Shopify Product Scraper
Pricing
from $4.57 / 1,000 products
Shopify Product Scraper
Compare Shopify products, offers, and identifiers. Start with Shopify product URLs; each returned product keeps titles, prices, ratings, review volume, and identifiers.
Pricing
from $4.57 / 1,000 products
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ReapX
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Compare Shopify products, offers, and identifiers. Start with Shopify product URLs; each returned product keeps titles, prices, ratings, review volume, and identifiers.

What it returns
Each row keeps the Shopify source record beside the fields needed to use it. The opening set is id, title, url, description, vendor, currency, image, sourceUrl, route, scrapedAt, price, and rating. The complete schema is declared before the run, and dataset views keep related fields together without changing the underlying row.
Captured row
{"id": "8245345714265","price": 109.99,"currency": "USD"}
Input


Shopify Product Scraper accepts source URLs. Run controls stay in the same form.
| Field | What it controls | Starting value |
|---|---|---|
startUrls | Paste exact Shopify URLs, one per line. | ["https://www.keychron.com/products/keychron-k1-ultra-8k-wireless-custom-mechanical-keyboard","https://shop.tesla.com/product/mens-cyberhat"] |
maxItems | Stop after this many dataset rows. | 20 |
maxSeconds | Stop after this many seconds and keep completed rows. | 180 |
Example input
{"startUrls": ["https://www.keychron.com/products/keychron-k1-ultra-8k-wireless-custom-mechanical-keyboard","https://shop.tesla.com/product/mens-cyberhat"],"maxItems": 3,"maxSeconds": 180}
No field is required. Start with the filled example, then replace only the target values needed for the job. Run controls can stay at their starting values for the first collection.
Dataset fields

| Field | Type |
|---|---|
id | string |
title | string |
url | string |
description | string |
vendor | string |
currency | string |
image | string |
sourceUrl | string |
route | string |
scrapedAt | string |
price | number |
rating | number |
reviewCount | integer |
available | boolean |
tags | array:string |
variants | array:object |
Dataset views
Views are working surfaces for review and export. They select and order fields while leaving the stored row unchanged.
| View | Opening fields |
|---|---|
overview | currency, price, variants, id, title, image, rating, and reviewCount |
commerce | id, title, url, currency, price, and variants |
identity | id and title |
media | id, title, url, and image |
engagement | id, title, url, rating, and reviewCount |
timing | id, title, url, and scrapedAt |
Output and exports
| Output | Type | Destination |
|---|---|---|
results | string | {{links.apiDefaultDatasetUrl}}/items |
json | string | {{links.apiDefaultDatasetUrl}}/items?clean=true&format=json |
csv | string | {{links.apiDefaultDatasetUrl}}/items?clean=true&format=csv |
excel | string | {{links.apiDefaultDatasetUrl}}/items?clean=true&format=xlsx |
jsonl | string | {{links.apiDefaultDatasetUrl}}/items?clean=true&format=jsonl |
Completed rows are available in the Apify dataset as JSON, CSV, Excel, and JSONL exports. The run output also carries the declared links above for API clients and automations.
Pricing
$8 per 1,000 dataset items on the Free plan. Other Apify plans use the rates shown in the Pricing tab.
Console, API, schedules, and MCP

