# Rakuma Scraper – Rakuten Flea Market Japan (楽天ラクマ) (`tokyo-select-jp/rakuma-search-scraper`) Actor Scrape Rakuma (fril.jp, 楽天ラクマ) — Rakuten's flea-market app, Japan's #2 C2C marketplace: fashion, brand bags, sneakers, hobby. Search by keyword, brand, category, price, condition, sold-out; get normalized size, condition rank, seller and images. JP Data Works series. - **URL**: https://apify.com/tokyo-select-jp/rakuma-search-scraper.md - **Developed by:** [JP Data Works](https://apify.com/tokyo-select-jp) (community) - **Stats:** 2 total users, 1 monthly users, 100.0% runs succeeded, 0 bookmarks - **User rating**: No ratings yet ## Pricing from $2.00 / 1,000 results This Actor is paid per event and usage. You are charged both the fixed price for specific events and for Apify platform usage. Learn more: https://docs.apify.com/actors/running/actors-in-store.md#pay-per-event ## What's an Apify Actor? An Actor is a serverless cloud program that runs on the Apify platform. It has two run modes. 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. Apify vocabulary and the platform model are defined once, in the agent quickstart at https://apify.com/agents.md. ## 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. Do not guess an integration path. Every one of them is in the agent quickstart at https://apify.com/agents.md: the Apify MCP server, Agent Skills with the Apify CLI, the JavaScript and Python clients, the REST API, and the account-free path for an agent with no human to sign in. It also carries the rule on stating cost before the first paid run. For examples already wired to this Actor's own input schema, see the [API](#api) section below. Each client library has reference documentation the quickstart does not restate: [JavaScript/TypeScript](https://docs.apify.com/api/client/js/docs.md) (`npm install apify-client`) and [Python](https://docs.apify.com/api/client/python/docs.md) (`pip install apify-client`). # README ## Rakuma Scraper – Rakuten Flea Market Japan (楽天ラクマ) Scrape **[Rakuma](https://fril.jp/) (楽天ラクマ)** — Rakuten's flea-market app and Japan's second-largest C2C marketplace after Mercari (tens of millions of listings: **fashion, brand bags and shoes, sneakers, cosmetics, hobby, kids**) — by **keyword, brand and category**, with **price, condition, sold-out and exclude-word filters**, and get clean JSON / CSV with **normalized size, condition rank (6–1), category path, seller and images**. Optionally open each item page for **condition, size, shipping, seller reviews, likes, description and the full gallery**. Part of the **JP Data Works** series of Japanese marketplace scrapers (Mercari, Yahoo! Fleamarket, KOMEHYO, Trefac, Vector Park …) that share one output shape so results can be merged. **Keywords:** Rakuma scraper · ラクマ スクレイピング · fril.jp · Rakuten flea market data · Japanese secondhand prices · sold listings price research · KAPITAL, visvim, Comme des Garçons, Supreme, Nike SB used · resale sourcing (eBay, Grailed, Depop, StockX) · price monitoring. ### What you get One row per listing: - `itemId`, `itemHash`, `url`, `title`, `brand`, `brandId` - `priceJpy`, `status` (`on_sale` / `sold`), `sizeRaw` / `sizeNorm` / `size` (`W32`, `L`, `JP3`, `26.5cm`, `FREE`) - `categoryId`, `categoryPath` (メンズ > ジャケット/アウター > Gジャン/デニムジャケット — from the listing card's leaf category), `categoryIds`, `gender` - `sellerId`, `imageUrl` / `imageUrls`, `fetchedAt`, `keyword`, `search` With **Enrich with item pages** each item additionally has `conditionRank` 6 (新品、未使用) … 1 (全体的に状態が悪い) and `conditionLabel`, `sizeRaw` from the item page, `shippingPayer` (seller 送料込 / buyer 着払い), `shippingMethod`, `shippingDuration`, `shippingFromArea`, `anonymousShipping`, `sellerName`, `shopName`, `shopHash`, `sellerReviews` (`{ good, neutral, bad }`), `likes`, `comments`, `description` and the full-size gallery. #### Example item (enriched) ```json { "source": "rakuma", "itemId": "862187021", "itemHash": "d61f0b0fcd51aaf40a346d015f3af984", "url": "https://item.fril.jp/d61f0b0fcd51aaf40a346d015f3af984", "title": "KAPITAL", "brand": "KAPITAL", "brandId": "1785", "priceJpy": 