Flipkart Product Search Data — Price, MRP, Specs & Ratings
Send a keyword and this source searches Flipkart and returns matching products as data: ID, title, brand, price, MRP, discount, image, key specs, rating and review counts.
{
"session_id": "11111111-1111-1111-1111-111111111111",
"kind": "flipkart_product_search",
"keyword": "iphone 15",
"max_items": 2,
"start_page": 1,
"partial": false,
"human": "# Flipkart product search\n\n- **Keyword:** iphone 15\n- **Starting page:** 1\n- **Max items:** 2\n- **Records returned:** 2\n- **Proxy traffic:** 575.9 KB",
"machine": {
"total_items": 2,
"first_item": {
"id": "itm235cd318bde73",
"product_id": "MOBGTAGPYYWZRUJX",
"url": "https://www.flipkart.com/apple-iphone-15-green-128-gb/p/itm235cd318bde73?pid=MOBGTAGPYYWZRUJX",
"alias": "apple-iphone-15-green-128-gb",
"title": "Apple iPhone 15 (Green, 128 GB)",
"brand": "Apple",
"price": 59900,
"list_price": null,
"discount_percentage": null,
"currency": "INR",
"image": "https://rukmini1.flixcart.com/image/832/832/xif0q/mobile/j/z/3/-original-imagtc5fqyz8tu4c.jpeg?q=70",
"key_specs": [
"128 GB ROM",
"15.49 cm (6.1 inch) Super Retina XDR Display"
],
"rating": 4.6,
"rating_count": 249074,
"review_count": 9818
},
"items": [
{
"id": "itm235cd318bde73",
"product_id": "MOBGTAGPYYWZRUJX",
"url": "https://www.flipkart.com/apple-iphone-15-green-128-gb/p/itm235cd318bde73?pid=MOBGTAGPYYWZRUJX",
"alias": "apple-iphone-15-green-128-gb",
"title": "Apple iPhone 15 (Green, 128 GB)",
"brand": "Apple",
"price": 59900,
"list_price": null,
"discount_percentage": null,
"currency": "INR",
"image": "https://rukmini1.flixcart.com/image/832/832/xif0q/mobile/j/z/3/-original-imagtc5fqyz8tu4c.jpeg?q=70",
"key_specs": [
"128 GB ROM",
"15.49 cm (6.1 inch) Super Retina XDR Display"
],
"rating": 4.6,
"rating_count": 249074,
"review_count": 9818
},
{
"id": "itm986f66c53cae4",
"product_id": "MOBGTAGPNEZZY2YR",
"url": "https://www.flipkart.com/apple-iphone-15-blue-256-gb/p/itm986f66c53cae4?pid=MOBGTAGPNEZZY2YR",
"alias": "apple-iphone-15-blue-256-gb",
"title": "Apple iPhone 15 (Blue, 256 GB)",
"brand": "Apple",
"price": 69900,
"list_price": null,
"discount_percentage": null,
"currency": "INR",
"image": "https://rukmini1.flixcart.com/image/832/832/xif0q/mobile/k/l/l/-resized-original-imagtc5fz9spysyk.jpeg?q=70",
"key_specs": [
"256 GB ROM",
"15.49 cm (6.1 inch) Super Retina XDR Display"
],
"rating": 4.6,
"rating_count": 249074,
"review_count": 9818
}
],
"proxy_traffic_bytes": 589706
},
"total_points": 2
}- You send
- A search keyword
- You get back
- Matching products with ID, title, brand, price, MRP, discount, image, key specs, rating and review counts
- Coverage
- Flipkart's searchable product catalog.
- Price
- 1 point per returned result, up to 500 per request — $1 per 1,000
- Billed per record actually returned, capped by max_items. A search that matches nothing costs nothing.
Ways to get this data
Three approaches teams use today, and where each one runs into trouble.
| Approach | What it takes | Cost | Trade-off |
|---|---|---|---|
| Searching Flipkart by hand | Type the keyword, scroll, copy | Free, and slow | Nobody keeps a category list current this way |
| Building a scraper | Write it, host it, and repair it when Flipkart changes the results page | Engineering time | A maintenance commitment for something that isn't your product |
| NeuralVerge | One request, keyword as a parameter | $1 per 1,000, misses not billed | A broad keyword returns a broad — and larger, more expensive — result set |
What you get back
Every field in the response shown above.
| Field | Type | Description |
|---|---|---|
total_items | number | How many products were returned in this batch (capped by max_items). |
id | string | Flipkart item ID (the itm... value). |
product_id | string | Flipkart's product ID (pid). |
url | string | Direct link to the product page. |
alias | string | URL slug of the product. |
title | string | Product title. |
brand | string | Brand as listed. |
price | number | Current price. |
list_price | null | Pre-discount price (MRP) where the result shows one; null in the sample. |
discount_percentage | null | Discount against the MRP where the result shows one; null in the sample. |
currency | string | Currency code, e.g. INR. |
image | string | Primary image URL. |
key_specs | array | Short list of headline specifications. |
rating | number | Average star rating. |
rating_count | number | Number of ratings. |
review_count | number | Number of written reviews. |
How to run it
The same lookup works from the app, the API, or as a tool an agent can call mid-task.
keyword is the only required field. max_items caps the result count (up to 500, defaults to 25) and sets what you're billed for; start_page sets the page to begin from.
curl -X POST https://api.neuralverge.ai/functions/v1/run-flipkart-product-search \
-H "Authorization: Bearer YOUR_API_KEY" \
-H "Content-Type: application/json" \
-d '{ "keyword": "wireless earbuds", "max_items": 2 }'What teams use it for
Where this field shows up in an actual workflow.
Pull every listing for a product type and compare price against rating.
See which brands and specs a category contains on Flipkart.
Re-run a keyword on a schedule to watch prices and ratings change.
Find IDs to feed into Flipkart product, reviews or seller lookups.
Coverage, freshness and limits
What this source covers, how fresh it is, and where it stops.
Flipkart's searchable product catalog.
Searched at request time.
This source returns publicly visible search results, stamped with the keyword it was read from and a session id you can trace.
- —Result order follows Flipkart's own ranking for the keyword.
- —A broad keyword returns a broad result set — narrow it or you'll pay for noise.
- —Search results carry less detail than a full product lookup; run Flipkart product for the description, images and availability.
Questions, answered
Pass it as product to Flipkart product, Flipkart product reviews or Flipkart seller.
Related sources
Full detail for a product you found here.
Customer reviews for a product.
The same idea on Amazon.
Amazon, eBay, Walmart, AliExpress, Alibaba, Avito, Craigslist, Flipkart and Mercari product, seller and review data.
Try flipkart product search on your own data
One request format across every source in the catalog.