Lamoda API & Scraper
The Lamoda API turns lamoda.ru, Russia's largest fashion e-commerce site, into JSON in four actions.
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search covers the whole catalogue: a keyword, a category, a brand, a gender or a colour (any combination, at least one of keyword, category or brand), up to 50 rows a page; every row carries product_id (the Lamoda SKU), title, model, brand, gender, images, the price the buyer pays now, the struck original price and the discount, the promotion behind the price with its end time, and every size with its stock. category lists one category 60 rows a page with the site's own sorts (popular, new, cheapest, dearest, biggest discount, newest discounts), an only-on-sale or only-full-price filter, a keyword, brand and gender, and adds the star rating, review count and season to each row. product returns one card in full: description, attribute table, supplier article, collection, season, category path, every size with its other size systems and stock, rating, review and question counts, and the seller with its public legal record. reviews pages through a product's customer reviews with the size bought and how it fit. One ReefAPI key, the standard { ok, data, meta, error } envelope, no Lamoda account.
What one Lamoda product returns
Real results read on 2026-10-15. The id from a search or listing row opened the same product card on 12 of 12 tries, with the same price, struck price, brand and size stock.
| product | what the site shows | price / was_price | other fields |
|---|---|---|---|
| Rich & Naked dress, search row | −60% badge, promotion ending that night | 11596 / 28990 | price_type onsite_promo, promotion.ends_at 2026-10-15T23:59 |
| adidas Originals Campus 00s W sneakers, product card | 4 961 ₽ · 12 099 ₽ | 4961 / 12099 | 5 sizes, rating 5.0 (7 reviews), supplier article JH8880 |
| Termit sneakers, product card (marketplace seller) | 2 665 ₽ · 4 443 ₽ | 2665 / 4443 | seller Спортмастер with its tax and registration numbers |
price is what the buyer pays without an account right now; when a timed promotion runs, the store's plain price field still shows the original, so price is taken from the promotion and promotion says which one and until when. was_price is null when nothing is discounted.
Real request and response JSON
Captured from the indexed primary action, search, on .
{
"method": "POST",
"url": "https://api.reefapi.com/lamoda/v1/search",
"headers": {
"x-api-key": "$REEF_KEY",
"content-type": "application/json"
},
"body": {
"query": "кеды",
"limit": 20
}
}{
"ok": true,
"meta": {
"api": "lamoda",
"endpoint": "search",
"mode": "live",
"latency_ms": 5845.3,
"record_count": 20,
"bytes": 241590,
"cache_hit": false,
"upstream_requests": 1,
"charged_credits": 3,
"version": "0.1.0",
"request_id": "0ac5005f2bdd43cd",
"queue_ms": 1.1,
"fetched_at": "2026-10-18T11:42:05.630Z"
},
"data": {
"results": [
{
"position": 1,
"product_id": "RTLAFQ557301",
"title": "Кеды",
"model": "Tensaur Sport 2.0 K",
"brand": "adidas",
"brand_id": 1061,
"gender": "children",
"url": "https://www.lamoda.ru/p/rtlafq557301/shoes-adidas-kedy/",
"image": "https://a.lmcdn.ru/product/R/T/RTLADN575001_23971432_1_v1.jpg",
"images": [
"https://a.lmcdn.ru/product/R/T/RTLADN575001_23971432_1_v1.jpg",
"https://a.lmcdn.ru/product/R/T/RTLADN575001_23971433_2_v1.jpg",
"https://a.lmcdn.ru/product/R/T/RTLADN575001_23971434_3_v1.jpg"
],
"price": 1416,
"was_price": 4799,
"discount_percent": 70,
"discount_percent_site": 70,
"price_type": "onsite_promo",
"promotion": {
"type": "onsite_promo",
"price": 1416,
"percent": 70,
"ends_at": "2026-10-19T23:59:59.000+03:00"
},
"promo_code_price": null,
"price_display": "1416 ₽",
"currency": "RUB",
"available": true,
"stock_quantity": 119,
"stock_cap": null,
"sizes": [
{
"size": "[trimmed-depth]",
"size_system": "[trimmed-depth]",
