Search Flipkart and read Indian marketplace prices as JSON
The Flipkart API returns product data from India's largest e-commerce marketplace as clean JSON.
12 active endpoints. Every call is 1 credit.
- POST/flipkart/v1/search
- POST/flipkart/v1/product
- POST/flipkart/v1/reviews
- POST/flipkart/v1/category
- POST/flipkart/v1/browse
- POST/flipkart/v1/similar
- POST/flipkart/v1/seller
- +5 more
What Flipkart endpoints does ReefAPI ship?
12 live read endpoints. Read-only data API: no writes, no account actions, no dashboard access on the target site.
Flipkart API
3 of 12 endpoints, ready to run
Product cards with the price and the maximum retail price in rupees, the discount, rating and rating count, key specs, stock and the category the row was classified into.
{ "ok": true, "meta": { "api": "flipkart", "endpoint": "search", "mode": "live", "latency_ms": 1743.3, "record_count": 24, "cache_hit": false }, "data": { "results": [ { "product_id": "COMH2TPSVSGUVKY4", "listing_id": "LSTCOMH2TPSVSGUVKY4MJENVA", "itm_id": "itm1bc0bcb4598e7", "title": "Acer Aspire Lite AMD Ryzen 3 Quad Core 5400U - (8 GB/256 GB SSD/Windows 11 Home) AL15-41 Thin and Light Laptop", "subtitle": "15.6 Inch, Steel Grey, 1.59 Kg", "url": "https://www.flipkart.com/acer-aspire-lite-amd-ryzen-3-quad-core-5400u-8-gb-256-gb-ssd-windows-11-home-al15-41-thin-light-laptop/p/itm1bc0bcb4598e7?pid=COMH2TPSVSGUVKY4", "price": 39990, "mrp": 44990, "discount_percent": 11, "currency": "INR", "rating": 4.2, "rating_count": 129, "review_count": 13, "images": [ "http://rukmini1.flixcart.com/image/832/832/xif0q/computer/u/p/m/-original-imah2pf2u98xefzx.jpeg?q=70", "http://rukmini1.flixcart.com/image/832/832/xif0q/computer/p/g/i/-original-imah3yhqmgfadrfy.jpeg?q=70", "http://rukmini1.flixcart.com/image/832/832/xif0q/computer/a/f/h/-original-imah2pf2fdbemtpw.jpeg?q=70" ], "image": "http://rukmini1.flixcart.com/image/832/832/xif0q/computer/u/p/m/-original-imah2pf2u98xefzx.jpeg?q=70", "availability": "IN_STOCK", "in_stock": true, "key_specs": [ "AMD Ryzen 3 Quad Core Processor", "8 GB DDR4 RAM", "Windows 11 Operating System" ], "vertical": "computer", "analytics": { "category": "Laptops", "subCategory": "Laptop", "superCategory": "LaptopAndDesktop", "vertical": "Laptop" }, "flipkart_advantage": true }, { "product_id": "COMHDG7CFDWVKYMZ", "listing_id": "LSTCOMHDG7CFDWVKYMZSGRBRE", "itm_id": "itm774438efecaf0", "title": "ASUS Vivobook 15 (2025) (i5 14th Gen) with MSO 2024 + M365 Basic*, Backlit Keyboard, Intel Core 5 120U - (16 GB/512 GB SSD/Windows 11 Home) X1504VAP-NJ2862WS / X1504VAP-BQ224WS Thin and Light Laptop", "subtitle": "15.6 Inch, Cool Silver, 1.7 Kg, With MS Office", "url": "https://www.flipkart.com/asus-vivobook-15-2025-i5-14th-gen-mso-2024-m365-basic-backlit-keyboard-intel-core-5-120u-16-gb-512-gb-ssd-windows-11-home-x1504vap-nj2862ws-x1504vap-bq224ws-thin-light-laptop/p/itm774438efecaf0?pid=COMHDG7CFDWVKYMZ", "price": 71500, "mrp": 75000, "discount_percent": 4, "currency": "INR", "rating": 4.3, "rating_count": 1876, "review_count": 152, "images": [ "http://rukmini1.flixcart.com/image/832/832/xif0q/computer/k/u/e/-original-imahcd8gzqjnp2vv.jpeg?q=70", "http://rukmini1.flixcart.com/image/832/832/xif0q/computer/v/s/v/x1504za-nj540ws-thin-and-light-laptop-asus-original-imahbguvdrdhjyt7.jpeg?q=70", "http://rukmini1.flixcart.com/image/832/832/xif0q/computer/y/h/a/-original-imahgfdfffgtybgg.jpeg?q=70" ], "image": "http://rukmini1.flixcart.com/image/832/832/xif0q/computer/k/u/e/-original-imahcd8gzqjnp2vv.jpeg?q=70", "availability": "IN_STOCK", "in_stock": true, "key_specs": [ "Intel Core 5 Processor", "16 GB DDR4 RAM", "Windows 11 Home Operating System" ], "vertical": "computer", "analytics": { "category": "Laptops", "subCategory": "Laptop", "superCategory": "LaptopAndDesktop", "vertical": "Laptop" }, "flipkart_advantage": false }, { "product_id": "COMHK77SZSZHTEV7", "listing_id": "LSTCOMHK77SZSZHTEV7VVWD14", "itm_id": "itm65704ff158138", "title": "HP Victus (i5 14th Gen) Intel Core 5 210 H - (16 GB/512 GB SSD/Windows 11 Home/6 GB Graphics/NVIDIA GeForce RTX 4050) 15-fa2203TX Gaming Laptop", "subtitle": "15.6 inch, Performance blue, 2.29 kg, With MS Office", "url": "https://www.flipkart.com/hp-victus-i5-14th-gen-intel-core-5-210-h-16-gb-512-gb-ssd-windows-11-home-6-graphics-nvidia-geforce-rtx-4050-15-fa2203tx-gaming-laptop/p/itm65704ff158138?pid=COMHK77SZSZHTEV7", "price": 94990, "mrp": 95746, "discount_percent": 0, "currency": "INR", "rating": 4.1, "rating_count": 61, "review_count": 5, "images": [ "http://rukmini1.flixcart.com/image/832/832/xif0q/computer/y/m/n/-original-imahzphnvwqqht2u.jpeg?q=70", "http://rukmini1.flixcart.com/image/832/832/xif0q/computer/9/u/d/-original-imahq5n6hprrvft4.jpeg?q=70", "http://rukmini1.flixcart.com/image/832/832/xif0q/computer/6/l/f/-original-imahn789a7zgcmhh.jpeg?q=70" ], "image": "http://rukmini1.flixcart.com/image/832/832/xif0q/computer/y/m/n/-original-imahzphnvwqqht2u.jpeg?q=70", "availability": "IN_STOCK", "in_stock": true, "key_specs": [ "Intel Core 5 Processor", "16 GB DDR4 RAM", "Windows 11 Operating System" ], "vertical": "computer", "analytics": { "category": "Laptops", "subCategory": "Laptop", "superCategory": "LaptopAndDesktop", "vertical": "Laptop" }, "flipkart_advantage": true } ], "query": "laptop", "total_results": 2288, "filters_applied": {}, "page": 1, "page_size": 24, "has_more": true, "next_page": 2 } }
How the Flipkart API works
Flipkart is a normal ReefAPI surface — the same four rules that hold for every other engine on the key.
No OAuth app, no request signing, no per-site account. One key covers all 185 engines.
Every route is a POST with a JSON body. Parameters are validated against the published schema before anything is charged.
Credits, not seats. Failed and blocked calls are never charged, and cache hits cost nothing.
One envelope everywhere. meta carries latency_ms, record_count and the endpoint that answered.
The sticker price is not what an Indian buyer pays
Flipkart's real price is the listed price minus a bank offer minus an exchange value. A price feed that reads only the price field is wrong by thousands of rupees on a phone, and the offer strip is a separate call.
{"q": "laptop", "page": 1}Take the row's own url. Forty rows of offers came back on the product we opened.
{"url": "<the url from above>"}Typed rows: a deal, an exchange value, a bank offer, a cashback, each with its own amount, plus the no-cost-instalment and cash-on-delivery flags.
