# Musinsa Product Scraper (`kdatafactory/musinsa-scraper`) Actor Scrape ranked and searched fashion products from Musinsa (musinsa.com), Korea's #1 fashion marketplace. JSON API first, HTML fallback. - **URL**: https://apify.com/kdatafactory/musinsa-scraper.md - **Developed by:** [Seok June Park](https://apify.com/kdatafactory) (community) - **Categories:** E-commerce, Automation, Other - **Stats:** 2 total users, 0 monthly users, 100.0% runs succeeded, 0 bookmarks - **User rating**: No ratings yet ## Pricing from $3.00 / 1,000 results This Actor is paid per event. You are not charged for the Apify platform usage, but only a fixed price for specific events. Learn more: https://docs.apify.com/platform/actors/running/actors-in-store#pay-per-event ## What's an Apify Actor? Actors are a software tools running on the Apify platform, for all kinds of web data extraction and automation use cases. In Batch mode, an Actor accepts a well-defined JSON input, performs an action which can take anything from a few seconds to a few hours, and optionally produces a well-defined JSON output, datasets with results, or files in key-value store. In Standby mode, an Actor provides a web server which can be used as a website, API, or an MCP server. Actors are written with capital "A". ## How to integrate an Actor? If asked about integration, you help developers integrate Actors into their projects. You adapt to their stack and deliver integrations that are safe, well-documented, and production-ready. The best way to integrate Actors is as follows. In JavaScript/TypeScript projects, use official [JavaScript/TypeScript client](https://docs.apify.com/api/client/js.md): ```bash npm install apify-client ``` In Python projects, use official [Python client library](https://docs.apify.com/api/client/python.md): ```bash pip install apify-client ``` In shell scripts, use [Apify CLI](https://docs.apify.com/cli/docs.md): ````bash # MacOS / Linux curl -fsSL https://apify.com/install-cli.sh | bash # Windows irm https://apify.com/install-cli.ps1 | iex ```bash In AI frameworks, you might use the [Apify MCP server](https://docs.apify.com/platform/integrations/mcp.md). If your project is in a different language, use the [REST API](https://docs.apify.com/api/v2.md). For usage examples, see the [API](#api) section below. For more details, see Apify documentation as [Markdown index](https://docs.apify.com/llms.txt) and [Markdown full-text](https://docs.apify.com/llms-full.txt). # README ## Musinsa Product Scraper πŸ›οΈ Scrape **ranked** and **searched** fashion products from [Musinsa](https://www.musinsa.com) β€” Korea's #1 online fashion marketplace β€” as clean, structured JSON. Get product names, brands, prices, discounts, ratings, review counts, and images in one call. Built for **K-fashion trend research**, **dropshipping product sourcing**, and **price monitoring**. --- ### What it does This actor pulls product data directly from Musinsa's public product-list JSON API (the same one that powers musinsa.com), so results are fast and complete β€” no fragile HTML scraping in the happy path. Two modes: - **Ranking** β€” the popularity-ranked products for a Musinsa category (e.g. Tops, Outerwear, Shoes). Each item includes its `rank`. - **Search** β€” every product matching a keyword (e.g. `nike`, `맨투맨`, `cardigan`). If the JSON API is ever unavailable, the actor automatically falls back to extracting the product list from the page's embedded `__NEXT_DATA__` payload. --- ### Input | Field | Type | Description | |-------|------|-------------| | `mode` | string | `"ranking"` or `"search"`. | | `query` | string | **Search mode:** a keyword. **Ranking mode:** a Musinsa category code (see below). Defaults to `001` (Tops) in ranking mode. | | `gender` | string | `"A"` (all), `"M"` (men), or `"F"` (women). Default `A`. | | `maxItems` | integer | Max products to collect. Default `100`. | #### Common category codes (ranking mode) | Code | Category | |------|----------| | `001` | Tops | | `002` | Outerwear | | `003` | Pants | | `100` | Bags | | `104` | Shoes | You can also use full 6-digit leaf codes (e.g. `001001` = short-sleeve tees) taken from the category menu on musinsa.com. #### Input example ```json { "mode": "ranking", "query": "001", "gender": "A", "maxItems": 100 } ```` ```json { "mode": "search", "query": "nike", "gender": "M", "maxItems": 200 } ``` *** ### Output Each product is one dataset record. Prices are in KRW (Korean won). `rating` is normalized to a 0–5 scale. `rank` and `category` are only populated in ranking mode. ```json { "source": "musinsa", "product_id": "6543427", "name": "μ›Œμ…”λΈ” 헨리λ„₯ 크둭 λ°˜νŒ” μΏ¨ λ‹ˆνŠΈ ( 5Color )", "brand": "브렌슨", "price_krw": 47400, "sale_price_krw": 37900, "rating": 4.9, "review_count": 31, "category": "001", "rank": 1, "url": "https://www.musinsa.com/products/6543427", "image_url": "https://image.msscdn.net/images/goods_img/20260526/6543427/6543427_17811581686328_500.jpg", "scraped_at": "2026-07-07T09:21:25+09:00" } ``` A full 40-item sample from a real run is in [`samples/sample-output.json`](samples/sample-output.json). | Field | Meaning | |-------|---------| | `source` | Always `"musinsa"`. | | `product_id` | Musinsa goods number. | | `name` | Product name. | | `brand` | Brand display name. | | `price_krw` | Original/list price (KRW). | | `sale_price_krw` | Discounted price if on sale, else `null`. | | `rating` | Review score, 0–5. | | `review_count` | Number of reviews. | | `category` | Category code (ranking mode only). | | `rank` | Popularity rank (ranking mode only). | | `url` | Product page URL. | | `image_url` | Thumbnail image URL. | | `scraped_at` | ISO-8601 timestamp (KST, UTC+9). | *** ### Use cases - **K-fashion trend research** β€” track which brands, silhouettes, and price points are climbing the Musinsa popularity rankings week over week. - **Dropshipping / product sourcing** β€” build a catalog of trending Korean fashion products with images, brands, and prices to source or resell. - **Price & discount monitoring** β€” watch `price_krw` vs `sale_price_krw` over time to catch drops and benchmark competitor pricing. - **AI agents & datasets** β€” feed structured fashion data into recommendation models, market dashboards, or LLM agents. *** ### Rate limiting & legality - The actor collects **only public, non-authenticated data**. It never logs in and never touches private endpoints. - **No personal data** is collected β€” no reviewer names, profiles, or IDs. (Individual review text is not scraped by this actor.) - Requests are rate-limited: one page at a time with a β‰₯ 500 ms delay between requests, to stay gentle on Musinsa's servers. - You are responsible for using the data in line with Musinsa's terms of service and applicable law. #### ⚠️ Proxy recommendation Musinsa may block datacenter IPs or high request volumes. For reliable runs β€” especially at higher `maxItems` β€” enable **Apify Proxy with the `RESIDENTIAL` group**. The actor automatically uses the proxy configuration you provide (via `proxyConfiguration` in input) and runs direct when none is set. If you see repeated `API HTTP 403/429` errors in the log, switch on residential proxy. # Actor input Schema ## `mode` (type: `string`): What to scrape. 'ranking' returns the popularity-ranked products for a category. 'search' returns products matching a keyword. ## `query` (type: `string`): For 'search' mode: a keyword (e.g. 'nike', '맨투맨'). For 'ranking' mode: a Musinsa category code (e.g. '001' Tops, '002' Outer, '003' Pants, '100' Bags, '104' Shoes). Leave blank in ranking mode to default to '001' (Tops). ## `gender` (type: `string`): Gender filter for the product feed. ## `maxItems` (type: `integer`): Maximum number of products to collect. ## Actor input object example ```json { "mode": "ranking", "query": "001", "gender": "A", "maxItems": 100 } ``` # API You can run this Actor programmatically using our API. Below are code examples in JavaScript, Python, and CLI, as well as the OpenAPI specification and MCP server setup. ## JavaScript example ```javascript import { ApifyClient } from 'apify-client'; // Initialize