Grailed Scraper — Streetwear Resale & Sold Prices | $1.50/1K avatar

Grailed Scraper — Streetwear Resale & Sold Prices | $1.50/1K

Pricing

from $4.00 / 1,000 listings

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Grailed Scraper — Streetwear Resale & Sold Prices | $1.50/1K

Grailed Scraper — Streetwear Resale & Sold Prices | $1.50/1K

Search Grailed resale listings via the public Algolia API. Returns price, price_drops, sold_price, condition, designer, size, strata (hype/luxury), seller score. Two-tier PPE: $1.50/1K active, $2.50/1K sold listings with confirmed prices. No proxy. Pay per result.

Pricing

from $4.00 / 1,000 listings

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Vitalii Bondarev

Vitalii Bondarev

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Grailed Scraper — Streetwear Resale + Sold Prices | from $1.50/1K | No Proxy

Built for streetwear resellers doing arbitrage between Grailed, StockX, and eBay — and for brand analysts tracking which designers are trending in the secondary market.

Pricing: Two-tier PPE — $1.50/1K (active listings), $2.50/1K (sold listings with confirmed sold_price). First 10 results free.

No proxy. No login. Self-healing Algolia key rotation.

Search Grailed listings by keyword, designer, category, or size via the public Algolia search API. Returns clean structured data including price history, condition, designers, seller score, and sold status. No proxy required. Pay per result.

Features

  • Search any keyword — brands, styles, items, designer names
  • 24 normalized fields — price, price_drops, condition, designers, category, size, color, sold, seller_username, seller_score, seller_reviews, cover_photo, listing_url, created_at, and more
  • parse_confidence field — quality indicator in every record (detects drift early)
  • No proxy needed — Grailed uses a public Algolia search key by design
  • Key-rotation fallback — if the hardcoded Algolia key rotates, the actor fetches a fresh key from the Grailed homepage automatically and retries
  • Client-side filters — designerFilter, categoryFilter, sizeFilter for targeted collection

How it works

Grailed's search is powered by Algolia and uses a public, intentionally exposed search-only API key embedded in window.PUBLIC_CONFIG on every Grailed page load. This is by design — the same key powers the site's search UI. The Algolia endpoint (*.algolia.net) has no Cloudflare protection.

Key-rotation durability

The hardcoded Algolia key is extracted once:

app_id: MNRWEFSS2Q
api_key: c89dbaddf15fe70e1941a109bf7c2a3d (as of 2026-05-31)
index: Listing_production

If this key ever rotates and returns HTTP 403, the actor automatically:

  1. Fetches https://www.grailed.com via curl_cffi (Chrome fingerprint)
  2. Extracts the fresh key via publicSearchKey regex from window.PUBLIC_CONFIG
  3. Retries the search with the fresh credentials

This makes the actor self-healing against key rotations without any manual update.

Input

FieldTypeDefaultDescription
searchQuerystringrequiredKeyword(s) to search (e.g. "nike vintage jacket")
maxItemsinteger100Max listings to return (1–10,000)
designerFilterstring""Filter by designer name (partial, case-insensitive)
categoryFilterstring""Filter by category (partial, case-insensitive)
sizeFilterstring""Filter by size (exact, case-insensitive)

Output fields

FieldTypeDescription
listing_idintGrailed numeric listing ID
titlestringListing title
pricefloatCurrent asking price (USD)
price_dropslistPrice drop history (descending)
conditionstring"new" / "new_with_tags" / "used"
designersstringComma-separated designer names
categorystringTop-level category (e.g. "outerwear")
category_pathstringFull category path (e.g. "outerwear.bombers")
sizestringSize string (e.g. "xl", "32")
colorstringPrimary color
soldboolTrue if sold
sold_pricefloatFinal sale price (null if not sold)
seller_usernamestringGrailed seller username
seller_scorefloatSeller rating average (0–5)
seller_reviewsintNumber of seller reviews
cover_photostringCover photo image URL
locationstringSeller location
marketplacestring"grailed" / "hbx" / etc.
stratastring"hype" / "luxury" / "sartorial" / "basic"
listing_urlstringCanonical Grailed listing URL
created_atstringISO 8601 UTC listing creation time
scraped_atstringISO 8601 UTC when this run started
parse_confidencefloatData quality score 0–1
warningslistQuality warning codes (e.g. ["price_missing"])

