Filtering

Since v3.1.20 (2025-06-12) you can now write queries to filter the results. It's based on Meilisearch's query syntax, you can read the original documentation here.

Writing queries for StockX endpoints

Currently, the StockX product model is structured as follows:

{
  "id": "uuid",
  "name": "string",
  "description": "string",
  "model": "string",
  "slug": "string",
  "brand": "string",
  "gender": "string",
  "product_type": "string",
  "category": "string",
  "secondary_category": "string",
  "categories": ["string"],
  "sku": "string",
  "rank": "number",
  "release_date": "string",
  "colorway": "string",
  "prices": {
    "currency_market": {
      // ^ Example: "USD_US", "EUR_FR"
      "size": "float"
      // ^ Example: 9.5 -- Value is the lowest price for this size
    }
  },
  "barcodes": ["string"]
}

This page will be updated whenever this structure changes. All fields are filterable, but only name, description, model, slug, brand and sku are searchable.

Examples

Get all products with a price lower than 100 USD for size 11:

prices.USD_US.11 < 100

You should exclude products with a price of 0 USD, which are not available for sale.
Example: prices.USD_US.11 > 0 AND prices.USD_US.11 < 100

Get all products with a price higher than 50 USD for size 9.5:

prices.USD_US.9.5 > 50

Get products matching barcodes:

barcodes IN ['193655590351', '884802676799']

Get products matching a specific SKU:

sku = 'CQ2514-005'

Complex queries with multiple operators:

(product_type = 'sneakers' OR category = 'Nike SB') AND (gender = 'men') AND (prices.EUR_FR.11 > 100 AND prices.EUR_FR.11 < 120)

Get products matching a specific category:

categories IN ['accessories']

It's recommended to use IN filter with categories instead of product_type or category. This offer a more detailed filtering.

Read about all operators here.

Writing queries for Shopify endpoints

Currently, the Shopify product model is structured as follows:

{
  "id": "string", // Generated by us, not the Shopify product ID
  "product_id": "number", // The Shopify product ID
  "title": "string",
  "description": "string",
  "slug": "string",
  "brand": "string",
  "product_type": "string",
  "sku": "string",
  "tags": ["string"],
  "prices": {
    "variant_title": "float" // variant_title -> variant price
  },
  "shop_name": "string",
  "barcodes": ["string"],
  "cursor": "number", // Used to paginate through the results
  "updated_at": "string",
  "published_at": "string"
}

This page will be updated whenever this structure changes. All fields are filterable, but only title, description, tags, slug, brand and sku are searchable.

Writing queries for GOAT endpoints

Currently, the GOAT product model is structured as follows:

{
  "id": "int",
  "name": "string",
  "brand": "string",
  "description": "string",
  "slug": "string",
  "sku": "string",
  "colorway": "string",
  "release_date": "string", // Format: YYYYMMDD or YYYY
  "retail_prices": { "retail_price_cents_<currency>": "number" }, // Example: "retail_price_cents_usd": 10000
  "rank": "number",
  "product_type": "string",
  "category": "string",
  "model": "string",
  "season": "string",
  "prices": {
    "<currency>": { "<size>": "float" } // Example: "usd": { "9": 123.45 }
    // if price == 0, it means the product is not available for sale
  }
}

This page will be updated whenever this structure changes. All fields are filterable, but only name, description, slug, brand and sku are searchable.

Writing queries for StockX endpoints#

Examples#

Writing queries for Shopify endpoints#

Writing queries for GOAT endpoints#

Writing queries for StockX endpoints

Examples

Writing queries for Shopify endpoints

Writing queries for GOAT endpoints