# Vinted Deep Scraper - Beyond the 960-Item Cap (`koatiromeo/vinted-deep-scraper`) Actor

Extract Vinted listings across 24 marketplaces: price, buyer-protection fee, total price, brand, size, condition, favourites, photos and seller. Automatic price partitioning breaks Vinted's hard 960-result cap, returning several times more items per query. No proxy, no browser.

- **URL**: https://apify.com/koatiromeo/vinted-deep-scraper.md
- **Developed by:** [Koati Romeo](https://apify.com/koatiromeo) (community)
- **Categories:** E-commerce
- **Stats:** 2 total users, 1 monthly users, 83.3% runs succeeded, 0 bookmarks
- **User rating**: No ratings yet

## Pricing

from $3.00 / 1,000 item scrapeds

This Actor is paid per event. You are not charged for the Apify platform usage, but only a fixed price for specific events.

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

## What's an Apify Actor?

Actors are web data automations that power AI and operations. They run on the Apify platform to scrape websites, process data, connect APIs, and automate workflows.
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.
Actors are written with capital "A".

## 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.
The best way to integrate Actors is as follows.

- **AI agents and MCP clients** — the [Apify MCP server](https://docs.apify.com/integrations/mcp.md) at `https://mcp.apify.com` (remote, streamable HTTP, OAuth on first use).
- **Agentic workflows and local Actor development** — [Agent Skills](https://apify.com/.well-known/agent-skills/index.json) with the [Apify CLI](https://docs.apify.com/cli/docs.md): `npm install -g apify-cli`, then `apify login`.
- **JavaScript/TypeScript projects** — the official [JS/TS client](https://docs.apify.com/api/client/js/docs.md): `npm install apify-client`.
- **Python projects** — the official [Python client](https://docs.apify.com/api/client/python/docs.md): `pip install apify-client`.
- **Any other language** — the [REST API](https://docs.apify.com/api/v2.md).

For usage examples, see the [API](#api) section below.

For more details, see Apify documentation as [Markdown index](https://docs.apify.com/llms.txt) and [Markdown full-text](https://docs.apify.com/llms-full.txt).

# README

## Vinted Deep Scraper — Beyond the 960-Item Cap

> **Unofficial tool.** Not affiliated with, endorsed by, or sponsored by Vinted.

Extract Vinted listings — price, brand, size, condition, favourites, photos and seller — from
any of **24 Vinted marketplaces**, as clean JSON, CSV or Excel.

### The problem this solves

Vinted's catalog will not give you more than **960 items for a single query**, no matter how many
results actually exist. The page size is capped at 96, page 11 returns an error, and the reported
total freezes at 960 — so the API stops telling you the truth well before you have the data.

Most Vinted scrapers inherit that ceiling and quietly stop there.

This Actor splits your query into **disjoint price slices**, each of which gets its own 960-item
budget, and keeps subdividing any slice that is still saturated. Duplicates across slice
boundaries are removed before anything is saved.

Measured on the query `nike` (vinted.fr, 11 August 2026):

| Mode | Unique items returned |
|---|---|
| Standard (what the API gives you) | 791 |
| Deep scan | **3 682** |

That is **4.6× more data from the same query**, and the run had not exhausted the price range.
Yield varies with how deep your query's inventory actually goes.

### What you get per listing

```json
{
  "id": "9634976009",
  "title": "T-shirt Nike",
  "url": "https://www.vinted.fr/items/9634976009-t-shirt-nike",
  "brand": "Nike",
  "size": "L",
  "condition": "Très bon état",
  "price": 5.0,
  "buyerProtectionFee": 0.95,
  "totalPrice": 5.95,
  "currency": "EUR",
  "favouriteCount": 2,
  "viewCount": 0,
  "isPromoted": false,
  "photoUrl": "https://images1.vinted.net/t/06_01e82/f800/1786455915.jpeg",
  "photoCount": 3,
  "sellerId": "285557605",
  "sellerLogin": "matheoh7",
  "sellerUrl": "https://www.vinted.fr/member/285557605-matheoh7",
  "sellerIsBusiness": false,
  "marketplace": "www.vinted.fr",
  "matchedQuery": "nike",
  "priceBucket": "3-5"
}
```

`price` is what the seller asks. `totalPrice` is what the buyer actually pays, buyer protection
included — the number you need for any resale or arbitrage calculation, and the one that is
missing from a plain listing export.