the ApifyClient with your Apify API token // Replace the '' with your token const client = new ApifyClient({ token: '', }); // Prepare Actor input const input = {}; // Run the Actor and wait for it to finish const run = await client.actor("kdatafactory/musinsa-scraper").call(input); // Fetch and print Actor results from the run's dataset (if any) console.log('Results from dataset'); console.log(`πŸ’Ύ Check your data here: https://console.apify.com/storage/datasets/${run.defaultDatasetId}`); const { items } = await client.dataset(run.defaultDatasetId).listItems(); items.forEach((item) => { console.dir(item); }); // πŸ“š Want to learn more πŸ“–? Go to β†’ https://docs.apify.com/api/client/js/docs ``` ## Python example ```python from apify_client import ApifyClient # Initialize the ApifyClient with your Apify API token # Replace '' with your token. client = ApifyClient("") # Prepare the Actor input run_input = {} # Run the Actor and wait for it to finish run = client.actor("kdatafactory/musinsa-scraper").call(run_input=run_input) # Fetch and print Actor results from the run's dataset (if there are any) print("πŸ’Ύ Check your data here: https://console.apify.com/storage/datasets/" + run["defaultDatasetId"]) for item in client.dataset(run["defaultDatasetId"]).iterate_items(): print(item) # πŸ“š Want to learn more πŸ“–? Go to β†’ https://docs.apify.com/api/client/python/docs/quick-start ``` ## CLI example ```bash echo '{}' | apify call kdatafactory/musinsa-scraper --silent --output-dataset ``` ## MCP server setup ```json { "mcpServers": { "apify": { "command": "npx", "args": [ "mcp-remote", "https://mcp.apify.com/?tools=kdatafactory/musinsa-scraper", "--header", "Authorization: Bearer " ] } } } ``` ## OpenAPI specification ```json { "openapi": "3.0.1", "info": { "title": "Musinsa Product Scraper", "description": "Scrape ranked and searched fashion products from Musinsa (musinsa.com), Korea's #1 fashion marketplace. JSON API first, HTML fallback.", "version": "0.1", "x-build-id": "fuDxXm3AELr05kOHI" }, "servers": [ { "url": "https://api.apify.com/v2" } ], "paths": { "/acts/kdatafactory~musinsa-scraper/run-sync-get-dataset-items": { "post": { "operationId": "run-sync-get-dataset-items-kdatafactory-musinsa-scraper", "x-openai-isConsequential": false, "summary": "Executes an Actor, waits for its completion, and returns Actor's dataset items in response.", "tags": [ "Run Actor" ], "requestBody": { "required": true, "content": { "application/json": { "schema": { "$ref": "#/components/schemas/inputSchema" } } } }, "parameters": [ { "name": "token", "in": "query", "required": true, "schema": { "type": "string" }, "description": "Enter your Apify token here" } ], "responses": { "200": { "description": "OK" } } } }, "/acts/kdatafactory~musinsa-scraper/runs": { "post": { "operationId": "runs-sync-kdatafactory-musinsa-scraper", "x-openai-isConsequential": false, "summary": "Executes an Actor and returns information about the initiated run in response.", "tags": [ "Run Actor" ], "requestBody": { "required": true, "content": { "application/json": { "schema": { "$ref": "#/components/schemas/inputSchema" } } } }, "parameters": [ { "name": "token", "in": "query", "required": true, "schema": { "type": "string" }, "description": "Enter your Apify token here" } ], "responses": { "200": { "description": "OK", "content": { "application/json": { "schema": { "$ref": "#/components/schemas/runsResponseSchema" } } } } } } }, "/acts/kdatafactory~musinsa-scraper/run-sync": { "post": { "operationId": "run-sync-kdatafactory-musinsa-scraper", "x-openai-isConsequential": false, "summary": "Executes an Actor, waits for completion, and returns the OUTPUT from Key-value store in response.", "tags": [ "Run Actor" ], "requestBody": { "required": true, "content": { "application/json": { "schema": { "$ref": "#/components/schemas/inputSchema" } } } }, "parameters": [ { "name": "token", "in": "query", "required": true, "schema": { "type": "string" }, "description": "Enter your Apify token here" } ], "responses": { "200": { "description": "OK" } } } } }, "components": { "schemas": { "inputSchema": { "type": "object", "required": [ "mode" ], "properties": { "mode": { "title": "Mode", "enum": [ "ranking", "search" ], "type": "string", "description": "What to scrape. 