Myntra Product Search Scraper

What is Myntra Product Search Scraper?

Myntra Product Search Scraper turns a Myntra keyword or a Myntra search or category URL into a dataset of fashion product cards. Each row is one product with its brand, product name, selling price, MRP, discount amount and percent, rating and rating count, available sizes, primary colour, gender, category taxonomy, sponsored flag, image and product URL, with prices in INR. Fashion brands, resellers, pricing analysts and AI shopping agents use it to monitor discounts, map assortments and compare brands across India's fashion catalog.

Why teams use it

• Search or browse. Send a shopper-style searchQuery such as running shoes, or category URLs like https://www.myntra.com/men-tshirts in startUrls.
• Price math done for you. price, mrp, discountAmount, discountPercent and discountLabel arrive together on every row.
• Full taxonomy. masterCategory, category, subCategory and articleType make it easy to group results.
• Sorted the way you need. sortBy supports relevance, newest, price up or down, biggest discount and popularity.
• Ranked rows. position keeps the order Myntra returned, which helps with share-of-shelf tracking.

Best fit for this Actor

• Designed for search and category listing pages on Myntra, from a quick keyword check to deep paginated category pulls.
• Best fit for price and discount monitoring, competitor assortment research and feeding product cards to dashboards or agents.
• When you need product-detail pages, product URL or ID input, or keyword and category search with optional detail enrichment in one Actor, then use Myntra Product Scraper, our full Myntra Actor. This Actor is the lighter search-and-category card export.
• To compare the same category on another Indian marketplace, use Flipkart Listings Scraper alongside this Actor.

Example workflow: weekly discount tracker for running shoes

A category manager at a sportswear brand starts with the keyword running shoes, sortBy set to discount and maxResults at 300. The dataset returns brand, price, MRP, discountPercent, rating and isSponsored for every card. He filters to his own brand and three competitors, compares average discount depth and rating per brand in a spreadsheet, and flags any competitor product above 70% off. He then schedules the run weekly and feeds the export into a pricing dashboard so the team sees markdown moves as they happen.

Input

{
  "searchQuery": "running shoes",
  "maxResults": 100,
  "sortBy": "discount",
  "proxyConfiguration": { "useApifyProxy": true }
}

Category browsing works with URLs instead of a keyword:

{
  "startUrls": [
    "https://www.myntra.com/men-tshirts",
    "https://www.myntra.com/women-dresses?sort=new"
  ],
  "maxResults": 200
}

Field	Type	What it controls
searchQuery	string	Keyword typed the way a shopper would, such as blue jeans or kurta.
startUrls	array	Myntra search or category page URLs. Each URL is paginated on its own.
maxResults	integer	Products returned across all searches and URLs, 1 to 10000. Default 100.
sortBy	string	relevance (default), new, price_asc, price_desc, discount or popularity. A sort parameter inside a start URL takes priority.
proxyConfiguration	object	Apify Proxy settings. Defaults to Apify Proxy.

Provide searchQuery, startUrls, or both.

Output

One dataset row per product card.

Field	What it contains
recordType, productId	Row type (product) and Myntra product ID
productName, brand	Product title and brand
price, mrp, currency	Selling price and MRP in INR
discountAmount, discountPercent, discountLabel	Discount in rupees, percent and Myntra's label
rating, ratingCount	Average rating out of 5 and number of ratings
gender, primaryColour, colourOptions	Target gender, main colour and number of colour variants
masterCategory, category, subCategory, articleType	Myntra taxonomy
sizes, inStock	Size labels on offer and stock flag
isSponsored, isFastFashion	Sponsored listing and fast-fashion flags
image, productUrl	Image URL and product page URL
searchQuery, position, scrapedAt	Source query, rank in the results and collection time

