# ASOS Scraper - Fashion, Prices, Discounts & Stock (`abotapi/asos-com-scraper`) Actor

Scrape ASOS by keyword, category or URL. Every row carries the selling price and the original price, the discount, brand, colour and selling-fast flags. Sizes, per-size stock and reviews are one toggle away. Recurring change tracking is first-class.

- **URL**: https://apify.com/abotapi/asos-com-scraper.md
- **Developed by:** [Abot API](https://apify.com/abotapi) (community)
- **Features:** Limited permissions
- **Stats:** 1 total users, 0 monthly users, 100.0% runs succeeded, 0 bookmarks
- **User rating**: No ratings yet

## Pricing

from $1.70 / 1,000 product records

This Actor is paid per event. You are not charged for the Apify platform usage, but only a fixed price for specific events.
Since this Actor supports Apify Store discounts, the price gets lower the higher subscription plan you have.

Learn more: https://docs.apify.com/actors/running/actors-in-store.md#pay-per-event

## What's an Apify Actor?

An Actor is a serverless cloud program that runs on the Apify platform. It has two run modes.
In Batch mode, an Actor accepts a well-defined JSON input, performs an action which can take anything from a few seconds to a few hours,
and optionally produces a well-defined JSON output, datasets with results, or files in key-value store.
In Standby mode, an Actor provides a web server which can be used as a website, API, or an MCP server.

Apify vocabulary and the platform model are defined once, in the agent quickstart at https://apify.com/agents.md.

## How to integrate an Actor?

If asked about integration, you help developers integrate Actors into their projects.
You adapt to their stack and deliver integrations that are safe, well-documented, and production-ready.

Do not guess an integration path. Every one of them is in the agent quickstart at https://apify.com/agents.md: the Apify MCP server, Agent Skills with the Apify CLI, the JavaScript and Python clients, the REST API, and the account-free path for an agent with no human to sign in. It also carries the rule on stating cost before the first paid run.

For examples already wired to this Actor's own input schema, see the [API](#api) section below.

Each client library has reference documentation the quickstart does not restate: [JavaScript/TypeScript](https://docs.apify.com/api/client/js/docs.md) (`npm install apify-client`) and [Python](https://docs.apify.com/api/client/python/docs.md) (`pip install apify-client`).

# README

## ASOS Scraper: Products, Prices & Stock

ASOS Scraper turns asos.com into a clean product feed. Search by keyword, or paste any ASOS product, search or category link and the actor reads the store's own catalogue directly: current price and original price with the discount computed, brand, colour and the store's own demand flags (new in, selling fast, restocking soon), on every row without a second request. Turn on two toggles for the full size list with per-size stock, and customer reviews. Export to JSON, CSV or Excel, or pull results straight into your app through the API.

### Why This Scraper?

- **Two ways to find products.** Search by keyword, or paste a product, search or category link; a pasted link decides its own scope.
- **The full price story on every row.** Selling price, original price and the discount percentage arrive from the listing itself, with no second request and no toggle required.
- **Store demand signals included.** New in, selling fast and restocking soon flags come straight off the listing card.
- **Size and stock on demand.** Turn on Fetch product details for the complete size list, brand size, SKU, EAN and per-size stock, including low-stock and restocking flags.
- **Customer reviews on demand.** Rating count, average rating, Fit and Quality scores and the reviews themselves, one toggle away.
- **Friendly brand and colour filters.** Type names such as "Bershka" or "Black"; the actor resolves them against the store's own live list and fails loud on a typo instead of silently widening the search.
- **Built for monitoring.** Incremental mode returns only new, changed and reappeared products on recurring runs, and a refused run fails loudly instead of returning an empty dataset.

### Use Cases

- **Pricing and promo tracking:** monitor a search or category for price cuts, new discounts and demand flags over time.
- **Assortment and stock research:** get notified when a product goes selling fast, runs low on a size, or comes back in stock.
- **Trend and competitor research:** track which brands and colours dominate a category or a search term.
- **Review and quality research:** pull rating counts, Fit and Quality scores and the reviews themselves for supplier or QA scoring.

