Mercari Real-Time Data — live resale market intelligence, thrift price comps, closet inventory, and vintage deal finder

Mercari Real-Time Data turns Mercari into a live pricing feed for fashion resellers. Search any thrift, vintage, or streetwear keyword and stream structured, ready-to-analyze data — prices, brands, sizes, condition, likes, seller stats, sold comps — straight into your dataset in real time. Whether you flip vintage single-stitch tees, hunt gorpcore fleece under retail, or run pricing models across marketplaces, this Actor gives you the market picture in seconds.

⚠️ Free plan notice: on a free Apify plan, runs are limited to 2 items per run. Upgrade to any paid Apify plan (Bronze or higher) for unlimited exports. See Free plan vs paid plans for details.

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👥 Who is this for?

• Vintage & thrift resellers sourcing undervalued inventory for Poshmark, eBay, Depop, and Mercari cross-listing
• Resale arbitrageurs hunting under-retail deals: vintage single-stitch tees, designer denim, gorpcore, Y2K, grail sneakers
• Consignment shop owners monitoring competitor closet inventory and sell-through
• Fashion market researchers and pricing intelligence teams tracking brand-level trends
• AI agents & automation builders wiring live resale data into Claude, LangChain, Zapier, Make, or custom pricing bots

🎯 What you can do with it

• Find undervalued thrift & vintage inventory — search "vintage 90s levis 501" with a max price and stream every hit with likes and condition to spot steals before anyone else
• Price comps & sell-through analysis — pull completed and sold listings for a brand or seller, compute average sold price, sell-through rate, and resale margins
• Closet inventory monitoring — track top competitors' or consignment closets' stock, pricing moves, and listing cadence
• Instant Slack / Discord deal alerts — every scraped row can be pushed live to a webhook, so newly listed steals hit your phone in seconds
• Multi-platform pricing sync — export clean JSON/CSV to feed cross-listing, repricing, and inventory pipelines
• AI agent feeds — plug the Actor into the Apify MCP server and ask your assistant market questions directly (see below)

✨ Feature matrix

Feature	What it does	Output (featureType)
🔍 Listing Search	Live keyword search with brand, size, condition, and min/max price filters. Defaults to 10 results per keyword for instant demo runs.	listing_search
🧬 Full Details Enrichment	Optional toggle on Listing Search: each search row is enriched in place with description, fabric/material tags, style tags, full image gallery, and seller shipping discounts. Same row, details_fetched: true — never duplicates, never filters items out.	listing_search
📦 Listing Details	Full listing records for specific Mercari URLs or listing IDs.	listing_details
🏬 Closet Listings	Scrape any reseller/thrift closet inventory to track competitor stock.	closet_listings
👤 Seller Profile	Reseller stats: love notes (ratings), items sold, closet size, verification, bio details.	seller_profile
🧾 Sold Item Comps / History	Completed and sold listings to calculate real market comps, resale margins, and sell-through rates.	sold_history
🔗 Scrape By URL	Direct Mercari URL processing: search URLs, closet URLs, item pages, category pages, brand feeds.	scrape_by_url

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🚀 Quick start

1. Click Start — the input is prefilled with three thrift keywords and 10 results max, so your first run finishes in seconds.
2. Watch results stream into the dataset row by row.
3. (Optional) Enable Enrich with full listing details for deeper rows, or add a Webhook URL for instant alerts.

Example searches that work well

Goal	Keywords	Filters
Vintage denim flips	vintage 90s levis 501, wrangler cowboy cut	Max price 60
Gorpcore sourcing	patagonia fleece, arcteryx gamma mx	Condition: like new
Workwear grails	carhartt detroit jacket, carhartt single knee	—
Y2K / streetwear	y2k baby tee, stussy 90s	—
Sneaker comps	jordan 1 chicago 1985	Sort: price high → low

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📥 Input parameters

🌍 Region

Field	Type	Default	Description
Region	select	US	Mercari market: US (USD) or JP (JPY). Affects currency and the recommended connection region.

