# Poshmark Scraper - Listings, Prices & Seller Data (`logiover/poshmark-scraper`) Actor Scrape Poshmark listings by keyword or URL. Extract title, brand, price, original price, size, color, condition, seller info, likes, shares, images, and more. No API key, no login required. - **URL**: https://apify.com/logiover/poshmark-scraper.md - **Developed by:** [Logiover](https://apify.com/logiover) (community) - **Categories:** E-commerce, AI, Automation - **Features:** Limited permissions - **Stats:** 1 total users, 0 monthly users, 100.0% runs succeeded, 0 bookmarks - **User rating**: No ratings yet ## Pricing from $3.50 / 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. Since this Actor supports Apify Store discounts, the price gets lower the higher subscription plan you have. 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 ## Poshmark Scraper Scrape Poshmark listings at scale by keyword or direct URL. Extract product titles, brands, prices, sizes, colors, seller profiles, engagement metrics, and images from poshmark.com without any API key or login. ### What does Poshmark Scraper do? Poshmark Scraper connects directly to Poshmark's internal data endpoints to pull structured listing data in bulk. It bypasses the browser-rendered frontend entirely and works with the server-side JSON API that powers poshmark.com, which means faster extraction and cleaner data compared to HTML-based scraping. The actor supports two input modes: keyword search (with full pagination up to 5,000 results per query) and direct listing URLs for targeted extraction. Every run outputs a flat, analysis-ready dataset with 24 fields covering product details, pricing history, seller identity, engagement metrics, and image CDN links. No API key, no login, no cookies required. Runs on datacenter proxies. Each request returns up to 48 listings per page, and the actor follows Poshmark's cursor-based pagination automatically until your configured limit is reached or results are exhausted. ### Who is it for? - **Resellers and flippers** who track pricing trends, brand demand, and competitive listings to optimize their own Poshmark closets. - **Market researchers** analyzing secondhand fashion pricing, brand popularity, and consumer demand across categories. - **E-commerce data teams** monitoring competitor inventory, pricing strategies, and product mix on the Poshmark marketplace. - **Brand analysts** tracking how specific brands perform in the resale market, including price decay from retail to secondhand. - **Academic researchers** studying circular fashion, resale economics, and consumer behavior in peer-to-peer marketplaces. ### Use cases - **Price benchmarking**: Search for a brand + category (e.g. "Nike Air Force 1") and extract current and original prices across hundreds of listings to compute average resale value and discount depth. - **Inventory monitoring**: Track daily snapshots of available listings for a product category to detect supply shifts, seasonal patterns, and new-listing velocity. - **Seller intelligence**: Extract seller usernames and engagement metrics (likes, shares, comments) to identify top-performing closets in a niche. - **Brand resale analysis**: Compare original retail prices against current asking prices to measure brand-level price retention in the secondhand market. - **Lead generation for consignment services**: Find high-volume sellers with large, active closets and extract their profile data for outreach. ### Why use Poshmark Scraper? - **No API key, no login**: Works out of the box. No Poshmark account, no OAuth, no cookies to manage. Fully keyless. - **24 structured fields**: Every listing comes with title, brand, price, original price, size, color, condition, category, department, seller info, engagement stats, images, style tags, and timestamps. - **Bulk extraction with pagination**: Each search query can return up to 5,000 listings via automatic cursor-based pagination. Feed multiple queries in a single run. - **Direct URL mode**: Pass specific listing URLs to extract full details for targeted items without running a broad search. - **Export to CSV, JSON, Excel**: Download your results from the Apify dataset tab in any format, or pipe them to Google Sheets, Slack, or your data warehouse via built-in integrations. - **Pay-per-result pricing**: You only pay for the compute time you use. No monthly subscription, no per-row surcharge. A typical run extracting 1,000 listings costs under $0.10. ### What data can you extract? The actor extracts 24 fields from each Poshmark listing. Every field is returned as a string for maximum compatibility with downstream tools. | Field | Type | Description | |-------|------|-------------| | id | string | Poshmark internal listing ID | | url | string | Full listing URL on poshmark.com | | title | string | Listing title | | brand | string | Brand name | | price | number | Current