### Input

| Field | What it does |
|---|---|
| **Search queries** | One or more keywords. Leave empty to browse a filtered catalog with no keyword. |
| **Marketplace** | Which of the 24 country sites to query. Prices come back in that market's currency. |
| **Maximum items** | Hard stop for the run. You are charged only for items actually saved. |
| **Deep scan** | Breaks the 960-item cap by price splitting. On by default. |
| **Sort by** | Relevance, newest first, or price ascending/descending. |
| **Minimum / maximum price** | Restrict the range. Deep scan splits inside whatever range you set. |
| **Category / brand / size / condition / colour IDs** | Copy the `catalog_ids`, `brand_ids`, `size_ids`, `status_ids` or `color_ids` values straight out of a filtered Vinted search URL. |

### Cost

Priced per item saved. Nothing is charged for items that are not delivered: the run stops
collecting as soon as your spending limit is reached, and the counter in the log always matches
the number of rows in the dataset.

### Notes and limits, stated honestly

- **Deep scan is switched off automatically when `maxItems` is 960 or less.** Below the cap it
  would add nothing and would bias your sample: slices are walked cheapest-first, so a small
  budget would return only the low end of the market instead of the most relevant results.
- **Deep scan costs more requests than a flat run** — roughly one request per 55 items delivered
  in testing — because saturated slices have to be probed before they are harvested.
- **Sold items are not returned.** Vinted's catalog only exposes active listings.
- **No login, no proxy, no browser.** The Actor talks to the public catalog endpoint over plain
  HTTP, which is why it is fast and cheap to run.
- Photo URLs are signed by Vinted and expire after some time. Download what you need promptly.

### FAQ

**Why do I get fewer items than `maxItems`?**
Your query genuinely ran out of inventory. The log prints each price slice and its size, so you
can see exactly where the catalog ended.

**Can I scrape several countries in one run?**
Not in a single run — pick one marketplace per run. Prices, currencies and inventories differ
per country, so mixing them in one dataset would be misleading.

**Why are some items repeated in the log counter but not in the dataset?**
Price slices overlap slightly at their boundaries. Duplicates are removed by listing ID before
anything is saved, and the number removed is reported at the end of the run.

**Can I get a seller's full inventory?**
Not through this Actor — it walks the catalog, not member profiles.

# Actor input Schema

## `searchQueries` (type: `array`):

Keywords to search, one entry per query. Leave empty to browse the filtered catalog without a keyword.

## `country` (type: `string`):

Which Vinted country site to query. Prices are returned in that marketplace's currency.

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

Hard stop for this run, across all queries. You are only charged for items actually saved.

## `deepScan` (type: `boolean`):

Vinted returns at most 960 items per query. When enabled, the query is split into disjoint price slices so each slice gets its own 960 budget - typically 3 to 10 times more items. Turn it off for the fastest possible run.

## `order` (type: `string`):

Sort order applied to each request.

## `priceFrom` (type: `integer`):

Lower price bound, in the marketplace's currency. Leave empty for no minimum.

## `priceTo` (type: `integer`):

Upper price bound, in the marketplace's currency. Leave empty for no maximum.

## `catalogIds` (type: `string`):

Comma-separated Vinted catalog IDs, taken from the catalog\_ids parameter of a filtered Vinted search URL.

## `brandIds` (type: `string`):

Comma-separated Vinted brand IDs, taken from the brand\_ids parameter of a filtered Vinted search URL.

## `sizeIds` (type: `string`):

Comma-separated Vinted size IDs, taken from the size\_ids parameter of a filtered Vinted search URL.

## `conditionIds` (type: `string`):

Comma-separated Vinted condition IDs, taken from the status\_ids parameter of a filtered Vinted search URL.

## `colorIds` (type: `string`):

Comma-separated Vinted colour IDs, taken from the color\_ids parameter of a filtered Vinted search URL.

## Actor input object example

```json
{
  "searchQueries": [
    "nike air max 90"
  ],
  "country": "fr",
  "maxItems": 100,
  "deepScan": true,
  "order": "relevance"
}
```

# Actor output Schema

## `results` (type: `string`):

One row per Vinted listing: title, brand, size, condition, price, buyer-protection fee, total price, favourites, views, photos and seller.

# 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 = {
    "searchQueries": [
        "nike air max 90"
    ],
    "country": "fr",
    "maxItems": 100
};

// Run the Actor and wait for it to finish
const run = await client.actor("koatiromeo/vinted-deep-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 = {
    "searchQueries": ["nike air max 90"],
    "country": "fr",
    "maxItems": 100,
}

# Run the Actor and wait for it to finish
run = client.actor("koatiromeo/vinted-deep-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 '{
  "searchQueries": [
    "nike air max 90"
  ],
  "country": "fr",
  "maxItems": 100
}' |
apify call koatiromeo/vinted-deep-scraper --silent --output-dataset

```

## MCP server setup

```json
{
    "mcpServers": {
        "apify": {
            "type": "http",
            "url": "https://mcp.apify.com/?tools=fetch-actor-details,koatiromeo/vinted-deep-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/15Hxr54AySfVspePU/builds/kAB0xVFTMacLzr15x/openapi.json