# Flipkart Products Scraper (`neuro-scraper/flipkart-products-scraper`) Actor

Flipkart Scraper SD - Flipkart Scraper is an e-commerce data tool that extracts Flipkart search and category results, product details (price, MRP, discount, ratings, specifications, seller) and customer reviews in INR, page after page, with no login.

- **URL**: https://apify.com/neuro-scraper/flipkart-products-scraper.md
- **Developed by:** [Neuro Scraper](https://apify.com/neuro-scraper) (community)
- **Categories:** E-commerce, Automation
- **Stats:** 2 total users, 1 monthly users, 100.0% runs succeeded, 0 bookmarks
- **User rating**: No ratings yet

## Pricing

from $2.49 / 1,000 results

This Actor is paid per event and usage. You are charged both the fixed price for specific events and for Apify platform usage.
Since this Actor supports Apify Store discounts, the price gets lower the higher subscription plan you have.

Learn more: https://docs.apify.com/actors/running/actors-in-store.md#pay-per-event

## What's an Apify Actor?

An Actor is a serverless cloud program that runs on the Apify platform. It has two run modes.
In Batch mode, an Actor accepts a well-defined JSON input, performs an action which can take anything from a few seconds to a few hours,
and optionally produces a well-defined JSON output, datasets with results, or files in key-value store.
In Standby mode, an Actor provides a web server which can be used as a website, API, or an MCP server.

Apify vocabulary and the platform model are defined once, in the agent quickstart at https://apify.com/agents.md.

## How to integrate an Actor?

If asked about integration, you help developers integrate Actors into their projects.
You adapt to their stack and deliver integrations that are safe, well-documented, and production-ready.

Do not guess an integration path. Every one of them is in the agent quickstart at https://apify.com/agents.md: the Apify MCP server, Agent Skills with the Apify CLI, the JavaScript and Python clients, the REST API, and the account-free path for an agent with no human to sign in. It also carries the rule on stating cost before the first paid run.

For examples already wired to this Actor's own input schema, see the [API](#api) section below.

Each client library has reference documentation the quickstart does not restate: [JavaScript/TypeScript](https://docs.apify.com/api/client/js/docs.md) (`npm install apify-client`) and [Python](https://docs.apify.com/api/client/python/docs.md) (`pip install apify-client`).

# README

### Flipkart Scraper

Flipkart Scraper exports Flipkart search results, category listings, full product details and customer reviews from flipkart.com, logged out. Prices are in INR.

Give it search terms or Flipkart URLs. In **products** mode you get one row per product (a product URL gives one full product row). In **reviews** mode you get one row per customer review of every product given by URL or found by the search terms.

It reads the data store Flipkart embeds in every page (`window.__INITIAL_STATE__`). The product id and listing id it needs for review pages are read from the live page on every run. It uses no login, no browser cookies and no CAPTCHA solving.

#### Input

| Field | Type | Default | Meaning |
|---|---|---|---|
| `mode` | select | `products` | `products` or `reviews` |
| `searchTerms` | array | `["iphone 15"]` (prefill) | What you would type in the Flipkart search box |
| `startUrls` | array | empty | Search URLs (your own filters and sort are kept), category URLs (`/mobiles/pr?sid=tyy,4io`) or product URLs (`/<name>/p/itm...?pid=...`, also `dl.flipkart.com` share links). The kind of each URL is detected automatically |
| `maxItems` | integer | `20` | Total rows: products, or reviews in reviews mode |
| `maxPagesPerSearch` | integer 1–100 | `50` | Safety limit on result pages per search term or URL |
| `sort` | select | `relevance` | `relevance`, `popularity`, `price_asc`, `price_desc`, `recency_desc`. Applies to search terms; URLs keep their own sort |
| `includeDetails` | boolean | `false` | Products mode: open each result's product page and add the detail fields below (one extra request per product) |
| `maxReviewsPerProduct` | integer 1–500 | `50` | Reviews mode: reviews per product |
| `reviewsSort` | select | `MOST_HELPFUL` | `MOST_HELPFUL`, `MOST_RECENT`, `POSITIVE_FIRST`, `NEGATIVE_FIRST` |
| `proxyConfiguration` | proxy | Apify RESIDENTIAL, India | Proxy for Flipkart |