asking price | | originalPrice | number | Original retail price listed by seller | | currency | string | Currency code (typically USD) | | size | string | Item size (e.g. "M", "10", "XXS") | | colors | string | Comma-separated color names | | condition | string | Item condition if specified | | department | string | Department (Women, Men, Kids, Home, etc.) | | category | string | Category within department (Tops, Shoes, etc.) | | description | string | Full listing description text | | sellerUsername | string | Seller's Poshmark username | | sellerFullName | string | Seller's display name | | likeCount | number | Number of likes on the listing | | commentCount | number | Number of comments | | shareCount | number | Number of shares | | imageUrl | string | Primary listing image URL (full resolution) | | allImages | string | All image URLs separated by pipe character | | styleTags | string | Comma-separated style/trend tags | | status | string | Listing status (available, sold, etc.) | | createdAt | string | ISO timestamp when listing was created | | updatedAt | string | ISO timestamp of last update | #### Example JSON output ```json { "id": "6681fd21154600608f5cc74f", "url": "https://poshmark.com/listing/NEW-STINE-GOYA-SLEEVELESS-SEQUIN-TOP-6681fd21154600608f5cc74f", "title": "NEW STINE GOYA SLEEVELESS SEQUIN TOP", "brand": "STINE GOYA", "price": 99, "originalPrice": 300, "currency": "USD", "size": "XXS", "colors": "Green, Pink", "condition": null, "department": "Women", "category": "Tops", "description": "NEW STINE GOYA SLEEVELESS SEQUIN TOP\n\nNEW WITHOUT TAGS\n\nSIZE- XXS\n\nDETAIL:\n- Sleeveless\n- Crew neckline\n- Hidden back zipper close", "sellerUsername": "hideandchic", "sellerFullName": "H&C Luxury Consignment", "likeCount": 4, "commentCount": 0, "shareCount": 164, "imageUrl": "https://di2ponv0v5otw.cloudfront.net/posts/2024/06/30/6681fd21154600608f5cc74f/l_6681fd4007ac558dfc3d835c.jpg", "allImages": "https://di2ponv0v5otw.cloudfront.net/posts/2024/06/30/6681fd21154600608f5cc74f/l_6681fd4007ac558dfc3d835c.jpg | https://di2ponv0v5otw.cloudfront.net/posts/2024/06/30/6681fd21154600608f5cc74f/l_6681fd4907ac558dfc3d835d.jpg", "styleTags": "Revolve, Designer, Sequins", "status": "available", "createdAt": "2024-06-30T17:49:37-07:00", "updatedAt": "2026-09-08T14:46:58-07:00" } ``` ### How to use #### Option A: Search by keyword Use keyword search to find listings across all of Poshmark. The actor paginates automatically and pulls up to 5,000 results per query. 1. Go to the actor page on Apify Store and click **Try for free**. 2. Enter one or more search keywords in the **Search Keywords** field. 3. Set **Max Items** to control how many listings to extract per query. 4. Click **Start** and wait for the run to finish. 5. Download your data from the **Dataset** tab. ```json { "searchQueries": ["nike air force 1", "vintage levis"], "maxItems": 200 } ``` #### Option B: Scrape specific listing URLs If you already have Poshmark listing URLs, paste them directly to extract full details. 1. Click **Try for free** on the actor page. 2. Paste your listing URLs into the **Listing URLs** field (one per line). 3. Click **Start**. 4. Download results from the **Dataset** tab. ```json { "listingUrls": [ "https://poshmark.com/listing/Nike-Air-Force-1-Womens-Shoes-6aa076731ae1adbd246fb4a6", "https://poshmark.com/listing/Nike-Dunks-6a974b26946da28798e231af" ] } ``` You can combine both modes in a single run. ### Input parameters | Parameter | Type | Default | Description | |-----------|------|---------|-------------| | searchQueries | array | \[] | List of search keywords. Each query runs as a separate search with its own pagination. | | listingUrls | array | \[] | Direct Poshmark listing URLs. The actor extracts the listing ID from the URL automatically. | | maxItems | integer | 100 | Maximum items per search query. Set to 0 for the maximum (5,000). Does not apply to direct URLs. | | proxyConfig | object | {"useApifyProxy": true} | Proxy settings. Datacenter proxies are sufficient. | #### Full input example ```json { "searchQueries": ["designer handbag", "jordan retro"], "listingUrls": ["https://poshmark.com/listing/Nike-Shoes-6aa076731ae1adbd246fb4a6"], "maxItems": 500, "proxyConfig": { "useApifyProxy": true } } ``` ### Output example ```json { "id": "6a974b26946da28798e231af", "url": "https://poshmark.com/listing/Nike-Dunks-6a974b26946da28798e231af", "title": "Nike Dunks", "brand": "Nike", "price": 65, "originalPrice": 110, "currency": "USD", "size": "10", "colors": "White, Black", "condition": null, "department": "Men", "category": "Shoes", "description": "Nike Dunk Low in White/Black. Worn twice, excellent condition. Original box included.", "sellerUsername": "sneakerhead_joe", "sellerFullName": "Joe S.", "likeCount": 12, "commentCount": 2, "shareCount": 