Two credits for the price a buyer actually sees. The seller action answers who is behind the listing, and variants answers what the sibling configurations cost.
curl -X POST https://api.reefapi.com/flipkart/v1/search \
-H "x-api-key: $REEF_KEY" \
-H "content-type: application/json" \
-d '{"q":"laptop"}'{
"ok": true,
"data": { … },
"meta": {
"api": "flipkart",
"endpoint": "search",
"mode": "live",
"latency_ms": …,
"record_count": …
},
"error": null
}The four Flipkart identifiers, and which one each action accepts
Flipkart puts three different ids on the same product and a fourth on whoever sells it. Passing the wrong one is the usual reason a lookup comes back empty. Every shape below was read off a live response, and every price field on this API is INR.
| Identifier | Measured shape | What it identifies |
|---|---|---|
| product_id (FSN) | 16 uppercase alphanumerics with a category prefix: MOBH4DQF849HCG6G (phone), COMHAUZWVNJSFAMN (computer), TABGJ6XUSFTPNTKH (tablet), ACCGS8R72CHAX9Y8 (accessory), SHOHZ9SVFZEB3Y3Q (footwear) | One exact SKU: this colour, this storage. It is the pid= in a Flipkart URL. |
| listing_id | LST + the FSN + 6 more characters, 25 in total: LSTMOBH4DQF849HCG6GN4L5IU | One seller's offer on that SKU. It changes when the winning seller changes. |
| itm_id | itm + 13 hex characters: itm7c0281cd247be | The /p/ segment of the product URL. product, reviews, variants and similar all accept it directly. |
| seller_id | 16 lowercase hex: f2e07cd334ca4fad | The merchant. Flipkart publishes no /seller/<id> storefront, so this names a seller but cannot browse one. |
| currency | Always the string INR | price, mrp and every variant price. |
product, reviews, variants, similar and seller all accept a full product url instead of any id, and that is the safest input because the url carries both the itm_id and the pid. search returns all three product ids on every card, so keep the card and you never have to reconstruct one.
Rupees, the retail price, and the two things that will surprise a sync
Measured on the live marketplace across one query paged to 55 and three separate runs of page 1. Three of these go against us.
currency comes back as INR on the row, price and mrp as plain numbers. mrp — the maximum retail price — was filled on 23 of 24 rows, and the discount matches: 39,990 against 44,990 reports 11 per cent, which is exactly right. On a product with no markdown the two numbers are equal and no percentage is reported, rather than a fabricated one.
Three runs of one query each returned 24 rows. Two of them were identical; the third shared only 11 of 24 with the others. The grid is re-ranked between runs. De-duplicate by product_id and do not treat a page number as a stable anchor into the result set.
Pages 10, 20, 30, 40 and 41 all returned 24 fresh rows with no overlap on page 1. Page 42 and everything past it returned zero, on a query reporting 1,722 matches. So about 980 products are reachable per query.
We did this to ourselves twice while measuring: a product URL assembled from a title and a guessed id answers TARGET_BLOCKED. The same call with the url copied out of a search row answered in two seconds. Always carry the row's own url forward.
A product with no colour or configuration siblings answers PARSE_ERROR saying no variants were found, marked retryable. That is a genuine absence rather than a transient failure — read the message and move on rather than queueing a retry.
Every row carries Flipkart's own vertical plus a four-level analytics classification — category, sub-category, super-category and vertical — so a row can be bucketed without a keyword rule of your own.
The reviews action returns the rating, the title, the body, the certified-buyer badge, the helpful count and the configuration the reviewer actually bought. The published sample on this page drops the author field; the API returns what Flipkart publishes.
What people build with Flipkart
The jobs this data is most often used for.
endpoints
credit per call
Pricing teams call search to track Flipkart prices, MRP and discounts against competitors.
Catalog-enrichment tools use product and variants to fill listings with specs and options.
Market analysts use category and filters to size demand and price ranges in an Indian segment.
What Flipkart data costs
The cheapest call here is 1 credit, so $15/mo (Pro) buys 10,000 of them — $1.50 per 1,000 credits. Credits roll over and never expire, and failed or blocked calls are not charged.
Full pricing →- 1,000 free credits on signup, no card
- One key, all 185 APIs, one credit pool
- Failed and blocked calls are never charged
- Credits roll over and never expire
Call it in two lines
Sign up, get 1,000 credits and one key that works on every engine. Then this is the whole protocol.
curl -X POST https://api.reefapi.com/flipkart/v1/search \
-H "x-api-key: $REEF_KEY" \
-H "content-type: application/json" \
-d '{"q":"laptop"}'import requests
r = requests.post(
"https://api.reefapi.com/flipkart/v1/search",
headers={"x-api-key": REEF_KEY},
json={
"q": "laptop"
},
)
print(r.json()["data"])Have a question? We got answers.
The questions people actually ask before wiring up Flipkart.