50000, "status": "on_sale", "sizeRaw": "L", "sizeNorm": { "kind": "alpha", "value": "L" }, "size": "L", "conditionRank": 3, "conditionLabel": "やや傷や汚れあり", "categoryId": 542, "categoryPath": "メンズ > ジャケット/アウター > Gジャン/デニムジャケット", "categoryIds": [10005, 539, 542], "gender": "mens", "sellerId": "17052770", "sellerName": "rkm0510", "shopHash": "ddb32042513b176103c3d77a30b5beb2", "shopName": "rkm0510's shop", "sellerReviews": { "good": 32, "neutral": 0, "bad": 0 }, "shippingPayer": "seller", "shippingMethod": "かんたんラクマパック(日本郵便)", "shippingDuration": "支払い後、4～7日で発送", "shippingFromArea": "静岡県", "anonymousShipping": true, "likes": 1, "comments": 0, "description": "ご覧いただきありがとうございます。\n\nストライプ柄フードとダブルブレストが特徴的なインディゴデニム素材のジャケットです。…", "imageUrl": "https://img.fril.jp/img/862187021/l/2990237096.jpg", "imageUrls": ["…/l/2990237096.jpg", "…/l/2990237088.jpg", "…/l/2990237184.jpg"], "fetchedAt": "2026-11-02T03:08:40.000Z", "detailFetchedAt": "2026-11-02T03:08:47.574Z", "keyword": "brand:KAPITAL#1785 メンズ>ジャケット/アウター ¥–60000", "search": { "label": "brand:KAPITAL#1785 メンズ>ジャケット/アウター ¥–60000", "mode": "brand_category", "brandId": "1785", "categoryId": 539, "categoryNames": ["メンズ", "ジャケット/アウター"], "priceMaxJpy": 60000, "status": "on_sale", "clientSideFilters": ["price ¥–60000", "status=on_sale"], "url": "https://fril.jp/brand/1785/category/539" } } ``` Without enrichment the detail fields are `null` and `imageUrls` holds the listing image, so the dataset always has the same columns. ### Output modes — listings or a market summary `outputMode` chooses what the dataset contains: - **`items`** (default) — one row per listing, as above. - **`summary`** — one **market-summary row per search** instead of the listings. The Actor still walks the search pages (up to `maxItemsPerSearch` listings, with `enrichDetail` if set), but stores only the aggregate — so a run that answers "what does X go for on Rakuma?" costs one `summary` event per search rather than hundreds of result events. - **`both`** — the listings plus the summary row. A summary row (`recordType: "summary"`) has the same shape in every JP Data Works Actor, so you can put several sites side by side: ```json { "recordType": "summary", "source": "rakuma", "search": { "label": "…", "url": "…", "…": "the resolved search parameters" }, "fetchedAt": "2026-11-02T03:00:00.000Z", "sampleSize": 180, "totalOnSite": 1243, "scanned": 190, "filteredOut": 10, "withDetail": 0, "status": { "on_sale": 180, "sold": 0, "unknown": 0 }, "price": { "count": 180, "min": 3300, "p25": 9800, "median": 16500, "mean": 19840, "p75": 25300, "max": 128000, "stddev": 15210 }, "priceOnSale": { "…": "same statistics for on-sale listings" }, "priceSold": { "…": "and for sold ones (sites that list them)" }, "priceHistogram": { "bucketJpy": 10000, "buckets": [ { "fromJpy": 0, "toJpy": 10000, "count": 46 }, "…" ] }, "conditionRank": { "6": 12, "5": 40, "4": 71, "3": 30, "unknown": 27 }, "conditionLabels": { "…": "the site's own labels" }, "sizes": { "M": 48, "L": 41, "W32": 12, "…": 0 }, "sizeKinds": { "alpha": 120, "waist": 30, "numeric": 20, "unknown": 10 }, "brands": { "KAPITAL": 180 }, "categories": { "メンズ > ジャケット/アウター": 95, "…": 0 }, "gender": { "mens": 170, "unknown": 10 }, "listed": { "last24h": 9, "last7d": 41, "last30d": 120 }, "sold": null, "cheapest": [ { "itemId": "…", "title": "…", "url": "…", "priceJpy": 3300, "conditionRank": 4, "size": "M", "status": "on_sale" }, "…" ], "cheapestGoodCondition": [ "… cheapest with condition rank ≥ 4 …" ], "newest": [ "… most recently listed (sites that expose listing times) …" ] } ``` Rakuma keeps sold listings in its catalogue, so with `status: "all"` the summary separates `priceOnSale` from `priceSold` — a quick asking-price vs sold-price comparison. The site exposes no listing time, so `listed` / `sold` are `null`. ### Input Two ways to describe what to search, which can be combined in one run: - **`keywords`** — simple: one search per keyword (`KAPITAL`, `リーバイス 501`, `Porter タンカー` …). - **`searches`** — structured: objects with any of `keyword`, `brand` / `brandId`, `categoryPath` / `categoryId`, `priceMinJpy`, `priceMaxJpy`, `conditionMin`, `status`, `excludeWords`, `sellerId`. Top-level `status`, `priceMinJpy`, `priceMaxJpy`, `conditionMin`, `excludeWords` are defaults for every keyword and search; a value inside a search wins. | Field | Type | Default | Notes | |---|---|---|---| | `keywords` | string\[] | — | One search per keyword. Optional when `searches` is given. | | `outputMode` | `items` | `summary` | `both` | `items` | Listings, one market-summary row per search, or both (see "Output modes"). | | `searches` | object\[] | — | Structured searches (table below). Each needs a keyword, brand or category. | | `status` | `on_sale` | `sold` | `all` | `on_sale` | `sold` = sold-out listings only, with their last price. | | `priceMinJpy` / `priceMaxJpy` | integer | none | Client-side (the site's price filter is robots-disallowed). | | `conditionMin` | 2–6 | none | Needs item pages → turns on `enrichDetail`. | | `excludeWords` | string\[] | `[]` | Client-side title filter. | | `maxItemsPerSearch` | integer | 100 | Per keyword / search. 40 cards per page, 100 pages max. | | `maxTotalItems` | integer | none | Hard cap per run. | | `dedupeAcrossSearches` | boolean | true | | | `enrichDetail` | boolean | false | One extra request + one `detail-page` event per item. | | `maxDetailPages` | integer | 100 | Cap on item-page requests per run. | | `requestDelayMs` | integer | 2000 | Minimum pause between requests. Please keep ≥ 2000. | | `proxyConfiguration` | object | none | Optional. Not needed under normal use. | | `outputFields` | string\[] | all | Keep only these fields (`itemId`, `url` always kept). | Fields of one `searches` entry (all optional): | Field | Example | How it is applied | |---|---|---| | `keyword` | `"KAPITAL デニム"` | Site keyword search (`/s?query=`), relevance order. | | `brand` | `"KAPITAL"`, `"COMME des GARCONS"` | Searched once as a keyword; the brand id is read from the result cards (one extra request per distinct brand). Unknown names are searched as a keyword and filtered by brand name client-side. | | `brandId` | `1785` | The site's brand id (`fril.jp/brand/`). 1785 = KAPITAL. | | `categoryPath` | `"mens"`, `"ladies"`, `"mens > jackets"`, `"mens > jackets > denim jacket"`, `"メンズ > パンツ > デニム/ジーンズ"`, `"ladies > バッグ"` | Top category (`mens`, `ladies`, `kids`, `cosmetics`, `hobby`, or the Japanese name) optionally followed by `>` and sub-category names as shown on the site (Japanese, or English for the common ones: tops, jackets, pants, shoes, bags, denim, sneakers, boots, knit, coat, dress, skirt …). The full tree (1,686 categories) is bundled. A name that exists under several parents (e.g. ジャケット/アウター) needs its parent. Unknown paths are used as an extra keyword. | | `categoryId` | `542` | The site's category id (`fril.jp/category/`). | | `priceMinJpy` / `priceMaxJpy` | `5000` / `30000` | **Client-side** from the card price. | | `conditionMin` | `4` | **Client-side after the item page**: 6 新品、未使用, 5 未使用に近い, 4 目立った傷や汚れなし, 3 やや傷や汚れあり, 2 傷や汚れあり. | | `status` | `"sold"` | `on_sale` (default), `sold`, `all` — from the card's SOLD OUT ribbon. | | `excludeWords` | `["ダメージ"]` | **Client-side**: drop items whose title contains any of these. | | `sellerId` | `"17052770"` | **Client-side**: keep only this seller's listings. | How the search is routed (robots.txt forbids combining a keyword with `brand_id=` / `category_id=`, so the Actor uses the page types it allows): | Input | Page crawled | Client-side | |---|---|---| | `keyword` only | `/s?query=&page=N` | — | | `keyword` + brand / category | `/s?query=&page=N` | cards filtered by the brand link / leaf category (and all its sub-categories) | | `brand` only | `/brand//page/N` | — | | `brand` + `category` | `/brand//category//page/N` | — | | `category` only | `/category//page/N` | — | #### Examples Sold KAPITAL jackets — what they actually went for (price research): ```json { "searches": [{ "brand": "KAPITAL", "categoryPath": "mens > jackets", "status": "sold" }], "maxItemsPerSearch": 200 } ``` Men's denim under ¥20,000 in good condition, with seller and shipping details: ```json { "searches": [{ "categoryPath": "mens > pants > denim", "priceMaxJpy": 20000, "conditionMin": 4 }], "maxItemsPerSearch": 100, "enrichDetail": true, "maxDetailPages": 100 } ``` Keyword within one brand (keyword search filtered by brand client-side): ```json { "searches": [{ "keyword": "センチュリーデニム", "brand": "KAPITAL", "status": "all" }], "maxItemsPerSearch": 100 } ``` Requests are strictly sequential: 100 listings ≈ 3 search pages ≈ 6 seconds; with `enrichDetail` ≈ 103 requests ≈ 3.5 minutes at the default delay (+1 request when brand names need to be resolved). #### Search URL parameters (how the filters map to fril.jp) Discovered from the site's search form, pager and robots.txt (2026-11-02): ``` https://fril.jp/s?query=KAPITAL&page=2 https://fril.jp/brand/1785/category/539/page/2 https://fril.jp/category/542/page/2 ``` | Actor field | Site URL | Notes | |---|---|---| | `keyword` | `/s?query=` | relevance order (the `sort=` parameter is robots-disallowed, so no newest-first) | | `brandId` | `/brand/` | brand page; `/brand//category/` for one category | | `categoryId` | `/category/` | 3-level tree: 10001 レディース, 10005 メンズ, 10003 キッズ/ベビー/マタニティ, 10004 コスメ/美容, 10007 エンタメ/ホビー, 10013 楽器, 10008 チケット … | | (pagination) | `?page=N` / `/page/N` | 40 cards per page, up to 100 pages | | price, condition, status, size | — | the site's `min=`, `max=`, `status=`, `size_id=`, `sort=`, `brand_id=`, `category_id=` query parameters are all robots-disallowed; the Actor never sends them and filters client-side instead | ### Pricing (pay per event) This Actor uses Apify's **pay-per-event** model. You only pay for what it produces: | Event | Charged when | Price | |---|---|---| | Result (`apify-default-dataset-item`, charged automatically by Apify) | one listing is saved to the dataset | $0.002 | | Detail page (`detail-page`) | that listing was enriched from its item page | $0.005 (in addition to the result) | | Market summary (`summary`) | one summary row is saved (outputMode `summary` / `both`) | $0.03 per search | | Actor start (`apify-actor-start`) | each run starts | $0.00005 | Example: 100 listings with detail ≈ 100 × $0.002 + 100 × $0.005 = **$0.70**. Without detail: **$0.20**. A `summary`-only run over 3 searches ≈ 3 × $0.03 = **$0.09**, whatever the number of listings sampled. Set **Max total charge** on the run to cap spending — the Actor stops cleanly when the limit is reached and you keep everything collected so far. ### FAQ **What is Rakuma?** Rakuma (楽天ラクマ, formerly Fril) is Rakuten's consumer-to-consumer flea-market app, Japan's second-largest after Mercari, with a strong fashion and brand-goods catalogue and lower seller fees — prices for the same item are often a little below Mercari. Listings are public at fril.jp; sold items stay visible with a SOLD OUT ribbon. **Why is there no "newest first" sort?** fril.jp's robots.txt disallows every URL carrying `sort=` (and the price / condition / size / brand / category query parameters). The Actor only requests the page types the site allows, so results come in the site's default order and all other filters run client-side on the listing cards. For new-arrival monitoring, schedule the Actor and diff `itemId` against the previous run. **Can I get sold items?** Yes — `status: "sold"` returns sold-out listings with their last price (listings stay in the catalogue after sale), which makes Rakuma a good source for "what did it actually sell for". Sold item pages no longer show the condition and size table, so `conditionRank` is usually `null` for them even with enrichment. **Do I need a proxy?** No. The site serves the listing and item pages to Apify's datacenter IPs at the default 2-second delay. `proxyConfiguration` is there if you need it. **How are sizes and conditions normalized?** `sizeRaw` keeps the site text (item page) or the size found in the title; `sizeNorm` interprets it (`waist` inches for `W32`, `alpha` for `S/M/L/LL→XL`, `numeric` for JP sizes such as `3`, `cm` for shoes, `free`). `conditionRank` uses 6 = best … 1 = worst — the same scale as our Mercari, Yahoo! Fleamarket, KOMEHYO, Trefac and Vector Park scrapers, so results from several Actors can be merged; `conditionLabel` keeps Rakuma's own wording. **Is this legal?