45, "imageUrl": "https://di2ponv0v5otw.cloudfront.net/posts/2026/08/15/6a974b26946da28798e231af/l_abc123.jpg", "allImages": "https://di2ponv0v5otw.cloudfront.net/posts/2026/08/15/6a974b26946da28798e231af/l_abc123.jpg | https://di2ponv0v5otw.cloudfront.net/posts/2026/08/15/6a974b26946da28798e231af/l_def456.jpg", "styleTags": "Sneakers, Streetwear", "status": "available", "createdAt": "2026-08-15T10:30:00-07:00", "updatedAt": "2026-09-01T08:15:00-07:00" } ``` ### Tips for best results - **Start with a small maxItems** (50-100) to test your query before running large extractions. This saves compute credits. - **Use specific search terms** rather than broad ones. "Nike Air Max 97 black" yields more relevant results than just "Nike". - **Combine multiple queries** in a single run to batch related searches efficiently. - **Monitor like counts and share counts** as engagement proxies for listing demand and seller activity. - **Compare price vs. originalPrice** to calculate discount percentages and identify underpriced items. - **Use the styleTags field** to discover trending categories and niche keywords for your own listings. - **Schedule regular runs** with Apify's built-in scheduler to track inventory changes and new listings over time. - **Filter by department/category** in your downstream analysis to segment data by Women, Men, Kids, or Home. - **Export to Google Sheets** for quick pivot tables and charts. The dataset integrates directly via the Apify Google Sheets connector. - **Check the status field** to distinguish between available, sold, and reserved listings in your analysis. ### Integrations Poshmark Scraper works with all standard Apify integrations: - **Google Sheets** — Automatically push results to a Google Sheet after each run. Perfect for tracking price changes over time. - **Slack** — Get notified in your Slack channel when a run completes, with a summary of items found. - **Zapier** — Connect the actor output to 5,000+ apps. Trigger workflows when new listings match your criteria. - **Make (Integromat)** — Build multi-step automations that process Poshmark data alongside other sources. - **Webhooks** — Receive a POST request with run metadata when the actor finishes. Use it to trigger your own pipeline. - **Schedule** — Run the actor on a schedule (hourly, daily, weekly) to monitor listings continuously. ### API usage #### cURL ```bash curl -X POST "https://api.apify.com/v2/acts/logiover~poshmark-scraper/runs?token=YOUR_TOKEN" \ -H "Content-Type: application/json" \ -d '{"searchQueries":["nike shoes"],"maxItems":100}' ``` #### Node.js ```javascript import { ApifyClient } from 'apify-client'; const client = new ApifyClient({ token: 'YOUR_TOKEN' }); const run = await client.actor('logiover/poshmark-scraper').call({ searchQueries: ['nike shoes'], maxItems: 100, }); const { items } = await client.dataset(run.defaultDatasetId).listItems(); console.log(items); ``` #### Python ```python from apify_client import ApifyClient client = ApifyClient("YOUR_TOKEN") run = client.actor("logiover/poshmark-scraper").call(run_input={ "searchQueries": ["nike shoes"], "maxItems": 100, }) items = list(client.dataset(run["defaultDatasetId"]).iterate_items()) print(f"Extracted {len(items)} listings") ``` ### 🤖 AI Agents, MCP & RAG Integration Poshmark Scraper is compatible with Apify's MCP (Model Context Protocol) server, which means you can call it directly from AI agents like Claude, ChatGPT, or custom LLM pipelines. Connect the Apify MCP server to your agent and ask it to run the actor with natural language prompts. Example prompt: *"Search Poshmark for 'vintage Levi's 501' and return the 50 cheapest listings with their prices and seller usernames."* Connect this Actor directly to **Apify AI**, **Claude Desktop**, **Cursor**, **VS Code**, **Windsurf**, **LangChain**, or **LlamaIndex** via the official **Apify MCP Server** — no custom wrapper code needed: ```json { "mcpServers": { "apify": { "type": "http", "url": "https://mcp.apify.com?tools=logiover/poshmark-scraper" } } } ``` - **Schema-typed inputs & outputs:** Clean JSON records with explicit `.actor/input_schema.json` and `.actor/output_schema.json` definitions so LLM agents infer parameters and parse fields accurately without HTML noise. - **Bounded & predictable runs:** Built-in volume caps and pay-per-result budget guards prevent runaway agent tool loops. - **RAG & automation ready:** Stream run datasets straight into vector stores, n8n, Make, Zapier, or webhook pipelines. ### FAQ #### Do I need a Poshmark account or API key? No. The actor works without any authentication. It accesses Poshmark's public-facing data endpoints that serve the website itself. No login, no API key, no cookies required. #### What data can I extract from Poshmark? You get 24 fields per listing: title, brand, price, original price, size, colors, condition, department, category, full description, seller username, seller name, likes, comments, shares, images, style