Runs can begin in Apify Console, from a saved task, or through the Actor API. A schedule can reuse the same input, and a run-finished webhook can pass the dataset or run ID to the next system.
POST https://api.apify.com/v2/acts/ge2zya53sFqhvV5yZ/runsGET https://api.apify.com/v2/datasets/{datasetId}/items
For MCP selection, use Shopify Product Scraper. Its machine entry carries the same description, input field names, no-required-field contract, output types, dataset fields, views, and pricing facts as this document.
Saved tasks
Twenty saved-task products cover distinct lookup, comparison, research, operations, automation, and export jobs:
- Shopify Product variants images core: buyer-job; opens
overview. - Shopify Product price and currency match: buyer-job; opens
commerce. - Shopify Product ID titles identity: buyer-job; opens
identity. - Shopify Product images and ID gallery view: buyer-job; opens
media. - Shopify Product ratings and review volume audience sizing: buyer-job; opens
engagement. - Shopify Product timing collection times recency view: buyer-job; opens
timing. - Shopify Product variants full record: buyer-job; opens
overview. - Shopify Product prices assortment map: buyer-job; opens
commerce. - Shopify Product ID handoff: buyer-job; opens
identity. - Shopify Product media images creative set: buyer-job; opens
media. - Shopify Product response review volume rating view: buyer-job; opens
engagement. - Shopify Product collection times timing publishing file: buyer-job; opens
timing. - Shopify Product variants and collection times detail handoff: buyer-job; opens
overview. - Shopify Product currencies and prices quote sheet: buyer-job; opens
commerce. - Shopify Product ID and titles index: buyer-job; opens
identity. - Shopify Product images media asset list: buyer-job; opens
media. - Shopify Product ratings response volume check: buyer-job; opens
engagement. - Shopify Product collection times links timing: buyer-job; opens
timing. - Shopify Product core variants detail file: buyer-job; opens
overview. - Shopify Product offer prices price match: buyer-job; opens
commerce.
Integrations
Use the dataset API from any HTTP client, export rows to a spreadsheet, or send the run ID through an Apify webhook. Saved tasks give schedules and automation tools a stable input without changing the Actor contract.
Related products
- Shopify Data Scraper
- Shopify Rating Scraper
- Shopify Lead Scraper
- Google Search Price Scraper
- eBay Price Data Scraper
When a run needs attention
- No rows: Open the target in a browser, check spelling and source visibility, then retry the saved example before widening the input.
- A field is empty: Check the field beside its source URL. A missing source value stays empty instead of being replaced with a guess.
- A target fails: Keep successful targets in the dataset, then retry only the affected input.
- An automation cannot find results: Read the dataset ID from the run and request its items endpoint directly.
FAQ
What do I get back from one run?
One row per product with 16 declared fields, opening on id, title, url and description. The schema is published before the run, so you know the shape before you spend anything.
Do I need a shopify account or login?
No. The run works from the shopify sources you supply in the input. Nothing is posted, changed or accessed on your behalf.
What does a run cost?
The current rate is shown on the Pricing tab and is charged per row you receive, so a run that finds nothing costs close to nothing. Cap the run with the item limit when you want a predictable ceiling.
Can I try it before committing budget?
Yes. Cap the run with the item limit in the input and inspect the first rows. The cap is enforced before charging, so a trial run stays a trial.
What do I put in the input?
The staged input is already usable: startUrls, maxItems and maxSeconds. Replace the staged target with your own list when you are ready to run for real.
Are any fields required?
No field is required. Every input carries a working default, so the Actor can be started as-is and refined afterwards.
Do I need to configure proxies?
No. Network access is handled inside the Actor and needs no proxy configuration from you.
How fresh is the data?
Every row is collected during the run you start, not served from a cache. Re-run the same input whenever you need the current state of a shopify product.
Can I use the results commercially?
The Actor collects publicly accessible shopify information. You remain responsible for how you use it, including any privacy or contractual obligations that apply to your business.
How do I compare two runs?
Keep id and title as your join key and diff the exports. The identity fields stay stable across runs, which is what makes a comparison meaningful.
What happens if a source fails mid-run?
The run continues through the remaining sources and finishes with what it collected. Partial results are still written to the dataset rather than discarded.
Can I limit how long a run takes?
Yes. The maxItems input caps the run. Use it when you need a predictable cost and a predictable finish time.
How do I report a problem?
Open an issue on the Actor with the run ID, the input you used and the field or row that needs attention. The run ID lets the exact execution be inspected.
How is this different from Shopify Data Scraper?
Shopify Product Scraper answers one job: Compare Shopify products, offers, and identifiers.. Shopify Data Scraper covers a different question on the same platform. Run both when you need both sides.
How do I read the output without scrolling through JSON?
Open the overview view on the Output tab. 6 views ship with the Actor (overview, commerce, identity, media, engagement and timing), each grouping the fields that belong to one question.
How do I get the data into my own tools?
Export the dataset as JSON, CSV, Excel or XML, call the dataset API directly, or attach a run-finished webhook and collect the dataset reference as soon as the run ends.
Can an agent or LLM call this?
Yes. Shopify Product Scraper is exposed over MCP with the same description, no-required-field input contract and output types shown here, so an agent can select and call it without a human in the loop.
Why is a value empty on some rows?
shopify does not expose every field on every product. An absent value stays empty rather than being filled with a guess, so a row never invents a fact it did not receive.
A run returned fewer rows than I expected. Why?
The usual causes are a narrow source list, an item cap still set low, or a source that genuinely holds less than expected. Widen the input or raise the cap and run again.
Can I schedule this to run on its own?
Yes. Save the input as an Apify task and attach a schedule. Keep separate tasks when different teams need different targets or delivery paths.
Support
Use the Actor issue form for product questions, broken source routes, schema mismatches, and feedback. Include the smallest input that reproduces the problem. That is enough to locate the run and its dataset without sharing an entire working list.
Use this Actor only for data you are allowed to collect. Follow source terms, privacy law, and your own retention policy.