'ranking' returns the popularity-ranked products for a category. 'search' returns products matching a keyword.", "default": "ranking" }, "query": { "title": "Query", "type": "string", "description": "For 'search' mode: a keyword (e.g. 'nike', '맨투맨'). For 'ranking' mode: a Musinsa category code (e.g. '001' Tops, '002' Outer, '003' Pants, '100' Bags, '104' Shoes). Leave blank in ranking mode to default to '001' (Tops).", "default": "001" }, "gender": { "title": "Gender filter", "enum": [ "A", "M", "F" ], "type": "string", "description": "Gender filter for the product feed.", "default": "A" }, "maxItems": { "title": "Max items", "minimum": 1, "maximum": 5000, "type": "integer", "description": "Maximum number of products to collect.", "default": 100 } } }, "runsResponseSchema": { "type": "object", "properties": { "data": { "type": "object", "properties": { "id": { "type": "string" }, "actId": { "type": "string" }, "userId": { "type": "string" }, "startedAt": { "type": "string", "format": "date-time", "example": "2025-01-08T00:00:00.000Z" }, "finishedAt": { "type": "string", "format": "date-time", "example": "2025-01-08T00:00:00.000Z" }, "status": { "type": "string", "example": "READY" }, "meta": { "type": "object", "properties": { "origin": { "type": "string", "example": "API" }, "userAgent": { "type": "string" } } }, "stats": { "type": "object", "properties": { "inputBodyLen": { "type": "integer", "example": 2000 }, "rebootCount": { "type": "integer", "example": 0 }, "restartCount": { "type": "integer", "example": 0 }, "resurrectCount": { "type": "integer", "example": 0 }, "computeUnits": { "type": "integer", "example": 0 } } }, "options": { "type": "object", "properties": { "build": { "type": "string", "example": "latest" }, "timeoutSecs": { "type": "integer", "example": 300 }, "memoryMbytes": { "type": "integer", "example": 1024 }, "diskMbytes": { "type": "integer", "example": 2048 } } }, "buildId": { "type": "string" }, "defaultKeyValueStoreId": { "type": "string" }, "defaultDatasetId": { "type": "string" }, "defaultRequestQueueId": { "type": "string" }, "buildNumber": { "type": "string", "example": "1.0.0" }, "containerUrl": { "type": "string" }, "usage": { "type": "object", "properties": { "ACTOR_COMPUTE_UNITS": { "type": "integer", "example": 0 }, "DATASET_READS": { "type": "integer", "example": 0 }, "DATASET_WRITES": { "type": "integer", "example": 0 }, "KEY_VALUE_STORE_READS": { "type": "integer", "example": 0 }, "KEY_VALUE_STORE_WRITES": { "type": "integer", "example": 1 }, "KEY_VALUE_STORE_LISTS": { "type": "integer", "example": 0 }, "REQUEST_QUEUE_READS": { "type": "integer", "example": 0 }, "REQUEST_QUEUE_WRITES": { "type": "integer", "example": 0 }, "DATA_TRANSFER_INTERNAL_GBYTES": { "type": "integer", "example": 0 }, "DATA_TRANSFER_EXTERNAL_GBYTES": { "type": "integer", "example": 0 }, "PROXY_RESIDENTIAL_TRANSFER_GBYTES": { "type": "integer", "example": 0 }, "PROXY_SERPS": { "type": "integer", "example": 0 } } }, "usageTotalUsd": { "type": "number", "example": 0.00005 }, "usageUsd": { "type": "object", "properties": { "ACTOR_COMPUTE_UNITS": { "type": "integer", "example": 0 }, "DATASET_READS": { "type": "integer", "example": 0 }, "DATASET_WRITES": { "type": "integer", "example": 0 }, "KEY_VALUE_STORE_READS": { "type": "integer", "example": 0 }, "KEY_VALUE_STORE_WRITES": { "type": "number", "example": 0.00005 }, "KEY_VALUE_STORE_LISTS": { "type": "integer", "example": 0 }, "REQUEST_QUEUE_READS": { "type": "integer", "example": 0 }, "REQUEST_QUEUE_WRITES": { "type": "integer", "example": 0 }, "DATA_TRANSFER_INTERNAL_GBYTES": { "type": "integer", "example": 0 }, "DATA_TRANSFER_EXTERNAL_GBYTES": { "type": "integer", "example": 0 }, "PROXY_RESIDENTIAL_TRANSFER_GBYTES": { "type": "integer", "example": 0 }, "PROXY_SERPS": { "type": "integer", "example": 0 } } } } } } } } } } ```