Sample output record

{
"listing_id": 97807015,
"title": "Nike x Off White Virgil Abloh Air Max 90 Brand New",
"price": 400.0,
"price_drops": [],
"condition": "new",
"designers": "Nike",
"category": "footwear",
"category_path": "footwear.lowtop_sneakers",
"size": "10",
"color": "white",
"sold": false,
"sold_price": null,
"seller_username": "luxcollector",
"seller_score": 4.993,
"seller_reviews": 146,
"cover_photo": "https://media-assets.grailed.com/prd/listing/temp/9d13f47b437549a69008a0baa5885421",
"location": "United States",
"marketplace": "grailed",
"strata": "hype",
"listing_url": "https://www.grailed.com/listings/97807015",
"created_at": "2026-05-31T15:47:24.368Z",
"scraped_at": "2026-05-31T15:48:53Z",
"parse_confidence": 1.0,
"warnings": []
}

Use cases

  • Market research — track prices and sold data for specific brands or items
  • Price monitoring — collect price_drops history to find deals
  • Resale arbitrage — compare Grailed prices vs other platforms
  • Trend analysis — track which categories and designers are trending (strata field)
  • Seller research — filter by seller_score for high-quality sources

Technical notes

  • Grailed uses Algolia's Listing_production index with ~250k+ active listings
  • Results are sorted by price_updated_at (default Algolia sort for this index)
  • No login or proxy required — this is Grailed's own public search infrastructure
  • The actor fetches 48 listings per page (Algolia max for this index)

Resale arbitrage example

Compare sold_price vs price to find underpriced listings:

  • sold_price: 320 + price: 200 → $120 spread on a Jordan 1
  • Use strata: "hype" filter to target the most liquid resale segment

vs. competitors

FeatureThis actorepctex/grailed-scraper (HTML)
Data sourceOfficial Algolia API (public)HTML scraping
price_drops historyYesNo
sold_price (comp data)YesRarely
strata field (hype/luxury)YesNo
Key rotation fallbackSelf-healingHard-coded (breaks on key change)
Price$1.50/1K active, $2.50/1K sold$3–5/1K flat

parse_confidence trust signal

Every record ships a parse_confidence score (0.0–1.0). Detects Algolia schema drift early.

Use with AI agents (MCP)

This actor is tagged MCP_SERVERS — compatible with Claude, GPT-4o, and other MCP-aware agents:

https://mcp.apify.com/?tools=bovi/grailed-listings

Pricing example

VolumeModeCost
100 listingsActive$0.15
1,000 listingsActive$1.50
100 listingsSold (with sold_price)$0.25
1,000 listingsSold (with sold_price)$2.50

First 10 results are free. Active vs sold routing happens automatically — sold items with a confirmed sold_price use the $2.50/1K rate.

FAQ

Do I need a proxy or login? No. Grailed search runs on a public Algolia endpoint — no proxy, no login, no credentials required.

What if the Algolia key changes? The actor self-heals: if the hardcoded key returns a 403, it fetches a fresh key from the Grailed homepage automatically and retries. No manual update needed.

What output formats are available? JSON (default), CSV, and Excel — via the Apify dataset export or API.

What if search returns empty? Try a broader keyword. Algolia's Grailed index has ~250k+ active listings. Misspellings and very niche terms return empty — use partial brand names (e.g. "Nike" not "Nike Off-White Collab Limited").

Pricing

Two-tier pay-per-result:

  • $1.50/1K — active listings (price, condition, designer, size)
  • $2.50/1K — sold listings with confirmed sold_price (comp data for arbitrage)

No proxy costs. No COGS.

Integrations

Built for streetwear resellers running arbitrage across Grailed, StockX, and eBay, plus analysts tracking secondary-market trends — the JSON/dataset output drops into the tools you already run, no glue code:

  • n8n / Make / Zapier — trigger a run or pipe every new dataset item into 500+ apps (Google Sheets, Airtable, Slack, HubSpot, your database) with no code: n8n, Make, Zapier.
  • Webhooks — fire your own endpoint the moment a run finishes, to push results straight into your pipeline (docs).
  • MCP server — expose this actor as a tool to Claude, Cursor, or any MCP client so an AI agent can pull this data mid-conversation (guide).
  • API & SDKs — fetch the dataset as JSON, CSV, or Excel through the Apify REST API or the Python / JS SDKs.

See all Apify integrations.