Mercari US Scraper: Sold Prices, Conditions & Sellers

Get structured listing data from mercari.com, including USD prices, condition labels, listing status, seller ID, and shipping fees. Built for resellers, pricing analysts, and store owners who need Mercari US datasets in bulk, without manual exports, complex proxy setups, or fragile scraper keys that break easily.

What does Mercari US Scraper do?

This Actor collects active and sold listings from any search query or category URL on Mercari US. Instead of relying on fragile webpage structures that break whenever the website changes its design, this scraper securely extracts real-time product information directly as the pages load.

It supports search queries with filters for pricing limits, item conditions, sort order, and listing status (active vs sold out). Scrolling and page transitions are handled automatically, and the run stops when your selected limit is reached.

Why use Mercari US Scraper?

Mercari US is America's second-largest peer-to-peer secondhand marketplace. Resellers, dropshippers, and pricing analysts require stable access to listing and completed-sales data:

• Sold Price Appraisal: Extract historically sold items to evaluate what buyers actually paid. This is the single most valuable metric for identifying high-margin reselling opportunities.
• Pricing Intelligence: Pull competitor prices to feed your automated spreadsheets, calculating your exact profits after shipping fees.
• Database Hydration: Provide clean, structured secondary-market listings to your automated pipelines (like Airtable, Excel, or Google Sheets).

How to use Mercari US Scraper

1. Configure input: Open the Input tab in your Apify Console.
2. Enter a keyword or URL: Provide a search keyword or paste a valid mercari.com search URL directly.
3. Apply status filters: Set the status to ["on_sale"] for active items, or ["sold_out"] to extract completed sold price history.
4. Select item conditions: Optionally narrow down by conditions such as ["new"] or ["like_new"].
5. Set limits: Specify a result cap (default: 1,000) and click Start.

Input

Field	Type	Description
startUrls	array	One or more Mercari US search, category, or listing URLs.
keyword	string	Search keyword query used if no startUrls are provided.
sort	string	Sort order: relevance, price_asc, listed_time, price_desc.
status	array	Listing status filter: on_sale, sold_out. Default: ["on_sale"].
priceMin	integer	Minimum price filter in USD.
priceMax	integer	Maximum price filter in USD.
condition	array	Condition labels: new, like_new, good, fair, poor.
limit	integer	Max listings to extract per query. Default: 1,000.
proxyConfiguration	object	Proxy settings. US rotating residential proxies are recommended.

Output

Each listing is returned as a structured JSON record inside the Apify dataset. You can download the dataset in JSON, CSV, Excel, or HTML format.

Example output record:

{
  "type": "listing",
  "id": 0,
  "url": "https://www.mercari.com/us/item/m78912345678/",
  "listing_id": "m78912345678",
  "title": "Vintage Patagonian Fleece Jacket Size L",
  "description": "Retro fleece jacket in excellent shape, no stains.",
  "price": 45,
  "original_price": 120,
  "currency": "USD",
  "listing_status": "active",
  "condition_id": "like_new",
  "brand": "Patagonia",
  "size": "L",
  "color": "Blue",
  "category_path": ["Men", "Coats & jackets", "Fleece Jacket"],
  "authenticated": false,
  "likes_count": 14,
  "thumbnail_url": "https://images.mercdn.net/item/m78912345678_1.jpg",
  "media": {
    "image_urls": ["https://images.mercdn.net/item/m78912345678_1.jpg"]
  },
  "seller_id": "89123456",
  "seller_username": "retro_finds_us",
  "seller_rating_score": 4.9,
  "seller_review_count": 112,
  "sales_count": 94,
  "shipping_payer": "buyer",
  "shipping_fee": 7.99,
  "item_location": "OR",
  "scrape_context": {
    "scraped_time": 1777464674689
  }
}

Data table

Field	Description
type	Always listing.
url	Full listing URL on mercari.com.
listing_id	Mercari US item ID (e.g. m78912345678).
title	Listing title.
description	Product text description.
price	Price in USD (float).
original_price	Retail price in USD (if available).
currency	Always USD.
listing_status	Status code: active or sold.
condition_id	Condition rating: new, like_new, good, fair, poor.
brand	Product brand name.
size	Sizing information (e.g. XL, 8.5).
color	Primary item color.
category_path	Array of strings representing category hierarchy.
authenticated	True if verified by Mercari Authenticate.
likes_count	Number of buyer favorites.
thumbnail_url	CDN-hosted primary image URL.
media.image_urls	List of all item photo URLs.
seller_id	Unique seller account identifier.
seller_username	Seller handle.
seller_rating_score	Average seller score out of 5 stars.
seller_review_count	Total reviews count.
sales_count	Total seller transactions.
shipping_payer	Who pays shipping: seller or buyer.
shipping_fee	Shipping rate in USD.
item_location	Sourcing state or city origin.

Pricing

Running this Actor costs approximately $2.99 per 1,000 results. A run of 500 listings typically completes in 2 to 3 minutes.

Tips

• Use proxies in production: Enable rotating proxies. Mercari US blocks search requests in large batches without rotating IP addresses.
• Validate first: Set the limit to 20-50 to check field coverage before running larger datasets.
• Deduplication: Adding multiple category URLs to startUrls will automatically deduplicate identical listing IDs inside the same run session.

FAQ, disclaimers, and support

Can I scrape completed sold price history? Yes. Set the status field to ["sold_out"] in the inputs.

How does this differ from other Mercari scrapers? Other scrapers rely on complex technical coding keys that break whenever the website's layout changes. This Actor reads the data directly as the browser receives it, making it much more reliable and stable.

Is this compliant? This Actor extracts public listings from mercari.com for research and comparison purposes. Users are responsible for ensuring their use complies with local laws, regulations, and platform terms of service.

Support: Open an issue in the Actor's Issues tab in your Apify Console.