### Data You Get

> Sample shape: values are illustrative placeholders, not from a live record.

| Field | Example |
| --- | --- |
| `recordId` / `productId` | `"10000001"` (the store's own product id, stable across runs) |
| `rowType` | `"product"` |
| `title` / `brand` / `brandId` | `"Sample Name Tiered Midi Dress"` / `"Sample Brand"` / `"15370"` |
| `productCode` | `"2000001"` |
| `price` / `priceText` | `45.0` / `"£45.00"` (the current selling price, as a number and as shown) |
| `originalPrice` | `60.0` (the original, pre-discount price) |
| `onSale` / `discountPercent` | `true` / `25.0` |
| `currency` | `"GBP"` |
| `colour` / `colourWayId` | `"Navy"` / `"10000005"` |
| `isNew` / `isSellingFast` / `isRestockingSoon` / `isPromotion` | `false` / `true` / `false` / `false` (the store's own demand flags) |
| `hasMultipleColours` | `false` |
| `imageUrl` / `url` | product image and product page link |
| `description` / `productType` | with Fetch product details on |
| `sizes` | with Fetch product details on: one row per size, with brand size, SKU, EAN, availability and per-size stock (`inStock`, `isLowInStock`, `isRestockingSoon`) |
| `inStock` / `seller` | with Fetch product details on: overall availability and the seller of record |
| `reviews` | with Fetch reviews on: rating count, average rating, Fit and Quality scores and the reviews themselves |
| `detailCarriedForward` | `true` only when a failed detail or review read was repaired from the previous run's snapshot |
| `scrapedAt` | `"2026-01-01T00:00:00Z"` |
| `changeType` / `changedFields` | incremental mode only: `"UPDATED"` / `["price"]` |
| `firstSeenAt` / `lastSeenAt` | incremental mode only: when a record was first and most recently seen |

### How to Use

1. Pick a **mode**: `search` (by keyword) or `url` (paste a product, search or category link).
2. Fill in the field for that mode, and narrow with the brand, colour, price and sort filters; they apply in both modes, and a pasted product link is the one exception, it returns that single product in full.
3. Turn on **Fetch product details** and/or **Fetch reviews** if you need sizes, stock or reviews.
4. Set **Max items** to control run size and cost, then click **Start**.

**Search by keyword:**

```json
{
  "mode": "search",
  "searchTerms": ["midi dress"],
  "maxItems": 20
}
```

**Search narrowed by brand, colour and sort:**

```json
{
  "mode": "search",
  "searchTerms": ["jeans"],
  "brandIds": ["Bershka"],
  "baseColourIds": ["Black"],
  "sortBy": "priceasc",
  "maxItems": 50
}
```

**Paste a category link, with details on:**

```json
{
  "mode": "url",
  "urls": ["https://www.asos.com/women/dresses/cat/?cid=8799"],
  "fetchDetails": true,
  "maxItems": 100
}
```

**Paste a single product link:**

```json
{
  "mode": "url",
  "urls": ["https://www.asos.com/sample-brand/sample-name/prd/10000001"]
}
```

#### Run it from your code

Python:

```python
from apify_client import ApifyClient

client = ApifyClient("<YOUR_APIFY_TOKEN>")
run = client.actor("abotapi/asos-com-scraper").call(run_input={"mode": "search", "searchTerms": ["midi dress"], "maxItems": 20})
for product in client.dataset(run["defaultDatasetId"]).iterate_items():
    print(product["title"], product["price"], product["originalPrice"])
```

JavaScript:

```javascript
import { ApifyClient } from 'apify-client';

const client = new ApifyClient({ token: '<YOUR_APIFY_TOKEN>' });
const run = await client.actor('abotapi/asos-com-scraper').call({ mode: 'search', searchTerms: ['midi dress'], maxItems: 20 });
const { items } = await client.dataset(run.defaultDatasetId).listItems();
```

Or connect it to Make, Zapier, n8n, Google Sheets or webhooks from the **Integrations** tab.

#### How Max items and Max pages shape a run

**Max items** is the single cap on a run, across every search term and URL; set it to `0` for unlimited. With more than one search term or URL, the cap is shared out evenly up front: each source gets at most its equal share (for example 20 each for two sources and Max items 40), and a share one source does not use is not handed to the others. **Max pages** is an optional safety bound per source, on top of that cap. The store serves 48 products per page: when a page holds more fresh candidates than the budget left for that source, only the first candidates on that page, in the store's own order, are read this run, and the run's log names how many of that page were kept. The rest of that page is not read this run, and a product cut off this way is also skipped if a later search term or URL in the same run lists it, so overlapping search terms can return fewer rows than Max items allows.