** The Actor collects public listing data only — no login, no purchases, no personal data beyond the public seller name — obeys robots.txt (including the disallowed query parameters) and throttles requests. How you use the data is your responsibility; respect the site's terms of use, keep runs small and scheduled, and do not republish its photos or texts as your own. **How do I call it from code or from an AI agent?** Any Apify client works. With the JavaScript client: ```js import { ApifyClient } from "apify-client"; const client = new ApifyClient({ token: process.env.APIFY_TOKEN }); const run = await client.actor("tokyo-select-jp/rakuma-search-scraper").call({ searches: [{ brand: "KAPITAL", categoryPath: "mens > jackets", status: "sold" }], maxItemsPerSearch: 100, }); const { items } = await client.dataset(run.defaultDatasetId).listItems(); ``` or with plain HTTP (`run-sync-get-dataset-items` returns the results directly): ``` POST https://api.apify.com/v2/acts/tokyo-select-jp~rakuma-search-scraper/run-sync-get-dataset-items?token=YOUR_TOKEN Content-Type: application/json { "keywords": ["visvim"], "maxItemsPerSearch": 50 } ``` # Changelog This Actor's version history is a separate document: https://apify.com/tokyo-select-jp/rakuma-search-scraper/changelog.md # Actor input Schema ## `keywords` (type: `array`): Simple keyword searches, one per line — brand names, item types, model numbers, Japanese or English (e.g. `KAPITAL`, `リーバイス 501`, `Porter タンカー`). Each keyword is one search and inherits the defaults below. Optional when `searches` is set. ## `searches` (type: `array`): Advanced searches as JSON objects. Every field is optional, but each search needs at least one of `keyword`, `brand`, `brandId`, `categoryPath`, `categoryId`. - `keyword` — free text (site keyword search). - `brand` — brand name as listed on Rakuma (e.g. `KAPITAL`, `COMME des GARCONS`); resolved to the site's brand id through one keyword search. `brandId` — that id directly (1785 = KAPITAL). - `categoryPath` — `mens`, `ladies`, `kids`, or a path such as `mens > jackets`, `メンズ > パンツ > デニム/ジーンズ`, `ladies > バッグ`; `categoryId` — the site's category id (542 = メンズ > ジャケット/アウター > Gジャン/デニムジャケット). - `priceMinJpy` / `priceMaxJpy` — price bounds (client-side; the site's price filter is robots-disallowed). - `conditionMin` — minimum condition rank 2–6 (6 = 新品、未使用, 5 = 未使用に近い, 4 = 目立った傷や汚れなし, 3 = やや傷や汚れあり, 2 = 傷や汚れあり). Needs the item page, so it turns on enrichDetail. - `status` — `on_sale` (default), `sold` (sold-out listings only — price research), `all`. - `excludeWords` — drop items whose title contains any of these (client-side). - `sellerId` — keep only one seller's items (client-side). A keyword combined with a brand or category runs the keyword search and filters the cards by brand / category client-side (the site's brand_id / category_id query parameters are robots-disallowed). Without a keyword the brand page, brand × category page or category page is crawled directly. Values set here override the defaults below. ## `outputMode` (type: `string`): `items` (default): one dataset row per listing. `summary`: one market-summary row per search instead of the listings — sample size, price min / p25 / median / mean / p75 / max, price histogram, status / condition-rank / size / brand / category breakdowns, cheapest listings — billed once per search as the `summary` event (the sampled listings are not billed). `both`: listings plus the summary row. ## `status` (type: `string`): Applied to every search without its own `status`. `sold` returns sold-out listings with their last price (price research); the site shows them in the same listing. ## `priceMinJpy` (type: `integer`): Lower price bound for every search without its own `priceMinJpy` (client-side). ## `priceMaxJpy` (type: `integer`): Upper price bound for every search without its own `priceMaxJpy` (client-side). ## `conditionMin` (type: `integer`): Only listings with this condition rank or better: 6 新品、未使用, 5 未使用に近い, 4 目立った傷や汚れなし, 3 やや傷や汚れあり, 2 傷や汚れあり. The condition is only on the item