Add unfinished stores from an earlier run.
Proxy configuration	proxyConfiguration	Keep the existing proxy settings or configure supported direct/custom access. See field help for defaults and costs.

To resume without adding stores, supply storeUrls: [] and the saved list as resumeStoreUrls. A resumed store starts from its first page, so reconcile duplicate products in your own workflow.

Output data

The dataset contains one row per saved product, plus an error row when a store cannot be read. This illustrative shape is not a fresh extraction result:

{
  "status": "success",
  "storeUrl": "https://example.com",
  "storeDomain": "example.com",
  "productId": 123,
  "title": "Example product",
  "handle": "example-product",
  "url": "https://example.com/products/example-product",
  "vendor": "Example vendor",
  "priceMin": 19.99,
  "priceMax": 24.99,
  "currency": null,
  "available": true,
  "variantCount": 2,
  "imageCount": 1
}

Fields	Meaning
status, errorMessage	Product success or store-level error and its reason.
storeUrl, storeDomain, sourceUrl, scrapedAt	Store identity, source page and extraction time.
productId, title, handle, url	Product identity and storefront link.
vendor, productType, tags	Catalog labels when present.
publishedAt, createdAt, updatedAt	Source timestamps when available.
priceMin, priceMax, compareAtPriceMin, compareAtPriceMax	Numeric variant price ranges, or null.
currency	Always null. No currency is inferred.
available, variantCount, imageCount	Availability summary and detail counts.
variants	Optional ID, title, SKU, price, compare-at price, availability and selected options.
images	Optional image ID, URL, alt text, dimensions and position.
rawProduct	Optional original product object.

RUN_SUMMARY in the run's key-value store records saved products, errors, failed stores, empty catalogs and unfinished stores. PENDING_STORE_URLS is saved when work remains. Blocked requests, invalid catalog responses and incomplete exports fail the run while preserving useful products and store-level errors. Customer spending or short time limits stop successfully with LIMIT_STOP and an explanation in the summary; raise the limit to collect more products.

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

This Actor uses pay-per-event pricing. The start event is charged once when processing begins.

A result event is charged for each successfully saved product. Store-level error rows do not incur a result event. A run without products can still incur the start charge. Input limits help bound the amount of work, and configured proxy traffic can have separate charges.

See the live Pricing tab for current rates and discounts.

Tips for best results

• Start with one store. Use a small product limit to check its public catalog.
• Use the storefront domain. Product and collection paths do not restrict the catalog.
• Keep exports small. Disable detailed variants, images or raw product objects when you do not need them. Price ranges and counts are still returned.
• Inspect partial results. Review error rows and RUN_SUMMARY before treating an export as complete.
• Compare your saved datasets. Recurring runs collect new snapshots, not built-in change alerts.

Limits and caveats

Only publicly readable Shopify storefront catalogs are supported. The Actor does not log in, access private inventory or guarantee access to every store.

There are no collection, search, bestseller or sorting filters. Capped exports retain the public catalog's returned selection. With the 10,000-product cap, images disabled and raw JSON disabled, an ID-only discovery can select a lower-bandwidth public Storefront export when the complete catalog fits. Complete Storefront exports use product-ID order; discovery overflow retains the original capped catalog route. Explicit proxy choices apply to both routes. Storefront rejection before any output can fall back to the original catalog route; errors after output fail rather than restart or silently mix selections.

sourceUrl identifies the actual public endpoint. updatedAt is that endpoint's timestamp and may differ between the Storefront and catalog JSON surfaces; it is not a cross-source change-tracking guarantee. Counts include all fetched image and variant pages even when their details are omitted. Raw JSON and image-detail exports retain the original complete catalog route. Prices have no verified currency code, and availability is a summary of the source variants, not an inventory quantity.

Empty public catalogs return no product rows. Unreadable stores produce error rows. A blocked response alone does not establish that a store is private or deleted. Large or slow catalogs can finish partially, and resuming repeats the unfinished store from its beginning.

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.

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 --request POST \
  --header "Authorization: Bearer $APIFY_TOKEN" \
  --header "Content-Type: application/json" \
  --data '{"storeUrls":[{"url":"https://www.deathwishcoffee.com"}],"maxProductsPerStore":20}' \
  'https://api.apify.com/v2/acts/fetch_cat~shopify-products-scraper/runs'

After the returned run completes, fetch https://api.apify.com/v2/datasets/DATASET_ID/items with the same authentication, replacing DATASET_ID with its defaultDatasetId.

Node.js

import { ApifyClient } from 'apify-client';

const client = new ApifyClient({ token: process.env.APIFY_TOKEN });
const run = await client.actor('fetch_cat/shopify-products-scraper').call({
  storeUrls: [{ url: 'https://www.deathwishcoffee.com' }],
  maxProductsPerStore: 20
});
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/shopify-products-scraper').call(run_input={
    'storeUrls': [{'url': 'https://www.deathwishcoffee.com'}],
    'maxProductsPerStore': 20,
})
items = client.dataset(run['defaultDatasetId']).list_items().items
print(items)

MCP and AI agents

You can ask your AI assistant to collect data with Shopify Products 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 Shopify Products 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/shopify-products-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 Shopify Products Scraper by Fetch Cat, or give it the identifier fetch_cat/shopify-products-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

• “Get 20 products from deathwishcoffee.com and summarize their price ranges.”
• “Collect up to 25 products each from deathwishcoffee.com and brooklinen.com, then compare their vendors and product types.”
• “Get 30 products with images from brooklinen.com and prepare a spreadsheet of product names and image URLs.”

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

Do I need a Shopify API key?

No. This scraper reads public storefront catalogs without Shopify login credentials. It is not a replacement for authenticated Shopify Admin API access.

Can I export variants and images?

Yes. Enable the corresponding settings to include the detail arrays. Each dataset row remains a product, not an individual variant.

Why is currency empty?

currency is always null in this Actor. Check the storefront separately before comparing prices across currencies.

Why did I get fewer products or error rows?

The store may expose fewer public products, block access or fail during processing. Inspect the error rows and run summary. No response alone proves that a store is private or deleted.

Can I monitor catalogs over time?

You can save settings and arrange recurring runs through Apify. Store snapshots and compare them in your own workflow. The scraper itself does not detect changes or send alerts.

Related Actors

• Google Shopping Results Scraper — Research shopping listings across stores.
• AliExpress Products Scraper — Collect marketplace product records.
• Walmart Products Scraper — Export Walmart product data.
• Shopify App Reviews Scraper — Research Shopify apps rather than storefront products.
• Website Contact Finder — Find publicly listed website contact information.

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. If the review page is unavailable, open the Actor page and use its available review option. Your feedback means a lot to us.

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