This matters most with **Incremental mode** on a small, recurring **Max items**. The budget counts returned rows across pages (an unchanged row that is suppressed does not use it up, so the walk moves on to the next page), but within one page it is a cut by position: the candidates after the first N on a page are never classified at all this run, even when the first N all turn out unchanged and nothing is returned. A genuine price or stock change on one of them is missed, and the run's summary message does not say it was capped (a run where every candidate it did classify was unchanged reports "N product(s) scanned, nothing changed", the same message a fully complete, unchanged scan produces). Because every run starts from the top of the results again, a later run with the same Max items cuts the page at the same place, so while the products ranked ahead of it stay unchanged, that change can stay unreported run after run. For a recurring, monitored search or URL, set **Max items** to `0` or to at least the size of the tracked scope so a page is never sliced mid-way.

#### Resume and recurring updates

- **Resume** (`resumeFromRunId`) continues one interrupted or capped run: paste its run or dataset ID and the actor skips everything already collected there, so you don't pay twice.
- **Incremental mode** (`incrementalMode`) is for running the same search or URL again and again (for example daily) and getting only what changed. Each record classifies `NEW`, `UPDATED` (with `changedFields`; a price move or a stock change on a storefront IS reported as UPDATED, since that is exactly what a monitor watches for), `UNCHANGED` (suppressed and not billed unless `emitUnchanged` is on), `REAPPEARED`, or `EXPIRED` (only after a run that scanned the whole tracked scope: never when Max items or Max pages capped the walk short, never with Resume, and never after a refusal). `stateKey` names or shares the stored state, so two differently configured searches never mix their history.

### Send results into your apps (MCP connectors)

Optionally pipe the scraped results into the apps you already use, via Model Context Protocol (MCP) connectors. This is an extra delivery step **after** the scrape: the Apify dataset is never changed.

**What gets written to the connector:** a condensed, human-readable **summary** of each record, not the full JSON. Each item becomes one entry with a **title** and its key fields flattened to plain text. The **complete record always stays in the Apify dataset**.

1. Authorize a connector once under **Apify → Settings → Integrations** (Notion, Linear, Airtable, or Apify).
2. Select it in the **"Pipe results into your apps"** input field. (If the picker is empty, you haven't authorized a connector yet.)
3. For **Notion**, also set `notionParentPageUrl` to the page where items should be created.

The connection is mediated by Apify's MCP proxy, so this actor never sees your third-party credentials. Leave the field empty to skip.

### Input Parameters

| Parameter | Type | Default | Description |
| --- | --- | --- | --- |
| `mode` | string | `search` | `search` (by keyword) or `url` (paste ASOS links). |
| `searchTerms` | array | `["midi dress"]` | Search mode: one or more terms to search for, each scraped independently. |
| `urls` | array | sample | URL mode: product, search or category links; each pasted URL decides its own scope. |
| `brandIds` | array | (none) | Only these brands. Names (e.g. "Bershka") or numeric store ids. Applies in both modes; a pasted product link is the exception. |
| `baseColourIds` | array | (none) | Only these colours. Names (e.g. "Black") or numeric store ids. Applies in both modes; a pasted product link is the exception. |
| `sortBy` | string | `relevance` | The store's own server-side ordering: `relevance`, `freshness`, `priceasc`, or `pricedesc`. |
| `minPrice` | integer | (none) | Only keep rows whose selling price is at least this many pounds. |
| `maxPrice` | integer | (none) | Only keep rows whose selling price is at most this many pounds. |
| `onSaleOnly` | boolean | `false` | Only keep rows with a discount (selling price below the original price). |
| `fetchDetails` | boolean | `false` | Fetch each item's product page: description, full size list and per-size stock. Charged once per record. |
| `fetchReviews` | boolean | `false` | Fetch each item's customer reviews. Charged once per record, under the same surcharge as Fetch product details. |
| `maxReviewsPerProduct` | integer | `10` | Cap on review rows returned per product when Fetch reviews is on. |
| `maxItems` | integer | `20` | The single cap on this run, across all search terms and URLs. `0` = unlimited. |
| `maxPages` | integer | `0` | Safety bound on result pages walked per search term or URL. `0` = no page limit (Max items still applies). |
| `resumeFromRunId` | string | (none) | Continue one interrupted run without returning or charging for records it already collected. |
| `incrementalMode` | boolean | `false` | Turn on for recurring monitoring of the same search or URL: later runs return only new, changed and reappeared records. |
| `stateKey` | string | (none) | Name or share an incremental-mode monitoring campaign's stored state. |
| `emitUnchanged` | boolean | `false` | Also return (and bill) records that have not changed since the last run. |
| `emitExpired` | boolean | `false` | Also return (and bill) records that were tracked before but are no longer found, once a run fully scans the tracked scope. |
| `mcpConnectors` | array | (none) | Optional: send a summary of each record to apps you authorized under Integrations. |
| `notionParentPageUrl` | string | (none) | Notion connector only: page under which record pages are created. |
| `maxNotifyListings` | integer | `50` | Cap on records written to each connector per run. |
| `proxy` | object | Apify Proxy | Connection settings. |

