quikr.com APIquikr.com ↗
Access Quikr used product listings, prices, descriptions, and categories via API. Search by keyword, category, and location across India.
curl -X GET 'https://api.parse.bot/scraper/0dbe3f78-9be1-4960-821a-df8414fcaac2/search_listings?query=samsung&category=mobile-phones&location=Delhi' \ -H 'X-API-Key: $PARSE_API_KEY'
Search for used product listings by keyword, category, and location. Returns paginated results from QuikrBazaar. Listings may include price, image, and description snippet. Not all fields are present on every listing.
| Param | Type | Description |
|---|---|---|
| page | integer | Page number for pagination |
| query | string | Search keyword (e.g., 'iphone', 'samsung') |
| filters | object | Optional filters as a JSON object (e.g., {"condition": "Used", "brand": "Apple"}) |
| category | string | Category slug (e.g., 'mobile-phones', 'accessories', 'tablets', 'laptops', 'cameras', 'tv', 'sofas', 'beds', 'cars', 'bikes') |
| location | string | Location to search in (e.g., 'Delhi', 'Bangalore', 'India') |
{
"type": "object",
"fields": {
"url": "string, the URL that was fetched",
"page": "integer, current page number",
"listings": "array of listing objects with available fields: price, image_url, description_snippet, title, url, ad_id, posted_date"
},
"sample": {
"data": {
"url": "https://www.quikr.com/mobiles-tablets/Mobile-Phones+India+y149f",
"page": 1,
"listings": [
{
"price": "7999",
"image_url": "https://teja10.kuikr.com/i6/20171228/VB201705171774173-ak_LWBP77997365-1514461008.jpeg",
"description_snippet": "- 3GB RAM | 64GB ROM- 5.8 inch HD Display- 12MP Primary Camera | 7MP Front"
}
]
},
"status": "success"
}
}About the quikr.com API
The Quikr API exposes 4 endpoints for retrieving used product listings, full ad details, category hierarchies, and search suggestions from Quikr.com. The search_listings endpoint accepts keyword queries, category slugs, and location filters to return paginated results with title, price, image URL, and posted date. The get_listing_detail endpoint returns structured product attributes, multiple images, and full descriptions by ad ID.
Searching Listings
The search_listings endpoint accepts a query string (e.g., 'iphone'), a category slug (e.g., 'mobile-phones', 'laptops', 'sofas'), and a location string (e.g., 'Delhi', 'Bangalore', 'India'). Results are paginated via the page parameter. Each listing object in the listings array may include title, price, image_url, description_snippet, url, ad_id, and posted_date. Not all fields are guaranteed on every listing — sparse fields are normal for older or incomplete ads. The optional filters parameter accepts a JSON object for additional narrowing such as {"condition": "Used", "brand": "Apple"}.
Listing Detail and Attributes
The get_listing_detail endpoint takes a single ad_id string and returns the most complete record available: title, price in INR (no currency symbol), description, location (city name), posted_date as relative text (e.g., '11 Days Ago'), an images array of URL strings, and an attributes object containing product specs such as Brand_name, Model, and Condition. The attributes object is key-value and varies by category — a mobile phone listing will differ structurally from a furniture listing.
Categories and Suggestions
The get_categories endpoint requires no inputs and returns a categories array. Each entry carries a name, slug, and subcategories array — each subcategory has its own name, slug, and code. These slugs feed directly into the category parameter of search_listings. The get_search_suggestions endpoint accepts a partial query string and returns a suggestions array where each item includes keyworddata, subcatdata, and a direct url, making it useful for autocomplete interfaces or for discovering relevant category context before running a full search.
- Track price trends for used smartphones in a specific Indian city using
search_listingswithqueryandlocation - Build a cross-platform used goods aggregator by pulling listing titles, prices, and images from Quikr alongside other sources
- Populate an autocomplete search bar with Quikr suggestions using
get_search_suggestionson partial user input - Extract product attribute sets (brand, model, condition) from
get_listing_detailto train classification models - Monitor new listings for a specific category and location combination by polling
search_listingswithposted_datefiltering - Enumerate all Quikr subcategory slugs via
get_categoriesto build a complete taxonomy navigator - Identify competitive pricing for second-hand laptops or tablets by querying the
'laptops'or'tablets'category with location set to'India'
| Tier | Price | Credits/month | Rate limit |
|---|---|---|---|
| Free | $0/mo | 100 | 5 req/min |
| Hobby | $30/mo | 1,000 | 20 req/min |
| Developer | $100/mo | 5,000 | 250 req/min |
One credit = one API call regardless of which marketplace API you call. Exceeding the rate limit returns a 429 response. Authenticate with the X-API-Key header.
Does Quikr have an official developer API?+
What does `get_listing_detail` return for product specifications?+
attributes object containing key-value product specs such as Brand_name, Model, and Condition. The exact keys vary by category vertical — electronics listings include different fields than furniture or appliance listings. It also returns images (an array of URLs), price in INR, location, and posted_date as a relative string like '11 Days Ago'.Are seller contact details or phone numbers available through the API?+
How reliable is field coverage across listings in `search_listings`?+
listings array are not guaranteed to be populated on every result. Older or incomplete ads may be missing price, image_url, or description_snippet. The title, url, and ad_id fields are the most consistently present. get_listing_detail generally returns more complete data for any individual ad.