tags, listing status, and timestamps. #### How many listings can I scrape per run? Each search query supports up to 5,000 results via automatic pagination. You can include multiple queries in a single run. Direct URL mode has no practical limit. #### Why am I getting zero results for my search? Poshmark may return zero results if the search term is too specific or misspelled. Try broader keywords. If you consistently get zero results, the search endpoint may be temporarily rate-limited; wait a few minutes and retry. #### Why are some fields null? Fields like `condition`, `styleTags`, or `sellerFullName` depend on what the seller provided when creating the listing. If the seller did not fill in a field, it will be null in the output. #### Can I export the data to CSV or Excel? Yes. After the run completes, go to the Dataset tab and click the download button. You can export as JSON, CSV, Excel, XML, or HTML. You can also push data directly to Google Sheets. #### How fast is the scraper? A typical run extracting 500 listings by search takes under 30 seconds. Direct URL mode processes about 5 listings per second with concurrency. Speed depends on your proxy configuration and Poshmark's response times. #### Is scraping Poshmark legal? This actor extracts publicly available data from poshmark.com. It does not bypass any authentication, CAPTCHA, or access control mechanisms. Users are responsible for complying with Poshmark's Terms of Service and applicable laws in their jurisdiction. See the legality section below. #### Can I scrape sold listings? The search API primarily returns available listings. Sold listings may appear in search results if recently sold. To check a specific sold listing, use the direct URL mode with the listing URL. #### How often is the data updated? The actor fetches live data from Poshmark on every run. Prices, availability, and engagement counts reflect the state at the moment of extraction. Schedule regular runs to track changes over time. #### What proxy should I use? Datacenter proxies work fine with Poshmark. The default Apify proxy configuration is sufficient. Residential proxies are not needed. #### Are there any related scrapers? Check the related scrapers section below for other e-commerce and marketplace scrapers by logiover. ### 💬 Support, Issues & Reviews - **Bug reports & target-site changes:** Hit an unexpected empty result or selector change? [Open a ticket in the Issues tab](https://apify.com/logiover/poshmark-scraper/issues) with your **Run ID** or sample input — we actively monitor issues and ship fixes fast. - **Feature & field requests:** Need an additional data attribute or filter? [Request it in the Issues tab](https://apify.com/logiover/poshmark-scraper/issues). - **Enjoying this Actor?** If it saved you engineering time, please consider leaving an honest [review on Apify Store](https://apify.com/logiover/poshmark-scraper/reviews) or bookmarking [logiover/poshmark-scraper](https://apify.com/logiover/poshmark-scraper) — organic developer feedback helps others discover reliable tools and keeps maintenance prioritized. ### Is it legal to scrape Poshmark? This actor accesses publicly visible listing data on poshmark.com. It does not log in, bypass CAPTCHAs, or circumvent any technical protection measures. The data extracted (product titles, prices, images, seller usernames) is the same information any visitor sees when browsing the site without an account. That said, web scraping exists in a legal gray area that varies by jurisdiction. Users are responsible for ensuring their use of this actor complies with Poshmark's Terms of Service, the Computer Fraud and Abuse Act (CFAA), GDPR, and any other applicable regulations. Apify provides the infrastructure; how you use the data is your responsibility. We recommend reviewing Poshmark's [Terms of Service](https://poshmark.com/terms) and [Privacy Policy](https://poshmark.com/privacy) before running large-scale extractions. This Actor is an independent tool. It is not affiliated with, endorsed by, or sponsored by Poshmark; Poshmark and all other trademarks mentioned here are the property of their respective owners. ### Related scrapers - [Amazon Scraper](https://apify.com/logiover/amazon-product-scraper) — Scrape product details, reviews, and pricing from Amazon. - [Mercari Scraper](https://apify.com/logiover/mercari-japan-scraper) — Extract listings and prices from Mercari marketplace. ### How much Poshmark data can you extract in one run? A single run returned **1,000 rows** in 253 seconds on the example input, and it was still going when the measurement stopped — raise the result limit and it keeps paginating. That is roughly **237 rows a minute**. There is no hard ceiling built into this Actor. What bounds a run is the result limit you set, the breadth of the input you give it, and how much Poshmark itself publishes. Because billing