### Output Example

> Sample shape: values are illustrative placeholders, not from a live record.

```json
{
  "recordId": "10000001",
  "rowType": "product",
  "productId": "10000001",
  "url": "https://www.asos.com/sample-brand/sample-name-tiered-midi-dress/prd/10000001",
  "title": "Sample Name Tiered Midi Dress",
  "brand": "Sample Brand",
  "brandId": "15370",
  "colour": "Navy",
  "colourWayId": "10000005",
  "price": 45.0,
  "priceText": "£45.00",
  "originalPrice": 60.0,
  "onSale": true,
  "discountPercent": 25.0,
  "currency": "GBP",
  "isNew": false,
  "isSellingFast": true,
  "isRestockingSoon": false,
  "isPromotion": false,
  "hasMultipleColours": false,
  "imageUrl": "https://images.example.com/products/sample-dress/10000001-1.jpg",
  "productCode": "2000001",
  "productType": "Dresses",
  "description": "A tiered midi dress in a relaxed fit, with a round neck and long sleeves.",
  "sizes": [
    {
      "size": "UK 8",
      "brandSize": "S",
      "sku": "0000001",
      "ean": "0000000000000",
      "available": true,
      "inStock": true,
      "isLowInStock": false,
      "isRestockingSoon": false,
      "seller": "SAMPLE BRAND LTD"
    }
  ],
  "inStock": true,
  "seller": "SAMPLE BRAND LTD",
  "reviews": {
    "ratingCount": 120,
    "averageRating": 4.3,
    "averageFromPage": true,
    "fitScore": 3.9,
    "qualityScore": 4.1,
    "reviews": [
      {
        "id": "1",
        "rating": 5,
        "title": "Great fit",
        "text": "Fits true to size and the fabric feels good.",
        "submittedAt": "2026-01-01T00:00:00Z",
        "recommended": true,
        "colour": "Navy"
      }
    ]
  },
  "detailCarriedForward": null,
  "scrapedAt": "2026-01-01T00:00:00Z"
}
```

With **Incremental mode** on, a row also carries `changeType`, `changedFields`, `firstSeenAt` and `lastSeenAt`.

### Plan Requirement

The default proxy setting works out of the box: the store serves ordinary shared connections, so no premium proxy tier is required. The actor rotates connections automatically when one is refused; change the Proxy configuration only if a run reports it could not read any results. Fetch product details and Fetch reviews add a paid surcharge, charged once per record at most even with both toggles on; the price pair, brand, colour and demand flags are on every row either way.

### FAQ

#### How much does it cost?

You pay per product record returned, plus an optional once-per-record surcharge when Fetch product details or Fetch reviews is on (never twice, even with both toggles on). The **Pricing** tab shows the current rates. Use **Max items** to cap the cost of any run.

#### Is it legal to scrape ASOS?

This actor collects only publicly available product data. You are responsible for how you use it: follow ASOS's terms and the laws that apply to you, and get legal advice if you plan commercial redistribution. Product names, prices and stock levels are generally facts, but images and descriptions may be subject to third-party rights.

#### Can I get only new or changed products on a schedule?

Yes. Schedule the actor from the **Schedules** tab and turn on **Incremental mode**. Each run then returns only new, updated and reappeared records; unchanged ones are suppressed and not billed unless **Emit unchanged** is on.

