Vinted.fr Scraper: Listings, Item Detail & Seller Reviews

Vinted.fr Scraper turns Vinted.fr, France's C2C secondhand fashion marketplace, into structured listing and seller data. Search by keyword with brand, price, condition and sort filters, paste any item or seller/member link directly, or pull a seller's complete feedback history. Every listing carries identity, price, brand and photos out of the box, with full description, condition, size, material, colour and seller reputation available on request. Export to JSON, CSV or Excel, or read results straight through the API.

Why This Scraper?

• Three ways in. Keyword/brand/category search with real source-side filters, paste any item or seller/member URL directly, or pull a seller's full feedback history.
• Real search filters, not guesswork. Brand id, price range, condition and sort order map directly to Vinted.fr's own search parameters, verified to narrow results rather than being accepted and silently ignored.
• Full item detail from the item's own page. Condition, size, material, colour, category and full description, read from the listing's own structured data and on-page attributes, not a third-party estimate.
• Honest pricing. Vinted.fr shows a second, larger figure next to the listed price ("buyer protection included"), which is the current price plus a checkout fee, never a former price. This scraper reports only the real listed price and does not invent a wasPrice or discount field the marketplace itself doesn't expose.
• Native seller feedback. Overall rating, feedback count and every individual review (reviewer, date, star rating, comment) sourced from Vinted.fr's own feedback system.
• Built for schedules. Incremental mode returns only new, changed and reappeared listings on recurring runs; because a sold listing on a C2C marketplace is gone for good, a sold or removed listing comes back marked EXPIRED once a full scan confirms it.
• Resume without re-billing. Continue one interrupted run from its own previous dataset without re-collecting or re-charging what it already delivered.

Use Cases

• Resale price research: track a keyword or brand across the marketplace to benchmark asking prices, sizes and condition mix.
• Deal and restock alerts: schedule a search with incremental mode on and get notified only about new or changed listings.
• Seller due diligence: pull a seller's profile and complete feedback history before buying from or dealing with them.
• Marketplace analytics: build a dataset of brand, price and condition trends for a category or set of keywords.
• Storefront monitoring: watch one seller's whole listing catalogue for new items through URL mode's member enumeration.

Data You Get

Sample shape: values are illustrative placeholders, not from a live listing.

Field	Example
itemId	"00000001"
title	"Sample knitted jumper"
url	"https://www.vinted.fr/items/00000001-sample-knitted-jumper"
brandTitle	"Sample Brand"
priceAmount / currency	15.0 / "EUR"
promoted	false
isVisible	true
photos	[{"id": 1, "url": "https://images.example.com/000001.jpeg", "isMain": true}]
seller	{"id": "00000002", "username": "sample_seller", "business": false} (search results leave username empty until Fetch item detail fills it)
mainImage (fetchDetails)	"https://images.example.com/000001.jpeg"
description (fetchDetails)	"Full listing description text appears here when present."
condition (fetchDetails)	"Bon état"
conditionSchema (fetchDetails)	"UsedCondition"
size (fetchDetails)	"M"
material (fetchDetails)	"Coton"
color (fetchDetails)	"Bleu"
categoryPath (fetchDetails)	"Femmes Vêtements"
catalogId (fetchDetails)	"1242"
isReserved (fetchDetails)	false
sellerUsername / sellerFeedbackRating / sellerFeedbackCount (fetchDetails)	"sample_seller" / 0.98 (reputation score from 0 to 1) / 120
scrapedAt	"2026-01-01T00:00:00+00:00"

Detail enrichment also fills isHidden, instantBuy, canBuy, brand (id, title, slug), sellerId and sellerBusiness as flat fields; the seller's rating, feedback count and username appear both flat (matching the dataset's table view) and nested under seller.feedbackRating / seller.feedbackCount / seller.username, for the same values.

Reviews mode (mode: "reviews") returns a different row shape instead: reviewId, sellerId, itemId (of the reviewed purchase, when available), reviewerUsername, rating, body, isSystemFeedback, createdAt, reviewUrl, and the seller's current sellerFeedbackRating / sellerFeedbackCount attached to every review row.

When incrementalMode is on, every returned record (either shape) also carries changeType (NEW, UPDATED, UNCHANGED, REAPPEARED or EXPIRED), changedFields, firstSeenAt and lastSeenAt.