"brand_size": "[trimmed-depth]",
"brand_size_system": "[trimmed-depth]",
"size_sku": "[trimmed-depth]",
"stock_quantity": "[trimmed-depth]",
"stock_capped": "[trimmed-depth]",
"available": "[trimmed-depth]",
"other_systems": "[trimmed-depth]"
},
{
"size": "[trimmed-depth]",
"size_system": "[trimmed-depth]",
"brand_size": "[trimmed-depth]",
"brand_size_system": "[trimmed-depth]",
"size_sku": "[trimmed-depth]",
"stock_quantity": "[trimmed-depth]",
"stock_capped": "[trimmed-depth]",
"available": "[trimmed-depth]",
"other_systems": "[trimmed-depth]"
},
{
"size": "[trimmed-depth]",
"size_system": "[trimmed-depth]",
"brand_size": "[trimmed-depth]",
"brand_size_system": "[trimmed-depth]",
"size_sku": "[trimmed-depth]",
"stock_quantity": "[trimmed-depth]",
"stock_capped": "[trimmed-depth]",
"available": "[trimmed-depth]",
"other_systems": "[trimmed-depth]"
}
],
"colours": [
"белый"
],
"category_id": 261,
"category_ids": [
261,
2079,
2217
],
"attributes": {
"site_section": "OUTLET, SPORT",
"production_country": "Вьетнам"
},
"tags": [
"аутлет"
],
"badges": [
"−70%"
]
},
{
"position": 2,
"product_id": "MP002XW0N7IC",
"title": "Кеды",
"model": null,
"brand": "Matrix Sport",
"brand_id": 36725,
"gender": "women",
"url": "https://www.lamoda.ru/p/mp002xw0n7ic/shoes-matrixsport-kedy/",
"image": "https://a.lmcdn.ru/product/M/P/MP002XW0N7IC_29023475_1_v1_2x.jpg",
"images": [
"https://a.lmcdn.ru/product/M/P/MP002XW0N7IC_29023475_1_v1_2x.jpg",
"https://a.lmcdn.ru/product/M/P/MP002XW0N7IC_29023476_2_v1_2x.jpg",
"https://a.lmcdn.ru/product/M/P/MP002XW0N7IC_29023477_3_v1_2x.jpg"
],
"price": 1599,
"was_price": 4740,
"discount_percent": 66,
"discount_percent_site": 66,
"price_type": "onsite_promo",
"promotion": {
"type": "onsite_promo",
"price": 1599,
"percent": 66,
"ends_at": "2026-10-18T23:59:59.000+03:00"
},
"promo_code_price": null,
"price_display": "1599 ₽",
"currency": "RUB",
"available": true,
"stock_quantity": 249,
"stock_cap": null,
"sizes": [
{
"size": "[trimmed-depth]",
"size_system": "[trimmed-depth]",
"brand_size": "[trimmed-depth]",
"brand_size_system": "[trimmed-depth]",
"size_sku": "[trimmed-depth]",
"stock_quantity": "[trimmed-depth]",
"stock_capped": "[trimmed-depth]",
"available": "[trimmed-depth]",
"other_systems": "[trimmed-depth]"
},
{
"size": "[trimmed-depth]",
"size_system": "[trimmed-depth]",
"brand_size": "[trimmed-depth]",
"brand_size_system": "[trimmed-depth]",
"size_sku": "[trimmed-depth]",
"stock_quantity": "[trimmed-depth]",
"stock_capped": "[trimmed-depth]",
"available": "[trimmed-depth]",
"other_systems": "[trimmed-depth]"
},
{
"size": "[trimmed-depth]",
"size_system": "[trimmed-depth]",
"brand_size": "[trimmed-depth]",
"brand_size_system": "[trimmed-depth]",
"size_sku": "[trimmed-depth]",
"stock_quantity": "[trimmed-depth]",
"stock_capped": "[trimmed-depth]",
"available": "[trimmed-depth]",
"other_systems": "[trimmed-depth]"
}
],
"colours": [
"коричневый"
],
"category_id": 5301,
"category_ids": [
5301,
5855,
2968
],
"attributes": {
"production_country": "Китай"
},
"tags": [],
"badges": [
"−66%"
]
},
{
"position": 3,
"product_id": "RTLAFQ471501",
"title": "Кеды",
"model": "CAMPUS 00s W",
"brand": "adidas Originals",
"brand_id": 1163,
"gender": "women",
"url": "https://www.lamoda.ru/p/rtlafq471501/shoes-adidasoriginals-kedy/",
"image": "https://a.lmcdn.ru/product/R/T/RTLAFQ471501_38855470_1_v1_2x.jpg",
"images": [
"https://a.lmcdn.ru/product/R/T/RTLAFQ471501_38855470_1_v1_2x.jpg",
"https://a.lmcdn.ru/product/R/T/RTLAFQ471501_38855471_2_v1_2x.jpg",
"https://a.lmcdn.ru/product/R/T/RTLAFQ471501_38855472_3_v1_2x.jpg"
],
"price": 4114,
"was_price": 12099,
"discount_percent": 66,
"discount_percent_site": 65,
"price_type": "onsite",
"promotion": null,
"promo_code_price": null,
"price_display": "4 114 ₽",
"currency": "RUB",
"available": true,
"stock_quantity": 1128,
"stock_cap": null,
"sizes": [
{