#### Why did a run return fewer products than I expected?

**Max items** is the single cap on a run, across every search term and URL, and with several sources it is split evenly between them up front: with two search terms and Max items 40, each term returns at most 20, even if the other term finds nothing. When a page holds more fresh candidates than a source's remaining budget, only the first candidates on that page, in the store's own order, are read, and a product cut off that way is also skipped by any later search term in the same run that lists it. Raise Max items, or set it to `0`, to read further. With **Incremental mode** on for a recurring search, keep Max items at `0` or at least the size of the whole tracked scope: a candidate cut off mid-page is not classified at all that run, so a genuine change on it can be missed without the run looking capped from its own summary message, and later runs with the same Max items cut the page at the same place, so it can stay missed until the products ranked ahead of it change or Max items is raised.

#### Why did my run fail instead of returning an empty dataset?

If the store refuses every request, the run stops with a clear message so "nothing matched" is never confused with "nothing could be read". Run it again in a few minutes, or change the Proxy configuration. If only some search terms or URLs could be read, you still get what was found, and the run's log shows which source could not be read (when nothing at all was found, the status message also gives the count of sources that could not be read).

#### What's the difference between Resume and Incremental mode?

**Resume** (`resumeFromRunId`) continues ONE specific interrupted or capped run: paste its run or dataset ID and this run skips everything it already collected there. **Incremental mode** is for running the SAME search or URL again and again (for example daily) and getting only what changed; it keeps its own state per search, independent of any one run.

#### Can I use it with AI agents or MCP?

Yes. Call it from any Apify integration or MCP client, and use the connector field to push results into Notion, Linear or Airtable.

### 🔗 More scrapers you might like

Pair this actor with these related scrapers from the same team:

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👉 [Browse all abotapi scrapers](https://apify.com/abotapi)

### 💬 Support

- 🐞 **Found a bug or a missing field?** Open a ticket on the [Issues tab](https://apify.com/abotapi/asos-com-scraper/issues/open). We usually reply within hours.
- 🛠️ **Need another site, extra fields or a private build?** Email <contact@abotapi.com>.
- ⭐ **Enjoying it?** A quick review on the actor page helps other users find it.

# Actor input Schema

## `mode` (type: `string`):

How to start the scrape. 'search' runs store searches. 'url' processes the store URLs you paste: a product URL is fetched as a single product, and a search or category URL is paged like a search, its own query or category deciding the scope. The filters below apply to every walk in both modes; a pasted product URL is the one exception and returns that single product in full.

## `searchTerms` (type: `array`):

One or more things to search ASOS for, for example 'midi dress', 'slim jeans', 'white trainers'. Each term is scraped independently. Search mode only: in URL mode the scope is read out of each pasted URL instead. Leave this empty and the run browses with only the filters applied.

## `urls` (type: `array`):

Paste product URLs (https://www.asos.com/brand/product-name/prd/0000001, the short https://www.asos.com/prd/0000001 form works too), search URLs (https://www.asos.com/search/?q=midi+dress) or category URLs (https://www.asos.com/women/dresses/cat/?cid=8799). A pasted URL decides its own scope. Add \&page=3 (search URLs) or \&offset=48 (category URLs) to start the walk further in; a product URL ignores paging and returns that one product in full. The filters below narrow what the walks read: the brand, colour and ordering filters are sent to the store with every page, and the price bounds and Discounted rows only are applied to the rows this run reads.

## `brandIds` (type: `array`):

Only these brands. Type brand NAMES (e.g. "Bershka", "Nike", "ASOS DESIGN"), the actor matches them against the store's own brand list and resolves the ids itself; unknown names fail the run with the available options listed. Numeric store ids (e.g. 15370) also work and pass through unchanged. Multiple values return the union. Applies in BOTH search mode and URL mode.

## `baseColourIds` (type: `array`):

Only these base colours. Type colour NAMES (e.g. "Black", "Brown", "Multi"), the actor matches them against the store's own colour list and resolves the ids itself; unknown names fail the run with the available options listed. Numeric store ids (e.g. 4) also work and pass through unchanged. Multiple values return the union. Applies in BOTH search mode and URL mode.

## `sortBy` (type: `string`):

The store's own server-side ordering, sent with every page of every walk. This orders the walk itself (and therefore which rows a capped run keeps), not just the output. Applies in BOTH search mode and URL mode.

## `minPrice` (type: `integer`):

Only keep rows whose selling price is at least this many pounds. The store has no parameter for this, so it is applied to the rows this run reads. Applies in BOTH search mode and URL mode.

## `maxPrice` (type: `integer`):

Only keep rows whose selling price is at most this many pounds. The store has no parameter for this, so it is applied to the rows this run reads. Applies in BOTH search mode and URL mode.