🔍 Listing Search (on by default)

Field	Type	Default	Description
Search keywords	string list	3 thrift examples	One or more search terms. Required when Listing Search is on.
Max results per keyword	integer (1–200)	10	Listings per keyword. Defaults to 10 for instant first runs.
Sort order	select	created_time	Relevance, newest, price low→high, price high→low, most liked.
Brand filter	text	—	e.g. Carhartt, Levi's, Patagonia.
Size filter	text	—	e.g. M, L, 32.
Condition filter	string list	—	Condition IDs: 1 New, 2 Like new, 3 Hardly used, 4 Lightly used, 5 Used, 6 Damaged.
Min / Max price	integer	—	Price window in region currency — perfect for under-retail hunts.
Listing status filter	string list	STATUS_ON_SALE	STATUS_ON_SALE for live, STATUS_SOLD_OUT for sold.
Category ID	text	—	Optional numeric category ID.
Enrich with full listing details	checkbox	false	Enriches each search row in place with description, fabric/material tags, style tags, full image gallery, and seller shipping discounts. Same row (featureType: listing_search, details_fetched: true). Adds a little extra time per listing to enrich full product details.

📦 Listing Details

Field	Type	Default	Description
Listing IDs	string list	—	24-character Mercari listing IDs.
Listing URLs	string list	—	Full product URLs.

🏬 Closet Listings / 👤 Seller Profile / 🧾 Sold Item Comps

Field	Type	Default	Description
Seller IDs	string list	—	Mercari seller IDs. Shared by Closet Listings, Seller Profile, and Sold Comps.
Seller usernames	string list	—	Alternative to seller IDs.
Max listings per closet	integer (1–500)	30	Active listings per closet.
Max sold items per seller	integer (1–200)	30	Sold listings per seller.

🔗 Scrape By URL

Field	Type	Default	Description
Mercari URLs	string list	—	Any Mercari search, closet, item, category, or brand URL. Auto-detects the page type.
Max pages per URL	integer (1–20)	3	How many result pages to browse per URL.

✨ Output options

Field	Type	Default	Description
Include description	checkbox	true	Keep seller-written description text.
Include shipping details	checkbox	true	Keep shipping cost, method, and origin.
Include seller details	checkbox	true	Keep seller rating, counts, and location on item rows.

⚙️ Run limits & delivery

Field	Type	Default	Description
Global max items	integer (1–10000)	—	Hard cap across all features.
Webhook URL	text	—	Optional real-time push of every row (see Webhooks).
Webhook format	select	json	json (full record) or slack (Slack message).

🌐 Connection

Field	Type	Default	Description
Proxy settings	proxy	Apify Residential, US	Residential proxies recommended. Match the country to the Region.

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📤 Output fields (dataset schema)

Every row carries featureType, country, scrapedAt, and url, plus the fields below depending on the feature.

Pricing

Field	Type	Notes
current_price	number	Current asking (or sold) price.
currency	string	USD / JPY.
original_price	number	Seller's original price when discounted.
discount_percentage	number	Computed markdown %.
shipping_cost	number	0 = free shipping.
shipping_payer	string	Who pays shipping (seller-paid discounts show here).
free_shipping	boolean
accepts_offers / price_is_negotiable	boolean	Negotiation signals.
lowest_offer_accepted	number	When exposed by the seller.

Product

Field	Type	Notes
title, description	string	Description filled on details/enriched rows.
brand, brand_id	string	e.g. Carhartt.
size	string
condition	string	new, like_new, good, fair, poor.
condition_description	string	Seller's damage/notes text.
category, subcategory, category_path	string/array	Full hierarchy.
color, material, gender	string	Fabric/material when exposed.
style_tags, hashtags	array	Style & thrift tags.
item_specifics	object	Extra structured specifics when available.
is_vintage, is_handmade, is_authentic	boolean	Vintage & authenticity flags.
main_image_url, additional_image_urls	string/array	Full gallery on enriched rows.

Engagement & timing

Field	Type	Notes
likes_count, comments_count, views_count	integer	Demand signals.
number_of_offers	integer
is_promoted, is_featured	boolean
created_at, updated_at, sold_at	string	ISO timestamps.
time_since_listed	string	e.g. 2d 4h.
is_newly_listed	boolean	Listed in the last 24 h — instant-deal-alert bait.
is_sold, status		Availability.

Seller

Field	Type	Notes
seller_username, seller_id, seller_display_name	string
seller_rating, seller_ratings_count		Love notes.
seller_items_sold, seller_items_listed	integer	Sales history & closet size.
seller_verified, seller_response_rate		Trust signals.
seller_location, seller_join_date, seller_last_active	string

Shipping & location

Field	Type
item_location, ships_from, ships_to, shipping_method, local_pickup_available	string / array / boolean

Row metadata

Field	Type	Notes
featureType	string	Which feature produced the row.
position	integer	Search rank.
details_fetched	boolean	true when the search row was enriched in place.
pageType	string	scrape_by_url rows only.