How to Use

1. Pick a mode: search (keyword/brand/category), url (paste item or seller/member links), or reviews (a seller's full feedback history).
2. Fill in the fields for that mode, and turn on Fetch item detail if you want full description, condition, size, material, colour and seller reputation.
3. Set Max items total (and optionally Max pages per search) to control run size and cost, then click Start.
4. Download the dataset as JSON, CSV or Excel, or read it through the API.

Basic keyword search:

{
  "mode": "search",
  "queries": ["sample keyword"],
  "maxItems": 20
}

Search with brand, price range, condition and sort:

{
  "mode": "search",
  "queries": ["sample keyword"],
  "brandId": "53",
  "minPrice": 5,
  "maxPrice": 60,
  "conditions": ["3", "4"],
  "sortBy": "price_low_to_high",
  "fetchDetails": true,
  "maxItems": 20
}

Paste item and seller/member links:

{
  "mode": "url",
  "urls": [
    "https://www.vinted.fr/items/00000001-sample-listing-title",
    "https://www.vinted.fr/member/00000002"
  ],
  "maxItems": 20
}

Pull a seller's full feedback history:

{
  "mode": "reviews",
  "sellers": ["00000002"],
  "maxItems": 100
}

Run it from your code

Python:

from apify_client import ApifyClient

client = ApifyClient("<YOUR_APIFY_TOKEN>")
run = client.actor("abotapi/vinted-fr-scraper").call(run_input={"mode": "search", "queries": ["sample keyword"], "maxItems": 20})
for item in client.dataset(run["defaultDatasetId"]).iterate_items():
    print(item["title"], item["priceAmount"], item["currency"])

JavaScript:

import { ApifyClient } from 'apify-client';

const client = new ApifyClient({ token: '<YOUR_APIFY_TOKEN>' });
const run = await client.actor('abotapi/vinted-fr-scraper').call({ mode: 'search', queries: ['sample keyword'], maxItems: 20 });
const { items } = await client.dataset(run.defaultDatasetId).listItems();

Or connect it to Make, Zapier, n8n, Google Sheets or webhooks from the Integrations tab.

How Max items and Max pages per search shape a run

The item budget (Max items total) splits evenly across every query, member URL or seller in one run. Max pages per search additionally caps how many result pages are walked per entry; leave it empty to walk as many pages as needed, bounded only by Max items.

A search run with more than one keyword that gets capped by its per-keyword share of Max items partway through a result page keeps the rest of that page marked as already seen internally, even though those listings were never returned. If a later keyword in the same run matches any of those listings, they are silently skipped there as well, so they are returned by neither keyword and the run can end with fewer rows than Max items. Keep Max items high enough to clear a full page for each keyword (or use 0 for unlimited, still bounded by Max pages per search) when several overlapping keywords run together, or split heavily-overlapping keywords into separate runs.

In Incremental mode specifically, the per-target budget of a keyword search, a seller's listing walk or a seller's review walk is drawn down as records are read, not only as they are actually returned; an unchanged, suppressed record still counts against the budget. On a recurring run where most previously-tracked records haven't changed, a walk can stop once it has read its share of the budget even though far fewer (or zero) new or changed rows were returned, while newer records further down the results stay unread; the run then reports that nothing changed. While the result order stays the same, later runs read the same first records and can keep missing those deeper changes. Raise Max items (or set it to 0, bounded by Max pages per search) above the size of the tracked scope on monitoring runs, and for searches consider sorting by newest first so fresh listings sit at the top of the walk.

Resume and recurring updates

• Resume (resumeFromRunId) continues one interrupted run: paste its run or dataset ID and the actor skips everything already collected there, so you don't pay twice.
• Incremental mode (incrementalMode) is for scheduled runs over the same scope. Each record is classified NEW, UPDATED (with changedFields), UNCHANGED (suppressed and not billed unless emitUnchanged is on), REAPPEARED or EXPIRED (only after a run that scanned the whole scope, and only with emitExpired). stateKey names or shares the stored state. With Incremental mode off, output is exactly as before.
• Turning on emitExpired adds a synthetic EXPIRED row for every tracked listing no longer found, once a run has fully scanned the tracked scope. These rows are added after Max items has already been applied to the run's freshly scraped listings, so a monitoring run with a large number of sold or removed listings can return, and be billed for, more rows in total than Max items specifies. If a hard per-run cap matters more than complete expiry tracking on a given run, leave emitExpired off, or expect the occasional oversized run when tracking a scope that turns over heavily.
• Combining resumeFromRunId with Incremental mode, on a state key with no prior incremental baseline, folds every id the resumed run already delivered (listings, or reviews in reviews mode) into the new baseline as a bare placeholder (marked present, with nothing recorded to compare against yet). The first later ordinary run (without Resume) that reads each of those records then has nothing on file to diff beyond presence, so it returns, and bills, every one of them as UPDATED with every field listed in changedFields, even when nothing on the marketplace actually changed. This happens once per record, on the first run that reads it after the bootstrap (usually the next run, unless Max items stops that run before reaching it); treat those UPDATED rows as informational rather than a real change signal.
• A manually set stateKey shared by runs with different searches, URLs, sellers or modes merges them into one tracked scope. With emitExpired on, a complete run of one configuration then marks every record tracked only by the other configuration as EXPIRED (and bills it), even though it was simply outside this run's scope, and it comes back as REAPPEARED when the other configuration runs again. Leave stateKey empty, or give each configuration its own key, unless every sharing run covers the same scope.