#### Output: product rows

| Field | Meaning |
|---|---|
| `productId`, `listingId` | Flipkart product id (pid) and listing id (lid) |
| `title`, `brand`, `url` | Product name, brand, clean product URL |
| `price`, `mrp`, `discountPercent`, `currency` | Selling price, struck-out MRP (null when the item sells at MRP), discount %, `INR` |
| `rating`, `ratingsCount`, `reviewsCount` | Average stars, number of ratings, number of written reviews |
| `availability`, `isAssured` | `IN_STOCK`, `OUT_OF_STOCK`, `COMING_SOON`...; Flipkart Assured |
| `isSponsored`, `badge`, `offerText`, `keySpecs`, `warranty` | From the search card: ad flag, badge ("Bestseller"), card offer lines, key specs, warranty |
| `image` | Main image |
| `position`, `page`, `searchUrl` | Flipkart's rank, result page, the page the row came from |
| `priceWithOffers`, `offerCount` | Product page only: Flipkart's "Buy at" price with offers, number of offers |
| `ratingHistogram`, `featureRatings` | Product page only: count per star (1–5), feature ratings (Camera 4.6, Comfort POSITIVE...) |
| `highlights`, `specifications`, `description` | Product page only: highlight lines, `{group, name, value}` list, seller's description |
| `sellerName`, `sellerRating`, `sellerScores` | Product page only: seller, seller stars, Product Sold / Quality Score / Speed Score |
| `codAvailable`, `returnPolicy`, `color`, `images` | Product page only |
| `searchTerm` / `inputUrl`, `scrapedAt` | The input that produced the row, ISO time (UTC) |

"Product page only" fields appear when `includeDetails` is on or when you give product URLs.

#### Output: review rows

`reviewId`, `productId`, `productTitle`, `rating`, `title`, `text`, `author`, `date` (Flipkart's own text: "Aug, 2024" or "2 days ago"), `city`, `state`, `certifiedBuyer`, `helpfulCount`, `notHelpfulCount`, `images`, `productAttributes` (the variant bought, e.g. `{"Color": "Blue", "Storage": "128 GB"}`), `sortOrder`, `page`, `productUrl`, `reviewsUrl`, `searchTerm` / `inputUrl`, `scrapedAt`.

#### Measured limits (2026-10-03, local runs from one IP)

- Result pages hold 24 cards (list layout, e.g. phones) or 40 cards (grid layout, e.g. shoes: 24 organic + 16 sponsored, and the sponsored ones repeat on later pages - each product is kept once).
- Flipkart stops listing after about 1,000 products per search or category. Shoes search: page 25 had 40 cards, page 26 had 0. Mobiles category: page 41 had 24, page 42 had 0. "iphone 15" ran to its end: 18 pages, 405 unique products in 22 s.
- Grid cards often carry no rating, stock or Assured flag (40 of 40 shoe cards). Turn on `includeDetails` to read them from the product page.
- Reviews: 10 per page, at most 50 pages (500 reviews) per product and sort order. Colour and storage variants share one review pool, so a variant with the same rating numbers is skipped without a request.
- Sorting is Flipkart's own: with `price_asc` the order follows list price (MRP), so a discounted ₹67,999 phone (MRP ₹74,900) came after ₹69,900 phones.
- A keyword Flipkart cannot place gets unrelated "All Categories" items instead of "no results". That case is detected and skipped with a warning.
- Delivery dates and pincode serviceability are not collected. No delivery location is set, so Flipkart shows "Location not set".

#### Example input

```json
{"mode": "products", "searchTerms": ["running shoes", "bluetooth speaker"], "maxItems": 100, "sort": "price_asc", "includeDetails": false}
```

```json
{"mode": "reviews", "startUrls": [{"url": "https://www.flipkart.com/apple-iphone-15-blue-128-gb/p/itm387c20f1f5347?pid=MOBHQV9YZGYG64U7"}], "maxItems": 200, "maxReviewsPerProduct": 200, "reviewsSort": "MOST_RECENT"}
```

# Actor input Schema

## `mode` (type: `string`):

Products: one row per product found by the search terms or URLs (a product URL gives one full product row). Reviews: one row per customer review of every product given by URL or found by the search terms.

## `searchTerms` (type: `array`):

What you would type in the Flipkart search box, one per line. Example: iphone 15

## `startUrls` (type: `array`):

Flipkart search URLs with your own filters and sort (https://www.flipkart.com/search?q=running+shoes\&sort=price_asc), category URLs (https://www.flipkart.com/mobiles/pr?sid=tyy,4io) or product URLs (https://www.flipkart.com/apple-iphone-15-blue-128-gb/p/itm387c20f1f5347?pid=MOBHQV9YZGYG64U7). The kind of each URL is detected automatically.

## `maxItems` (type: `integer`):

Maximum number of rows in total (products, or reviews in reviews mode). Result pages are followed until this number is reached or Flipkart has no more. Example: 100

## `maxPagesPerSearch` (type: `integer`):

Safety limit on result pages read per search term or URL. Flipkart shows 24 or 40 products per page and stops after about 1,000 products (page 25 at 40 per page, page 41 at 24 per page in our tests). Example: 10

## `sort` (type: `string`):

Order of the results for the search terms above (URLs keep their own sort). Example: price_asc for the cheapest first.

