Shopify Products Scraper for Catalogs & Variants

Extract public product catalogs from Shopify storefronts.

Use this actor to collect product titles, handles, prices, compare-at prices, variants, images, vendors, product types, tags, availability, and source URLs from one or more Shopify stores.

At a glance

• Input: Shopify storefront URLs, per-store product cap, variant mode, image mode, raw product mode, and optional proxy settings.
• Output: One dataset row per public product with title, handle, URL, vendor, product type, tags, price range, availability, variants, images, and status fields.
• Best for: Product catalog exports, price monitoring, assortment research, merchandising audits, and ecommerce data pipelines.
• Pricing unit: A start event per run plus one result event for each successful saved product row.
• Login required: No. The Actor reads public Shopify storefront catalog data only.

What can it do?

Shopify Products Scraper turns public Shopify storefront catalogs into clean product datasets for price monitoring, catalog QA, and product intelligence.

Who is it for?

Why use this actor?

• Simple input: enter storefront domains and get product rows.
• Multi-store runs for comparing brands, categories, or markets.
• Variant-level prices and availability when includeVariants is enabled.
• Image URLs and dimensions when includeImages is enabled.
• Clear error rows for stores that do not expose a public catalog.
• Scheduling, API, and integration support for recurring workflows.

Common workflows

• Price monitoring across competing Shopify stores.
• Assortment tracking for categories, tags, product types, or vendors.
• Variant and SKU exports for catalog review.
• Image URL extraction for merchandising audits.
• Availability checks for products and variants.
• New product discovery from public storefront catalogs.

Example input

{
  "storeUrls": [
    { "url": "https://www.deathwishcoffee.com" },
    { "url": "https://www.brooklinen.com" }
  ],
  "maxProductsPerStore": 25,
  "includeVariants": true,
  "includeImages": true,
  "includeRawProduct": false
}

Output overview

The default dataset contains one row per product.

If a store cannot be read, the dataset includes an error row for that store.

Successful product rows have status set to success.

Store failure rows have status set to error and include errorMessage.

Variant fields

Variant objects can include ID, title, SKU, price, compare-at price, availability, and selected options.

This is useful when a product has sizes, colors, bundles, or subscriptions.

Variant fields can be disabled to keep datasets smaller.

Image fields

Image objects can include ID, URL, alt text, width, height, and position.

Image fields can be disabled when you only need pricing and catalog metadata.

How to run in Apify Console

Open the actor page.

Click Try for free or Start.

Paste one or more Shopify store URLs.

Choose the maximum products per store.

Select whether to include variants and images.

Start the run.

Download results from the Dataset tab as JSON, CSV, Excel, XML, or RSS.

Tips for best results

Start with one store and a small product limit.

Increase maxProductsPerStore after confirming the store returns the expected data.

Use full storefront domains instead of product URLs.

Disable raw product output unless you need original source payloads.

Disable images or variants if you want smaller exports.

Check status and errorMessage for stores that do not expose a public catalog.

Handling stores that fail

Some Shopify stores disable public catalog access.

Some stores use security rules that block automated catalog requests.

This actor reports those stores as error rows instead of hiding failures.

For failed stores, try a smaller run first and verify the domain is the storefront homepage.

If a store still fails, it may not support public catalog extraction.

Scheduling workflows

You can schedule the actor daily, weekly, or monthly in Apify.

Scheduled runs are useful for price monitoring.

They are also useful for detecting catalog changes, new products, or availability updates.

Export each run to your warehouse or compare datasets between runs.

Integrations

Send product rows to Google Sheets for category review.

Send price and availability changes to Slack alerts.

Load datasets into BigQuery, Snowflake, or PostgreSQL.

Trigger Make or Zapier workflows after each run.

Use webhooks to notify your own backend when a catalog scrape finishes.

API usage with 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: 25,
  includeVariants: true,
  includeImages: true
});

console.log(run.defaultDatasetId);

API usage with Python

from apify_client import ApifyClient
import os

client = ApifyClient(os.environ['APIFY_TOKEN'])
run = client.actor('fetch_cat/shopify-products-scraper').call(run_input={
    'storeUrls': [{'url': 'https://www.deathwishcoffee.com'}],
    'maxProductsPerStore': 25,
    'includeVariants': True,
    'includeImages': True,
})
print(run['defaultDatasetId'])

API usage with cURL

curl -X POST "https://api.apify.com/v2/acts/fetch_cat~shopify-products-scraper/runs?token=$APIFY_TOKEN" \
  -H "Content-Type: application/json" \
  -d '{"storeUrls":[{"url":"https://www.deathwishcoffee.com"}],"maxProductsPerStore":25}'

MCP and AI agents

Use Apify MCP with Claude Code, Claude Desktop, or compatible tools.

MCP URL format:

https://mcp.apify.com/?tools=fetch_cat/shopify-products-scraper

Add it in Claude Code:

claude mcp add apify-shopify-products "https://mcp.apify.com/?tools=fetch_cat/shopify-products-scraper"

Claude Desktop JSON configuration:

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

Example prompts:

• "Scrape 25 products from deathwishcoffee.com and summarize price ranges."
• "Compare vendors and product types from these three Shopify stores."
• "Find products with compare-at prices and list discount candidates."

Data quality notes

Prices are returned as numbers when present.

Currency is only filled when it can be inferred.

Availability is summarized from variant availability.

Product tags are normalized into an array.

Product URLs are built from the storefront domain and product handle.

Limits

The actor targets public Shopify storefront data.

It does not log in to stores.

It does not bypass hard security walls.

It does not guarantee that every Shopify store exposes a public catalog.

Very large catalogs may require higher maxProductsPerStore values and longer run time.

Legality

Only scrape public storefront data that you are allowed to process.

Respect applicable laws, website terms, and privacy obligations.

Do not use exported data for spam, deceptive practices, or prohibited profiling.

If you are unsure about your use case, consult your legal advisor.

Troubleshooting

Why did a store return an error row?

The store may not expose a public catalog, may block automated requests, or may not be a Shopify storefront.

Verify the domain in a browser and try a small run first.

Why are there fewer products than expected?

The store may have fewer public products than expected, hidden products, regional catalog differences, or storefront rules that limit catalog access.

Increase maxProductsPerStore only after confirming the store has more public products.

Why is currency empty?

Some public catalog responses provide prices without a currency code.

When currency cannot be inferred safely, the actor leaves it empty rather than guessing.

Support

If a public Shopify store fails unexpectedly, include the store URL and run ID when requesting support.

Small reproducible inputs are easiest to investigate.