Send results into your apps (MCP connectors)

Optionally pipe the scraped results into the apps you already use, via Model Context Protocol (MCP) connectors. This is an extra delivery step after the scrape: the Apify dataset is never changed.

What gets written to the connector: a condensed, human-readable summary of each record, not the full JSON. Each item becomes one entry with a title and its key fields flattened to plain text. The complete record always stays in the Apify dataset.

1. Authorize a connector once under Apify → Settings → Integrations (Notion, Linear, Airtable, or Apify).
2. Select it in the "Pipe results into your apps" input field. (If the picker is empty, you haven't authorized a connector yet.)
3. For Notion, also set notionParentPageUrl to the page where items should be created.

The connection is mediated by Apify's MCP proxy, so this actor never sees your third-party credentials. Leave the field empty to skip.

Input Parameters

Parameter	Type	Default	Description
mode	string	search	search, url, or reviews.
queries	array	(none)	Free-text keywords (search mode). Item budget splits evenly across them.
categoryId	string	(none)	Vinted catalog id (search mode, optional). Narrows a keyword search, or browses the whole category when Search keywords is left empty.
brandId	string	(none)	Vinted brand id (search mode, optional).
conditions	array	(none)	Restrict to one or more condition levels (search mode, optional). Leave empty for any condition.
minPrice	integer	(none)	Minimum price in EUR (search mode, optional).
maxPrice	integer	(none)	Maximum price in EUR (search mode, optional).
sortBy	string	relevance	relevance, newest_first, price_low_to_high, or price_high_to_low.
urls	array	sample	Item pages (/items/<id>-<slug>) or seller/member pages (/member/<id>) to paste (url mode). A member URL enumerates every item that seller has listed. Filter fields above are ignored in this mode.
sellers	array	(none)	Numeric member ids or /member/<id> URLs to fetch feedback for (reviews mode). A plain username is not resolved to a member and is skipped.
fetchDetails	boolean	true	Adds full description, condition, size, material, colour, category, and the seller's feedback rating/count. Identity, price, brand and photos are already included without this toggle.
maxPages	integer	(none)	Stop after this many result pages per keyword/category/URL entry. Leave empty (or 0) for as many pages as needed, bounded by Max items.
maxItems	integer	20	Hard cap on total items (listings or reviews) returned across the whole run. 0 = unlimited (still bounded by Max pages per search).
proxy	object	Apify Proxy (Datacenter)	Vinted.fr works reliably over a Datacenter connection, so it stays the cost-efficient default. Switch to Residential only if you see a rise in failed runs.
mcpConnectors	array	(none)	Optional: send a summary of each record to apps you authorized under Integrations.
notionParentPageUrl	string	(none)	Notion connector only: page under which item pages are created.
maxNotifyListings	integer	50	Cap on items written to each connector per run. Does not affect the dataset.
resumeFromRunId	string	(none)	Continue one interrupted run without returning or charging for records already collected there.
incrementalMode	boolean	false	Turn on for daily or recurring monitoring; returns only new, changed and reappeared records on later runs.
stateKey	string	(none)	Name this monitoring campaign to keep its state stable, or to deliberately share state across differently-configured runs. Auto-derived from mode/search/URL/seller/detail settings when left empty.
emitUnchanged	boolean	false	Also return (and bill) records unchanged since the last run, marked UNCHANGED.
emitExpired	boolean	false	Also return (and bill) records no longer found since the last run, marked EXPIRED, once a run has fully scanned the tracked scope.