Get a free key →Why do every colour and storage of the same phone report identical rating_count and review_count?▾
Because Flipkart aggregates ratings at the parent product, not per SKU. A measured search for 'apple iphone 16' returned eight cards spanning five colours and two storage sizes, and all eight reported rating_count 197427 and review_count 8517. The product action returns the same aggregate plus rating_breakup (a count per star value) and parameter_ratings (Camera 4.6, Battery 4.3, Display 4.6 on that listing). There is no per-colour rating anywhere in the response.
What is the difference between price, mrp and discount_percent?▾
mrp is the maximum retail price, the struck-through number; price is what Flipkart is charging; discount_percent is Flipkart's own rounded integer rather than something we compute. The two surfaces round it independently: a Motorola laptop listing came back as price 76990 and mrp 93690 with discount_percent 17 on the search card and 18 on the product record. If you need an exact percentage, derive it from price and mrp yourself.
Do out-of-stock products still carry a price?▾
At card and product level, yes. A measured lookup on Samsung Galaxy M35 5G (pid MOBH2Z9HJYYQBFGD) returned availability OUT_OF_STOCK and in_stock false alongside price 13719 and mrp 24499. Inside variants[] the rule is different: a variant Flipkart is not currently selling comes back with price null and in_stock false, which is what the 512 GB iPhone 16 returned while its 128 GB and 256 GB siblings carried prices.
Which field holds the price of the exact colour and storage I asked for?▾
variants[], keyed by product_id. On multi-storage listings the page-level price can echo the parent listing instead of the selected SKU: for all four iPhone 16 128 GB colours the product action returned price 69900 with discount_percent null, equal to the mrp, while the variants entry for that same product_id and the search card both returned 64900. Single-variant listings agree on both surfaces. Whenever a listing has more than one variant, read the price out of variants[].
Can a search come back with no prices at all?▾
Yes, intermittently, and it is visible when it happens: price, mrp and discount_percent go null together on every card while title, rating, images, availability and all three ids stay intact. Three consecutive identical 'laptop' searches returned 24 of 24, then 2 of 24, then 24 of 24 null prices, so it tracks which of two card layouts Flipkart serves rather than the query. Re-issue the request, or read prices from product and variants for the pids you care about.
What date does a review carry?▾
Not a date. created is the relative label Flipkart prints, and it changes shape with age: measured values on one listing were '1 day ago', '4 months ago', '11 months ago', 'Jan, 2025' and 'Apr, 2025'. If you need ordering, use sort=MOST_RECENT rather than parsing it. Reviews come 10 per page with meta.next_page for the next one; each carries certified_buyer, helpful_count, a location such as 'Kaimganj, Uttar Pradesh', and product_attributes naming the colour and storage that reviewer actually bought.
Why does the seller action return an empty results[] and catalog_count 0?▾
Because Flipkart has no public seller storefront to list. A measured call with the iPhone product URL resolved seller_id f2e07cd334ca4fad, flipkart_fulfilled true and availability_status IN_STOCK, with results [] and catalog_count 0. The action answers 'who sells this product', not 'what else does this seller list'. Pass product_url; a bare seller_id yields metadata only.
What is the Flipkart API?▾
Flipkart API is a ReefAPI endpoint group for flipkart It returns live JSON through POST requests under /flipkart/v1.
Is the Flipkart API free to try?▾
Yes. ReefAPI starts with 1,000 free credits, no card required. Flipkart calls use the same shared credit balance as every other ReefAPI engine.
Do I need a Flipkart login or account?▾
No login to Flipkart 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 Flipkart 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 Flipkart API use?▾
Flipkart actions currently cost 1 credit per successful call. Failed or blocked calls are free, and all APIs draw from one credit pool.
Can I call Flipkart from an AI assistant or MCP client?▾
Yes. Connect ReefAPI once through MCP and your assistant can call flipkart actions with the same key, credit pool and JSON envelope used by normal REST requests.
Is the Flipkart API a Flipkart scraper?▾
It is the managed alternative to a DIY Flipkart 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 flipkart back as clean JSON.
37 E-commerce & Marketplaces APIs on the same key
One key, one credit pool, one response envelope. If you are pulling Flipkart, you are one call away from the rest of the category — no second contract, no second integration.
Need something this API does not do?
Name the endpoint, the field, or a source we do not carry yet. We ship new APIs every week and you would be first to get the key. Real people read every message and reply the same day.
Try it on your own data before you pay anything
The call above is the real endpoint, not a recording. A free key gives you 1,000 credits, the other 184 APIs, and the same envelope everywhere.
Endpoints, parameters and credit costs on this page are read from the live catalog and cannot drift from what the API accepts. Field notes were captured on 2026-08-28.