## `onSaleOnly` (type: `boolean`):

Only keep rows whose selling price is below the original price, that is rows with a discount. The store has no parameter for this, so it is applied to the rows this run reads. Applies in BOTH search mode and URL mode.

## `fetchDetails` (type: `boolean`):

Fetch each item's product page for the description, the full size list (brand size and store size), and per-size stock availability including low-stock and restocking flags. Slower, and charged once per record. Leave off for a fast crawl: identity, prices, discount, brand and colour are included either way, without a stock state (the store does not serve one on its listing cards).

## `fetchReviews` (type: `boolean`):

Fetch each item's customer reviews: the rating summary (average, count and the Fit/Quality score breakdown) and the most recent reviews up to Max reviews per product. Slower, and charged once per record under the same details surcharge (never twice, even with Fetch product details also on). Leave off by default.

## `maxReviewsPerProduct` (type: `integer`):

Cap on review rows returned per product when Fetch reviews is on. The store serves one reviews page per product to automated readers, so this is a cap, not a pagination promise: rows beyond it are not fetched.

## `maxItems` (type: `integer`):

The single cap on this run: stop after collecting this many records across all search terms and URLs. Set 0 for unlimited.

## `maxPages` (type: `integer`):

Safety bound on how many result pages to walk per search term or URL. Leave empty (0) for no page limit: the run then stops at Max items, not here. Does not impose a separate cap below Max items.

## `proxy` (type: `object`):

Leave the default for the cheapest run. The store serves ordinary shared connections, so the default pool is enough. Change it only if a run reports that it could not read any results.

## `resumeFromRunId` (type: `string`):

Paste a previous run ID or dataset ID to continue a large crawl without returning or charging for records already collected there. Use this after an interrupted or capped run. For recurring monitoring of the same search, use Incremental mode below instead.

## `incrementalMode` (type: `boolean`):

Turn this on for daily or weekly recurring monitoring of the same search, for example a price watch. The first run returns everything matching as NEW. Later runs normally return only NEW, UPDATED and REAPPEARED records. Price moves and stock changes ARE reported as UPDATED: on a store they are the signal, not noise. Turn on Emit unchanged or Emit expired only when you also want those rows returned (and billed). State is kept separately per search, URL and filter setup; use State key to name or deliberately share a monitoring campaign. To continue one specific interrupted run instead, use Resume from a previous run above.

## `stateKey` (type: `string`):

Optional. Name this monitoring campaign to keep its state stable, or to deliberately share state across differently configured runs. Leave empty to let the actor derive a key automatically from the search terms, URLs and filters, so two different searches never mix state.

## `emitUnchanged` (type: `boolean`):

Off by default. Turn on to also return records that have not changed since the last run, marked UNCHANGED. This returns, and bills, extra rows you already have, so leave it off unless you specifically want a full snapshot every run.

## `emitExpired` (type: `boolean`):

Off by default. Turn on to also return records that were present in a previous run but are no longer found, marked EXPIRED. Only produced once a run has fully scanned the tracked search: not when Max items capped it, not when Resume was used, and not when the run was refused. This returns, and bills, extra synthetic rows, so leave it off unless you need expiry tracking.

## `mcpConnectors` (type: `array`):

Optionally send results into the apps you already use, via Model Context Protocol (MCP) connectors. Authorize one under Apify, Settings, API & Integrations, then select it here. Notion gets a page per record; other connectors get a best-effort write or digest. Each connector receives a condensed summary per record, not the full record; the complete record always stays in the dataset. Leave empty to skip; this never changes the dataset output. Supported: Notion (https://mcp.notion.com/mcp), Linear (https://mcp.linear.app/sse), Airtable (https://mcp.airtable.com/mcp), Apify (https://mcp.apify.com).

## `notionParentPageUrl` (type: `string`):

URL or id of the Notion page under which record pages are created. Required to enable the Notion export; ignored by other connectors.

## `maxNotifyListings` (type: `integer`):

Cap on records written to each connector per run. Does not affect the dataset.