## `includeDetails` (type: `boolean`):

Products mode: open each result's product page and add price with offers, rating histogram, feature ratings, highlights, specifications, description, seller, COD and return policy. One extra request per product, so runs take about 1 second longer per row.

## `maxReviewsPerProduct` (type: `integer`):

Reviews mode: how many reviews to collect per product. Flipkart serves 10 reviews per page and at most 50 pages (500 reviews) per product and sort order. Example: 100

## `reviewsSort` (type: `string`):

Reviews mode: the order Flipkart lists reviews in. Example: MOST_RECENT for the latest reviews.

## `proxyConfiguration` (type: `object`):

Proxy used for Flipkart. An Indian residential proxy is recommended and is the default.

## Actor input object example

```json
{
  "mode": "products",
  "searchTerms": [
    "iphone 15"
  ],
  "startUrls": [],
  "maxItems": 20,
  "maxPagesPerSearch": 50,
  "sort": "relevance",
  "includeDetails": false,
  "maxReviewsPerProduct": 50,
  "reviewsSort": "MOST_HELPFUL",
  "proxyConfiguration": {
    "useApifyProxy": true,
    "apifyProxyGroups": [
      "RESIDENTIAL"
    ],
    "apifyProxyCountry": "IN"
  }
}
```

# API

You can run this Actor programmatically using our API. Below are code examples in JavaScript, Python, and CLI, as well as the OpenAPI specification and MCP server setup.

## JavaScript example

```javascript
import { ApifyClient } from 'apify-client';

// Initialize the ApifyClient with your Apify API token
// Replace the '<YOUR_API_TOKEN>' with your token
const client = new ApifyClient({
    token: '<YOUR_API_TOKEN>',
});

// Prepare Actor input
const input = {
    "searchTerms": [
        "iphone 15"
    ],
    "startUrls": [],
    "maxItems": 20,
    "proxyConfiguration": {
        "useApifyProxy": true,
        "apifyProxyGroups": [
            "RESIDENTIAL"
        ],
        "apifyProxyCountry": "IN"
    }
};

// Run the Actor and wait for it to finish
const run = await client.actor("neuro-scraper/flipkart-products-scraper").call(input);

// Fetch and print Actor results from the run's dataset (if any)
console.log('Results from dataset');
console.log(`💾 Check your data here: https://console.apify.com/storage/datasets/${run.defaultDatasetId}`);
const { items } = await client.dataset(run.defaultDatasetId).listItems();
items.forEach((item) => {
    console.dir(item);
});

// 📚 Want to learn more 📖? Go to → https://docs.apify.com/api/client/js/docs

```

## Python example

```python
from apify_client import ApifyClient

# Initialize the ApifyClient with your Apify API token
# Replace '<YOUR_API_TOKEN>' with your token.
client = ApifyClient("<YOUR_API_TOKEN>")

# Prepare the Actor input
run_input = {
    "searchTerms": ["iphone 15"],
    "startUrls": [],
    "maxItems": 20,
    "proxyConfiguration": {
        "useApifyProxy": True,
        "apifyProxyGroups": ["RESIDENTIAL"],
        "apifyProxyCountry": "IN",
    },
}

# Run the Actor and wait for it to finish
run = client.actor("neuro-scraper/flipkart-products-scraper").call(run_input=run_input)

# Fetch and print Actor results from the run's dataset (if there are any)
print(f"💾 Check your data here: https://console.apify.com/storage/datasets/{run.default_dataset_id}")
for item in client.dataset(run.default_dataset_id).iterate_items():
    print(item)

# 📚 Want to learn more 📖? Go to → https://docs.apify.com/api/client/python/docs/quick-start

```

## CLI example

```bash
echo '{
  "searchTerms": [
    "iphone 15"
  ],
  "startUrls": [],
  "maxItems": 20,
  "proxyConfiguration": {
    "useApifyProxy": true,
    "apifyProxyGroups": [
      "RESIDENTIAL"
    ],
    "apifyProxyCountry": "IN"
  }
}' |
apify call neuro-scraper/flipkart-products-scraper --silent --output-dataset

```

## MCP server setup

```json
{
    "mcpServers": {
        "apify": {
            "type": "http",
            "url": "https://mcp.apify.com/?tools=fetch-actor-details,neuro-scraper/flipkart-products-scraper"
        }
    }
}
```

The hosted server signs you in with OAuth on first connect, so no API token belongs in this config. Clients without OAuth support can send an `Authorization: Bearer <APIFY_API_TOKEN>` header instead, using a token from API & Integrations in Apify Console (https://console.apify.com/settings/integrations).

## OpenAPI specification

Download the OpenAPI definition: https://api.apify.com/v2/actors/dV0Cg7fqBrfFWhFSs/builds/qKw1CYTtpJopLsbxr/openapi.json