"size": "[trimmed-depth]",
"size_system": "[trimmed-depth]",
"brand_size": "[trimmed-depth]",
"brand_size_system": "[trimmed-depth]",
"size_sku": "[trimmed-depth]",
"stock_quantity": "[trimmed-depth]",
"stock_capped": "[trimmed-depth]",
"available": "[trimmed-depth]",
"other_systems": "[trimmed-depth]"
},
{
"size": "[trimmed-depth]",
"size_system": "[trimmed-depth]",
"brand_size": "[trimmed-depth]",
"brand_size_system": "[trimmed-depth]",
"size_sku": "[trimmed-depth]",
"stock_quantity": "[trimmed-depth]",
"stock_capped": "[trimmed-depth]",
"available": "[trimmed-depth]",
"other_systems": "[trimmed-depth]"
},
{
"size": "[trimmed-depth]",
"size_system": "[trimmed-depth]",
"brand_size": "[trimmed-depth]",
"brand_size_system": "[trimmed-depth]",
"size_sku": "[trimmed-depth]",
"stock_quantity": "[trimmed-depth]",
"stock_capped": "[trimmed-depth]",
"available": "[trimmed-depth]",
"other_systems": "[trimmed-depth]"
}
],
"colours": [
"белый"
],
"category_id": 129,
"category_ids": [
129,
905,
5855
],
"attributes": {
"site_section": "OUTLET, SPORT",
"production_country": "Вьетнам"
},
"tags": [
"аутлет"
],
"badges": [
"−66%"
]
}
],
"count": 20,
"page": 1,
"limit": 20,
"total_results": 19515,
"last_page": 498,
"has_more": true,
"query": "кеды",
"predicted_query": "кеды",
"applied_filters": {}
}
}What the Lamoda API does
| Action | Description | Concrete use case | Key params |
|---|---|---|---|
| search | Search the whole Lamoda catalogue by keyword and/or category, brand, gender and colour (at least one of query, category_id or brand_id). Rows carry the price, struck price, per-size stock (uncapped on this surface), colours and category. | Pricing teams call search to search the whole Lamoda catalogue by keyword and/or category, brand, gender and colour (at le…. | query, category_id, brand_id, gender, color_id, ... |
| category | List one Lamoda category, 60 rows a page, with the site's sorts, the on-sale filter, an optional keyword, brand and gender. Rows add rating, review count and seasons; per-size stock on this surface is capped at 10 by the source (stock_capped says when). | Marketplace operators call category to list one Lamoda category, 60 rows a page, with the site's sorts, the on-sale filter, an optio…. | category_id, query, brand_id, gender, on_sale, ... |
| product | One full Lamoda product card by SKU or URL: title, brand, supplier article, description, attributes, price and struck price, every size with its stock (the card caps stock at 20 per size), colours, season, collection, category path, rating, review and question counts, seller and its legal owner. | Catalog enrichment teams call product to get one full Lamoda product card by SKU or URL. | product_id, url |
| reviews | Customer reviews of one Lamoda product, paged: star rating, text, author's display name, date, the size bought, size fit, likes and photos. | Retail analysts call reviews to get customer reviews of one Lamoda product, paged. | product_id, sort, direction, page, limit |
Call search from your stack
curl -X POST https://api.reefapi.com/lamoda/v1/search \
-H "x-api-key: $REEF_KEY" \
-H "content-type: application/json" \
-d '{"query":"кеды","limit":20}'import requests
r = requests.post(
"https://api.reefapi.com/lamoda/v1/search",
headers={"x-api-key": REEF_KEY},
json={
"query": "кеды",
"limit": 20
},
)
print(r.json()["data"])const res = await fetch("https://api.reefapi.com/lamoda/v1/search", {
method: "POST",
headers: {
"x-api-key": process.env.REEF_KEY,
"content-type": "application/json",
},
body: JSON.stringify({
"query": "кеды",
"limit": 20
}),
});
const { ok, data, meta, error } = await res.json();Ask your MCP-connected assistant: call reefapi.lamoda.search with {"query":"кеды","limit":20}.Who uses this API and why
- Track fashion prices in Russia: product for your SKUs, with the paid price, the struck price and the promotion's end time.
