Collector
Shopify Storefronts scraper
Every product a Shopify store publishes — title, price, compare-at price, stock, SKU, vendor, type, tags and images, a row per product, straight off the storefront’s own catalogue file with no account and no browser.
On this page
What it collects
Every product a Shopify store publishes — title, price, compare-at price, stock, SKU, vendor, type, tags and images, a row per product, straight off the storefront’s own catalogue file with no account and no browser. It is a scraper, which means the whole contract is: fill in the form, and one table comes back. No browser window opens, it costs none of your plan's automation slots, and the requests go out over plain HTTP carrying a real browser's TLS fingerprint.
It runs fine from your own address; a proxy is available on the run and this target does not need one. Whichever way it went, every row records it — see the provenance columns below.
What you give it — 7
The form the app draws, read out of the card itself. Each hint below is the one shown beside that field in the run dialog, so nothing here is a description of the product written separately from it.
The one answer it needs
- startUrls
- Stores · list · required
One store per line — the domain, the homepage, or any product or collection link from it. A 404 means that host does not serve this file: either it is not a Shopify store, or it is one that has switched the catalogue off. The collector is fine either way and the other stores keep going.
Everything else is optional
- maxProductsPerStore
- Products per store · number
- keywords
- Title contains · list
- productTypes
- Product type · list
- vendors
- Vendor · list
- minPrice
- Minimum price · number
- onlyAvailable
- In stock only · boolean
Rounded up to whole pages of 250. There is no early stop — a shop with forty products still costs the page count asked for, so raise this for a big catalogue rather than leaving it high for everything.
Keeps a product only when its title contains one of these. Costs no extra requests — the reply already carried the title.
Matched against the shop’s own type, exactly as it writes it.
Useful on a reseller, where one storefront carries many brands.
In the store’s own currency, which this endpoint does not name. A product with no price fails this rather than counting as zero.
Drops products whose first variant is sold out.
What comes back — 22 columns
One dataset per run — a typed table your workspace owns, which you can then sort, filter, edit in the grid, export whole, or read back over the local API. These are the columns it is created with.
3 columns are marked may be empty. That is a fact about the record rather than about the collector — a post with nowhere tagged, an account with no business category — and it is said out loud so a blank cell does not read as a broken scraper. A column the reply never carries at all is deleted upstream rather than shipped empty, so nothing here is decoration.
18 from Shopify Storefronts
| Key | Column | Type |
|---|---|---|
| title | Product | text |
| productUrl | Product page | url |
| vendor | Brand | text |
| productType | Typemay be empty | text |
| price | Price | number |
| compareAtPrice | Compare-at pricemay be empty | number |
| available | In stock | select |
| sku | SKU | text |
| variantCount | Variants | number |
| tags | Tagsmay be empty | text |
| imageUrl | Image | url |
| imageCount | Images | number |
| handle | Handle | text |
| publishedAt | Published | datetime |
| createdAt | Created | datetime |
| updatedAt | Updated | datetime |
| productId | Product ID | text |
| searchTerm | Store | text |
4 that every scraper writes
The same four on every card, so a table can still answer months later how its rows got there: which service they came from, when, which profile's identity the requests carried, and whether that identity was signed in.
| Key | Column | Type |
|---|---|---|
| platform | Platform | text |
| collected_at | Collected at | datetime |
| profile | Collected by | profile |
| logged_in | Signed in | select |
Four ways to run it
The Scrapers tab. Pick the card, fill in the form, press Start. Every run started here makes a new table, named after what you searched for and when. Check first if you like — it collects one page, writes nothing, and reports which columns came back filled.
Ask the assistant. It has the whole catalogue, so this card is a sentence rather than a form. It fills in the parameters above from what you said and shows you them before it starts.
Over MCP or the local API. The same card, from a coding agent — argus_run_scraper over the MCP server, or POST http://127.0.0.1:39219/v1/scrapers/run on the local API. There is a sample call beside it that writes nothing.
{
"kind": "shopify_products",
"inputs": {
"startUrls": [
"…"
]
}
}As a step inside a workflow. The Run scraper step puts this collector in the middle of an automation — collect, then filter, then mail — and the tree still opens no window doing it. It is also the one caller that can overrule the table-per-run rule: pointed at a table you name, it creates that table with the columns above if it is missing and files every run into it after, appending or updating the row in place on a column you match on. The step hands the next one the table's name, its id and the row count.
Where it stops
It will not drive a page. Anything that needs a real browser — a site with no list endpoint behind it, or anything operating an account of your own — is an automation instead, and that is a different tool rather than a worse version of this one.
It signs in to nothing. Reading a public page signed out is the settled position — Bright Data scraped Meta signed out and won; hiQ scraped LinkedIn signed in and lost — so this card asks for no account and holds none.