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🔔 Webhook integration

Every row is always saved to the run dataset. Optionally, each row is also POSTed in real time to your webhook — perfect for instant alerts when a rare thrift item or low-priced comp drops.

Setup:

1. Put your webhook URL into Webhook URL (Slack, Discord, Zapier, Make, n8n, or your own pricing bot).
2. Choose Webhook format:
   • json — the full dataset record as JSON (Slack: use with Incoming Webhooks + a formatter; Discord/Zapier/Make: consume directly).
   • slack — a ready-to-post Slack message payload ({"text": "…"}), just paste a Slack Incoming Webhook URL.
3. Start the run — alerts arrive as rows stream, not at the end.

Slack payload example:

{
  "text": ":shopping_bags: *Carhartt Detroit Jacket Vintage Brown*  •  *Price:* $85  •  *Brand:* Carhartt  •  *Condition:* good\n*Seller:* thriftking92\n<https://www.mercari.com/us/item/m12345678901/|Open on Mercari>"
}

JSON payload: the full dataset record (all fields from the Output section above).

🤖 MCP / AI Agent usage

Plug this Actor into Claude Desktop, Cursor, or LangChain via the Apify MCP Server:

1. In Claude Desktop / Cursor, add the Apify MCP server and sign in with your Apify token.
2. Enable this Actor for the assistant.
3. Ask natural-language questions like:
   • "What is the average sold price for a 90s Carhartt J97 jacket on Mercari?"
   • "Find Patagonia fleece under $40 with more than 10 likes."
   • "Watch this closet and alert me when new vintage Levi's 501s drop."

The Actor returns clean, structured rows your AI agent can aggregate, chart, or reason over directly.

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🔒 Free plan vs paid plans

Plan	Behavior
Free (no paid plan)	Runs are capped at 2 items per run. A clear log line explains the cap and the run exits gracefully — no errors.
Any paid plan (Bronze+)	Paying user — full output. Unlimited results, all features, no caps.

• The cap applies to the whole run (all features combined) and is visible in the run's OUTPUT summary under paywall.
• Owners can tune the free cap (FREE_TIER_MAX_ITEMS) or block free runs entirely (FREE_TIER_MODE=block) via Actor environment variables in the Apify Console.
• Pay-per-event charges apply per collected result on paid plans.

❓ FAQ

Does this need my Mercari login or account? No. The Actor collects publicly available catalog data — no accounts, no logins, nothing to configure.

Do I need proxies? No setup needed — the Actor defaults to Apify Residential proxies (US) automatically, and the input lets you switch regions. Residential connections give the most reliable results at scale.

Why do I only get 2 results? You're on a free Apify plan. Free runs are capped at 2 items so you can try before you buy. Upgrade to any paid plan for unlimited exports.

How fast is a run? A prefilled 10-result search finishes in seconds. Full-details enrichment adds a little extra time per listing to enrich full product details. Large runs (10,000+ items) stream row by row, so memory stays flat and the run remains stable for hours (runs support up to 10,000 seconds).

How often can I run it? As often as you like. For continuous monitoring, schedule the Actor (e.g. every 15 minutes with a webhook) and diff dataset rows by created_at / is_newly_listed for new-drop alerts.

Is there rate limiting? The Actor automatically paces requests with small randomized pauses, rotates connections, and retries transient hiccups on your behalf. You don't need to configure anything — just keep result volumes within your plan's budget.

Can I get the raw internal payloads? No — output is a clean, stable, structured catalog schema. This keeps your pipelines from breaking when internal formats change.

Which regions are supported? US and JP markets. Currency and language adapt automatically.

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🧾 Notes

• One listing = one dataset row. Full-details enrichment merges into the same row (details_fetched: true) — never duplicates, never filters items out.
• Every discovered item goes to the dataset, even when deep attributes are unavailable — those rows simply carry null in the missing fields.
• Structured catalog intelligence only: stable field names, no internal payloads, no brittle formats.

Keywords this Actor shines with: thrift flips, vintage finds, streetwear, gorpcore, Y2K, resale arbitrage, market comps, sell-through, closet monitoring, Poshmark / eBay / Depop / Mercari cross-listing.