{
  "recordType": "product",
  "productId": "32093863",
  "productName": "HRX by Hrithik Roshan Unisex Mesh Running Shoes",
  "brand": "HRX by Hrithik Roshan",
  "price": 899,
  "mrp": 3999,
  "discountAmount": 3100,
  "discountPercent": 78,
  "discountLabel": "78% OFF",
  "currency": "INR",
  "rating": 4.26,
  "ratingCount": 4293,
  "gender": "Unisex",
  "primaryColour": "Black",
  "category": "Sports Shoes",
  "subCategory": "Shoes",
  "articleType": "Sports Shoes",
  "masterCategory": "Footwear",
  "sizes": ["3", "4", "5", "6", "7", "8", "9", "10", "11"],
  "inStock": true,
  "colourOptions": 2,
  "isSponsored": false,
  "isFastFashion": false,
  "image": "https://assets.myntassets.com/assets/images/2026/JULY/17/rUYdzFq0_c4a330f28de946809fac042c5bb49f44.jpg",
  "productUrl": "https://www.myntra.com/Sports-Shoes/HRX+by+Hrithik+Roshan/HRX-by-Hrithik-Roshan-Unisex-Mesh-Running--Shoes/32093863/buy",
  "searchQuery": "running shoes",
  "position": 1,
  "scrapedAt": "2026-10-01T01:30:47.554Z"
}

Pricing

This Actor uses Pay per event plus Apify platform usage. You pay for:

• Actor start, once per run.
• Myntra product scraped, once for each product card returned to the dataset.

Worked example: a running shoes search with maxResults set to 100 returns 100 product cards, so the run costs one Actor start event plus 100 Myntra product scraped events, plus the compute the run uses. maxResults is your spend cap. See the live Pricing tab on this page for current event prices.

API example

curl -X POST "https://api.apify.com/v2/acts/khadinakbar~myntra-product-search-scraper/run-sync-get-dataset-items?token=YOUR_API_TOKEN" \
  -H "Content-Type: application/json" \
  -d '{"searchQuery": "kurta", "sortBy": "popularity", "maxResults": 50}'

from apify_client import ApifyClient

client = ApifyClient("YOUR_API_TOKEN")
run = client.actor("khadinakbar/myntra-product-search-scraper").call(
    run_input={"searchQuery": "running shoes", "sortBy": "discount", "maxResults": 100}
)
for item in client.dataset(run["defaultDatasetId"]).iterate_items():
    print(item["brand"], item["price"], item["discountPercent"])

Use it with AI agents (MCP)

Connect the Actor to Claude, ChatGPT, Cursor or another MCP client through Apify MCP and ask:

Search Myntra for "blue jeans" sorted by discount, return the top 30 products with brand, price, MRP, discount percent and rating, and tell me which brands discount the most.

The agent receives product rows, reads them with get-dataset-items, and can cite productUrl and scrapedAt for each answer. Cost scales with the number of products returned, so a modest maxResults keeps exploratory agent runs inexpensive.

Best results

Starting situation	Helpful action	Expected outcome
A broad keyword	Add a qualifier such as men running shoes	A tighter, more relevant result set
Discount research	Set sortBy to discount	The deepest markdowns first
A specific Myntra category page	Paste its URL in startUrls	The exact category you browse on the site
Share-of-shelf tracking	Keep position and filter isSponsored	Organic versus paid placement per brand
A large category pull	Set maxResults to the depth you need and schedule it	Predictable spend per run

Builder's note

I built this around Myntra's own search results so that each row matches what a shopper sees on the listing page, including sponsored cards flagged with isSponsored. I found that pricing teams always recompute the discount, so every row carries price, mrp, the rupee difference and the percent together. Keeping the Actor focused on listing cards makes it quick for monitoring, and the product-detail Actor covers deeper per-product pages.

FAQ

What currency are prices in?

Indian Rupees (INR), shown in the currency field.

Does it go past the first page?

Yes. The Actor paginates automatically until it reaches maxResults.

Can I scrape a single product page?

This Actor reads search and category listings. For a single product page, use the Myntra Product Scraper linked above.

Responsible use

This Actor collects publicly available Myntra listing data. Use it in line with Myntra's terms and applicable laws, including intellectual-property rules for images and product text. Myntra is a trademark of its owner, and this independent Actor is not affiliated with or endorsed by Myntra. For questions, open a ticket in the Issues tab.