is per result, a wider run costs proportionally more and a narrow one costs almost nothing — so it is worth starting small and scaling once the output looks right. ### 📝 Changelog #### 2026-11-14 - Verified live production health run (2026-11-14): extracted **35** structured records in **9.0s** with valid schema output. - Hardened internal proxy stall fallback and pay-per-event dataset instance budget protection. #### 2026-11-11 - Added reliable terminal run status telemetry and structured Apify AI / MCP Server (`mcp.apify.com`) tool configuration. - Added direct Issues & Reviews support links and refreshed live maintenance verification. #### 2026-11-01 - Monthly health check (2026-11-01): a live run on the current build completed successfully and returned data. Input options, output fields and pricing are unchanged. - README refreshed: 2 links to renamed Actors updated, 2 links to retired Actors removed; independence disclaimer added. #### 2026-10-15 - Every request now has a hard time limit, so a proxy connection that stalls can no longer hold up the run or push it past its timeout. - A run that reaches its maximum cost per run now stops cleanly with its results saved and a status message, instead of ending as aborted. - A proxy group your account cannot use no longer stops the run at start-up; it falls back to the default Apify Proxy. - Memory is managed within the run's own limit, which removes a rare out-of-memory crash on large pages. - The prefilled example for `maxItems` is now 89 (was 100). - The default used when the field is left out for `maxItems` is now 4,743 (was 100). #### 2026-09-23 - Fleet-wide quality audit. Verified end to end against live data and re-checked the input schema, the output columns and the run configuration. - Output verified on a live run: 50 row(s) across 24 columns, 96.5% of cells populated. - Run reliability reviewed: 100.0% of public runs succeeded in the last 30 days. - Input schema, output schema and pricing configuration reviewed. # Changelog This Actor's version history is a separate document: https://apify.com/logiover/poshmark-scraper/changelog.md # Actor input Schema ## `searchQueries` (type: `array`): List of search keywords to scrape (e.g. 'nike shoes', 'vintage dress'). Leave empty if using listing URLs. The shipped example searches "nike sneakers" so a first run returns something. ## `listingUrls` (type: `array`): Direct Poshmark listing URLs to scrape (e.g. 'https://poshmark.com/listing/Nike-Shoes-abc123'). Leave empty if using search keywords. ## `maxItems` (type: `integer`): Maximum number of items to scrape per search query. Set 0 for unlimited (up to 5000). ## `proxyConfig` (type: `object`): Proxy settings. Datacenter proxies work fine with Poshmark. ## Actor input object example ```json { "searchQueries": [ "nike sneakers" ], "listingUrls": [], "maxItems": 89, "proxyConfig": { "useApifyProxy": true } } ``` # Actor output Schema ## `id` (type: `string`): No description ## `url` (type: `string`): No description ## `title` (type: `string`): No description ## `brand` (type: `string`): No description ## `price` (type: `string`): No description ## `originalPrice` (type: `string`): No description ## `currency` (type: `string`): No description ## `size` (type: `string`): No description ## `colors` (type: `string`): No description ## `condition` (type: `string`): No description ## `department` (type: `string`): No description ## `category` (type: `string`): No description ## `description` (type: `string`): No description ## `sellerUsername` (type: `string`): No description ## `sellerFullName` (type: `string`): No description ## `likeCount` (type: `string`): No description ## `commentCount` (type: `string`): No description ## `shareCount` (type: `string`): No description ## `imageUrl` (type: `string`): No description ## `allImages` (type: `string`): No description ## `styleTags` (type: `string`): No description ## `status` (type: `string`): No description ## `createdAt` (type: `string`): No description ## `updatedAt` (type: `string`): No description # 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 = { "searchQueries": [ "nike sneakers" ], "maxItems": 89 }; // Run the Actor and wait for it to finish const run = await client.actor("logiover/poshmark-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 = { "searchQueries": ["nike sneakers"], "maxItems": 89, } # Run the Actor and wait for it to finish run = client.actor("logiover/poshmark-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 '{ "searchQueries": [ "nike sneakers" ], "maxItems": 89 }' | apify call logiover/poshmark-scraper --silent --output-dataset ``` ## MCP server setup ```json { "mcpServers": { "apify": { "type": "http", "url": "https://mcp.apify.com/?tools=fetch-actor-details,logiover/poshmark-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/XCoDyfzzIFAoApTSd/builds/5UXdfMY9VLMT58MZ0/openapi.json