- Watch promotions: category with sort=new_sale or discount lists the newest and deepest markdowns.
- Size-level availability: search returns every size with its real stock for assortment and sell-through analysis.
- Compare with Wildberries: the same keyword on both stores, rows with matching field names.
- Read customer feedback: reviews with the size bought and how it fit.
Questions developers ask before integrating
Which prices does it return?
The price the buyer pays (price), the struck original price (was_price) with the computed discount_percent, the store's own discount figure (discount_percent_site), price_type (original, onsite markdown or onsite_promo) and, for a timed promotion, promotion with its percent and end time. In our 2026-10-15 sample 56 of 260 search rows and 142 of 420 listing rows were priced by a running promotion. A price that needs a promo code would be returned apart as promo_code_price; none appeared. Prices shown only after signing in (Lamoda Club) are not available.
How exact is the stock figure?
It depends on the action, because Lamoda publishes different ceilings on different pages. search returns the real per-size figure (up to 480 seen). The category listing stops at 10 per size and the product card at 20 per size; on those, stock_capped tells you when the figure is the ceiling rather than the count.
Why does a listing row sometimes contain sizes of another product?
The category listing groups colour variants of one model and can show sizes of a sibling SKU inside a row. Every size names its own product_id; the row's stock and availability count only its own sizes, and sizes_from_other_products lists the siblings (17 of 420 rows in our sample).
How many results can I page through?
search: up to 50 rows a page and up to result 10 000 (the store's own ceiling); last_page tells you where it ends. category: 60 rows a page and up to page 167. total_results is the store's own count.
Which filters does search take?
query, category_id, brand_id, gender (women, men, girls, boys, children, unisex) and color_id, one value each. Sorting, the sale filter and a keyword inside one category are on the category action. A price range is not offered: the store's price filter returned products outside the requested range in our tests.
What does the seller block contain?
On product: the seller's name and whether Lamoda itself or a marketplace partner sells it, and the legal owner's company name, shop name, tax number, registration number, address and the delivery terms the seller publishes.
How fast is it?
One request to the store per call. Over three runs every positive call succeeded (69 of 69); median times were about 3.2 seconds for search, 4.4 to 5.2 seconds for category pages, 2.8 to 3.3 seconds for product cards and about 3 seconds for reviews, with the slowest calls around 9 seconds.
What is the Lamoda API?
Lamoda API is a ReefAPI endpoint group for russia's lamoda fashion store as json: keyword search, category listings with the site's sorts and sale filter, full product cards with the price the buyer pays, every size with its stock, the seller, and customer reviews. It returns live JSON through POST requests under /lamoda/v1.
Is the Lamoda API free to try?
Yes. ReefAPI starts with 1,000 free credits, no card required. Lamoda calls use the same shared credit balance as every other ReefAPI engine.
Do I need a Lamoda login or account?
No login to Lamoda is needed for the API response. You call ReefAPI with your x-api-key header, and the playground can run live examples before you create a production key.
How fresh is the Lamoda data?
The page example is captured from a live search call, and production requests fetch live data through ReefAPI rather than a static sample.
How many credits does the Lamoda API use?
Lamoda actions currently cost 1-3 credits per successful call. Failed or blocked calls are free. All APIs draw from one credit pool.
Can I call Lamoda from an AI assistant or MCP client?
Yes. Connect ReefAPI once through MCP and your assistant can call lamoda actions with the same key, credit pool and JSON envelope used by normal REST requests.
Is the Lamoda API a Lamoda scraper?
It is the managed alternative to a DIY Lamoda scraper. Instead of building and maintaining your own scraper — proxies, headless browsers, captcha and constant breakage — you call one ReefAPI endpoint and get the same russia's lamoda fashion store as json: keyword search, category listings with the site's sorts and sale filter, full product cards with the price the buyer pays, every size with its stock, the seller, and customer reviews back as clean JSON.