page, so this turns on item-page enrichment. Leave empty for all. ## `excludeWords` (type: `array`): Drop items whose title contains any of these words (case-insensitive). ## `maxItemsPerSearch` (type: `integer`): Stop after this many listings for each keyword / search. The site shows 40 listings per page, up to 100 pages. ## `maxTotalItems` (type: `integer`): Hard cap on listings saved in this run across all searches. Leave empty for no cap (Max total charge still applies). ## `dedupeAcrossSearches` (type: `boolean`): Save a listing only once when several searches return it. ## `enrichDetail` (type: `boolean`): Open each item page for condition, size, shipping (payer, method, days, prefecture), seller (name, shop, review counts), likes, comments, description, full category path and the full-size gallery. One extra request and one `detail-page` event per item. ## `maxDetailPages` (type: `integer`): Cap on item-page requests per run. Items beyond the cap are returned without detail fields. ## `requestDelayMs` (type: `integer`): Minimum pause between requests. Please keep ≥ 2000. ## `proxyConfiguration` (type: `object`): Optional Apify Proxy or your own proxies. Not needed under normal use. ## `outputFields` (type: `array`): Keep only these top-level fields in the output (`itemId` and `url` are always kept). Leave empty for all fields. ## Actor input object example ```json { "keywords": [ "KAPITAL" ], "searches": [ { "brand": "KAPITAL", "categoryPath": "mens > jackets", "priceMaxJpy": 30000 } ], "outputMode": "items", "status": "on_sale", "excludeWords": [], "maxItemsPerSearch": 100, "dedupeAcrossSearches": true, "enrichDetail": false, "maxDetailPages": 100, "requestDelayMs": 2000, "proxyConfiguration": { "useApifyProxy": false }, "outputFields": [] } ``` # Actor output Schema ## `listings` (type: `string`): All scraped items (default dataset) # 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 = { "keywords": [ "KAPITAL" ], "searches": [ { "brand": "KAPITAL", "categoryPath": "mens > jackets", "priceMaxJpy": 30000 } ], "maxItemsPerSearch": 100, "proxyConfiguration": { "useApifyProxy": false } }; // Run the Actor and wait for it to finish const run = await client.actor("tokyo-select-jp/rakuma-search-scraper").call(input); // Fetch and print Actor results from the run's dataset (if any) console.log('Results from dataset'); console.log(`💾 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); }); // 📚 Want to learn more 📖? Go to → 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 = { "keywords": ["KAPITAL"], "searches": [{ "brand": "KAPITAL", "categoryPath": "mens > jackets", "priceMaxJpy": 30000, }], "maxItemsPerSearch": 100, "proxyConfiguration": { "useApifyProxy": False }, } # Run the Actor and wait for it to finish run = client.actor("tokyo-select-jp/rakuma-search-scraper").call(run_input=run_input) # Fetch and print Actor results from the run's dataset (if there are any) print(f"💾 Check your data here: https://console.apify.com/storage/datasets/{run.default_dataset_id}") for item in client.dataset(run.default_dataset_id).iterate_items(): print(item) # 📚 Want to learn more 📖? Go to → https://docs.apify.com/api/client/python/docs/quick-start ``` ## CLI example ```bash echo '{ "keywords": [ "KAPITAL" ], "searches": [ { "brand": "KAPITAL", "categoryPath": "mens > jackets", "priceMaxJpy": 30000 } ], "maxItemsPerSearch": 100, "proxyConfiguration": { "useApifyProxy": false } }' | apify call tokyo-select-jp/rakuma-search-scraper --silent --output-dataset ``` ## MCP server setup ```json { "mcpServers": { "apify": { "type": "http", "url": "https://mcp.apify.com/?tools=fetch-actor-details,tokyo-select-jp/rakuma-search-scraper" } } } ``` The hosted server signs you in with OAuth on first connect, so no API token belongs in this config. Clients without OAuth support can send an `Authorization: Bearer ` header instead, using a token from API & Integrations in Apify Console (https://console.apify.com/settings/integrations). ## OpenAPI specification Download the OpenAPI definition: https://api.apify.com/v2/actors/SOisCfn6MOaGnXekB/builds/MRBUeU2Y4HbPYSnQY/openapi.json