## Actor input object example

```json
{
  "mode": "search",
  "searchTerms": [
    "midi dress"
  ],
  "urls": [
    "https://www.asos.com/women/dresses/cat/?cid=8799"
  ],
  "brandIds": [],
  "baseColourIds": [],
  "sortBy": "relevance",
  "onSaleOnly": false,
  "fetchDetails": false,
  "fetchReviews": false,
  "maxReviewsPerProduct": 10,
  "maxItems": 20,
  "maxPages": 0,
  "proxy": {
    "useApifyProxy": true
  },
  "incrementalMode": false,
  "emitUnchanged": false,
  "emitExpired": false,
  "maxNotifyListings": 50
}
```

# Actor output Schema

## `overview` (type: `string`):

No description

# API

You can run this Actor programmatically using our API. Below are code examples in JavaScript, Python, and CLI, as well as the OpenAPI specification and MCP server setup.

## JavaScript example

```javascript
import { ApifyClient } from 'apify-client';

// Initialize the ApifyClient with your Apify API token
// Replace the '<YOUR_API_TOKEN>' with your token
const client = new ApifyClient({
    token: '<YOUR_API_TOKEN>',
});

// Prepare Actor input
const input = {
    "mode": "search",
    "searchTerms": [
        "midi dress"
    ],
    "urls": [
        "https://www.asos.com/women/dresses/cat/?cid=8799"
    ],
    "brandIds": [],
    "baseColourIds": [],
    "fetchDetails": false,
    "fetchReviews": false,
    "maxItems": 20,
    "proxy": {
        "useApifyProxy": true
    },
    "incrementalMode": false,
    "emitUnchanged": false,
    "emitExpired": false
};

// Run the Actor and wait for it to finish
const run = await client.actor("abotapi/asos-com-scraper").call(input);

// Fetch and print Actor results from the run's dataset (if any)
console.log('Results from dataset');
console.log(`💾 Check your data here: https://console.apify.com/storage/datasets/${run.defaultDatasetId}`);
const { items } = await client.dataset(run.defaultDatasetId).listItems();
items.forEach((item) => {
    console.dir(item);
});

// 📚 Want to learn more 📖? Go to → https://docs.apify.com/api/client/js/docs

```

## Python example

```python
from apify_client import ApifyClient

# Initialize the ApifyClient with your Apify API token
# Replace '<YOUR_API_TOKEN>' with your token.
client = ApifyClient("<YOUR_API_TOKEN>")

# Prepare the Actor input
run_input = {
    "mode": "search",
    "searchTerms": ["midi dress"],
    "urls": ["https://www.asos.com/women/dresses/cat/?cid=8799"],
    "brandIds": [],
    "baseColourIds": [],
    "fetchDetails": False,
    "fetchReviews": False,
    "maxItems": 20,
    "proxy": { "useApifyProxy": True },
    "incrementalMode": False,
    "emitUnchanged": False,
    "emitExpired": False,
}

# Run the Actor and wait for it to finish
run = client.actor("abotapi/asos-com-scraper").call(run_input=run_input)

# Fetch and print Actor results from the run's dataset (if there are any)
print(f"💾 Check your data here: https://console.apify.com/storage/datasets/{run.default_dataset_id}")
for item in client.dataset(run.default_dataset_id).iterate_items():
    print(item)

# 📚 Want to learn more 📖? Go to → https://docs.apify.com/api/client/python/docs/quick-start

```

## CLI example

```bash
echo '{
  "mode": "search",
  "searchTerms": [
    "midi dress"
  ],
  "urls": [
    "https://www.asos.com/women/dresses/cat/?cid=8799"
  ],
  "brandIds": [],
  "baseColourIds": [],
  "fetchDetails": false,
  "fetchReviews": false,
  "maxItems": 20,
  "proxy": {
    "useApifyProxy": true
  },
  "incrementalMode": false,
  "emitUnchanged": false,
  "emitExpired": false
}' |
apify call abotapi/asos-com-scraper --silent --output-dataset

```

## MCP server setup

```json
{
    "mcpServers": {
        "apify": {
            "type": "http",
            "url": "https://mcp.apify.com/?tools=fetch-actor-details,abotapi/asos-com-scraper"
        }
    }
}
```

The hosted server signs you in with OAuth on first connect, so no API token belongs in this config. Clients without OAuth support can send an `Authorization: Bearer <APIFY_API_TOKEN>` header instead, using a token from API & Integrations in Apify Console (https://console.apify.com/settings/integrations).

## OpenAPI specification

Download the OpenAPI definition: https://api.apify.com/v2/actors/ODflaworP0tackyA0/builds/1mNf4svQMUYdefdOo/openapi.json