Output Example

Sample shape: values are illustrative placeholders, not from a live listing.

{
  "itemId": "00000001",
  "title": "Sample knitted jumper",
  "url": "https://www.vinted.fr/items/00000001-sample-knitted-jumper",
  "path": "/items/00000001-sample-knitted-jumper",
  "brandTitle": "Sample Brand",
  "priceAmount": 15.0,
  "currency": "EUR",
  "isVisible": true,
  "promoted": false,
  "photos": [
    { "id": 1, "url": "https://images.example.com/000001.jpeg", "width": 800, "height": 1200, "isMain": true }
  ],
  "seller": {
    "id": "00000002",
    "username": "sample_seller",
    "photo": "https://images.example.com/seller-000002.jpeg",
    "business": false,
    "feedbackRating": 0.98,
    "feedbackCount": 120
  },
  "description": "Full listing description text appears here when present.",
  "mainImage": "https://images.example.com/000001.jpeg",
  "conditionSchema": "UsedCondition",
  "condition": "Bon état",
  "size": "M",
  "material": "Coton",
  "color": "Bleu",
  "categoryPath": "Femmes Vêtements",
  "catalogId": "1242",
  "isReserved": false,
  "sellerId": "00000002",
  "sellerBusiness": false,
  "sellerFeedbackRating": 0.98,
  "sellerFeedbackCount": 120,
  "sellerUsername": "sample_seller",
  "scrapedAt": "2026-01-01T00:00:00+00:00"
}

Plan Requirement

The default proxy setting (Datacenter) works out of the box and stays the cost-efficient choice for this actor. For large or frequent runs, or if you notice a rise in failed runs, switch to the Residential proxy group under Connection.

FAQ

How much does it cost?

You pay per record returned, with detail enrichment billed only when Fetch item detail is on. The Pricing tab shows the current rates. Use Max items total to cap the cost of any run.

Is it legal to scrape Vinted.fr?

This actor collects only publicly available marketplace listings and seller feedback. You are responsible for how you use it: follow Vinted.fr's terms and the laws that apply to you, and get legal advice if you plan commercial redistribution. Do not use it to collect personal data beyond what a listing or public feedback entry itself shows.

Can I get only new or changed listings on a schedule?

Yes. Schedule the actor from the Schedules tab and turn on Incremental changes for scheduled runs. Each run then returns only new, updated and reappeared records, and unchanged ones are not billed unless you turn on Emit unchanged records.

What's the difference between Resume and Incremental mode?

Resume from a previous run continues one specific interrupted run so you don't re-collect or re-pay for what it already delivered; you paste its run or dataset ID once. Incremental mode is for recurring monitoring of the same search, URLs or sellers: the actor remembers its own state between scheduled runs, so you never paste an ID, and it keeps classifying records as new, changed, unchanged, reappeared or expired every time it runs.

Why did my run return fewer listings than Max items?

Two run shapes can do this. First, in a search with more than one keyword, a result page cut short by a keyword's share of Max items still marks the rest of that page as seen internally, so any of those listings that a later keyword also matches are skipped there too and returned by neither; keep Max items high enough to clear a full page per keyword, or run heavily-overlapping keywords separately. Second, in Incremental mode, the per-target budget is drawn from records read during the walk, not only from ones actually returned, so a recurring run where most records are unchanged (and suppressed) can stop at its budget having returned far fewer rows than Max items, or none, even with newer records left unread; raise Max items above the tracked scope on recurring runs (and sort searches by newest first) if you want every change picked up.

Why did the run right after a Resume plus Incremental bootstrap mark everything UPDATED?

Starting Incremental mode together with resumeFromRunId on a fresh state key seeds every id the resumed run already delivered into the new baseline without a stored snapshot to compare against. The next ordinary run (without Resume) that reads each of those records finds nothing on file to diff beyond "it exists", and returns (and bills) it as UPDATED with every field listed as changed. This happens once per record, normally on the very next run; treat those UPDATED rows as informational. Once a record has been read this way, its classification is accurate from then on.

Why did my run fail instead of returning an empty dataset?

If the site refuses every request, the run stops with a clear message so "no listings match" is never confused with "nothing could be read". Run it again in a few minutes. If only some pages could be read, you still get what was found.

Can I use it with AI agents or MCP?

Yes. Call it from any Apify integration or MCP client, and use the connector field to push results into Notion, Linear or Airtable.

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