# Poshmark Search Scraper (`xtracto/poshmark-search-scraper`) Actor Search Poshmark for any keyword and get clean resale listings with price, brand, size, condition, seller, and photos. - **URL**: https://apify.com/xtracto/poshmark-search-scraper.md - **Developed by:** [Farhan Febrian Nauval](https://apify.com/xtracto) (community) - **Categories:** E-commerce, Lead generation - **Stats:** 2 total users, 1 monthly users, 100.0% runs succeeded, 0 bookmarks - **User rating**: No ratings yet ## Pricing from $20.00 / 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. Since this Actor supports Apify Store discounts, the price gets lower the higher subscription plan you have. 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 ## Poshmark Search Scraper Search [Poshmark](https://poshmark.com/) for any keyword and get clean resale listings — title, price, brand, size, condition, colors, seller, and photos — as structured JSON. ### Why use this actor - **Resale market research at scale** — pull live listings for any brand, item, or keyword and track pricing across the marketplace. - **Real resale pricing** — captures the asking price (and the original/retail price when the seller set one) for every listing. - **Rich listing detail** — brand, size, condition (e.g. *New with tags*, *Like new*, *Good*), department, category, and colors for each item. - **Seller and engagement signals** — the seller's username and handle plus like and comment counts on every listing. - **All the photos** — every listing photo as a ready-to-use image URL. - **No account, no API key** — works straight from public search results. - **Stable JSON output** — the same field names every run, ready for spreadsheets, databases, or pipelines. ### How it works 1. You provide one or more search keywords and a sort order. 2. The actor pulls the search results for each keyword across as many pages as you allow (about 40 listings per page). 3. Each item is saved as a `LISTING` record with its price, brand, size, condition, seller, and photos. 4. If a keyword returns nothing, the actor still writes one diagnostic record so a query is never silently dropped. 5. Everything lands in your dataset, exportable as JSON, CSV, or Excel. You don't need to manage any browsers or scrapers. ### Input ```json { "queries": [ "coach bag", "nike air max" ], "maxPagesPerQuery": 3, "sortBy": "added_desc", "maxConcurrency": 4, "maxRequestRetries": 5, "proxyConfiguration": { "useApifyProxy": true } } ```` Each keyword in `queries` is searched independently and produces its own set of `LISTING` records. | Field | Type | Description | | --- | --- | --- | | `queries` | array | **Required.** Keywords to search (one per array entry). Each keyword yields its own listings. | | `maxPagesPerQuery` | integer | Pages of results per query, ~40 listings/page (`1`–`50`). Stops early when a query runs out of results. Default `3`. | | `sortBy` | string | Result order: `added_desc` (Newest), `price_asc` (Price: Low to High), `price_desc` (Price: High to Low), `like_count` (Most Loved). Default `added_desc`. | | `maxConcurrency` | integer | Number of parallel requests across all keywords (`1`–`20`). Default `4`. | | `maxRequestRetries` | integer | Retries per page before giving up (`1`–`15`). Default `5`. | | `proxyConfiguration` | object | Apify Proxy or a custom proxy list. Datacenter proxies work fine for this source. | ### Output Each listing is one record (`recordType: "LISTING"`): ```json { "recordType": "LISTING", "query": "coach bag", "id": "6a18787a7ddf562f464583a0", "title": "Vintage Coach Julia OP Tote Bag/ Vintage Coach Bags Y2K Vintage Coach", "url": "https://poshmark.com/listing/6a18787a7ddf562f464583a0", "price": 125.0, "currency": "USD", "originalPrice": null, "size": "One Size", "brand": "Coach", "condition": "Good", "newWithTags": false, "department": "Women", "category": "Bags", "colors": [ "Gray", "Purple" ], "sellerUsername": "myclosetlaurie", "sellerHandle": "myclosetlaurie", "images": [ "https://di2ponv0v5otw.cloudfront.net/posts/2026/05/28/6a18787a7ddf562f464583a0/m_6a18787d21bd4295939a39b0.jpeg", "https://di2ponv0v5otw.cloudfront.net/posts/2026/05/28/6a18787a7ddf562f464583a0/m_6a187884dc3b469182ad420c.jpeg", "... 6 more" ], "coverImage": "https://di2ponv0v5otw.cloudfront.net/posts/2026/05/28/6a18787a7ddf562f464583a0/m_6a18787d21bd4295939a39b0.jpeg", "likeCount": 9, "commentCount": 0, "createdAt": "2026-05-28T10:16:42-07:00", "scrapedAt": "2026-06-10T19:26:16Z" } ``` If a keyword returns no listings, the actor writes a single diagnostic record instead: ```json { "recordType": "LISTING", "_input": "xyzzy no such item", "error": "NO_RESULTS", "scrapedAt": "2026-06-10T19:26:16Z" } ``` | Field | Type | Description | | --- | --- | --- | | `recordType` | string | Always `"LISTING"`. | | `query` | string | The keyword that produced this record. | | `id` | string | Poshmark listing identifier. | | `title` | string | Listing title. | | `url` | string | Full public listing URL. | | `price` | number | Asking price. | | `currency` | string | ISO currency of the price (e.g. `USD`). | | `originalPrice` | number | Original/retail price when the seller set one, otherwise `null`. | | `size` | string | Item size (e.g. `One Size`, `Large`, `8`). | | `brand` | string | Brand name. | | `condition` | string | Item condition: `New with tags`, `Retail`, `Like new`, `Good`, or `null` when unspecified. | | `newWithTags` | boolean | `true` when the listing is flagged new with tags. | | `department` | string | Top-level department (e.g. `Women`, `Men`, `Kids`). | | `category` | string | Item category (e.g. `Bags`, `Shoes`). | | `colors` | array | Color names listed for the item. | | `sellerUsername` | string | Seller's username. | | `sellerHandle` | string | Seller's display handle. | | `images` | array | All listing photo URLs. | | `coverImage` | string | Primary (cover) photo URL. | | `likeCount` | integer | Number of likes on the listing. | | `commentCount` | integer | Number of comments on the listing. | | `createdAt` | string | When the listing was created. | | `scrapedAt` | string | ISO 8601 timestamp of collection. | | `error` | string | Only on diagnostic records: `NO_RESULTS` or `BLOCKED_AFTER_RETRIES`. | ### Other Resale / Marketplace Scrapers | Actor | Description | | --- | --- | | [Poshmark Search Scraper](https://apify.com/poshmark-search-scraper) | Keyword search → resale listings with price, brand, size, condition, seller, and photos. | | [eBay Search Scraper](https://apify.com/ebay-search-scraper) | Keyword search → eBay listings with price, condition, and seller. | | [eBay Sold Comps Scraper](https://apify.com/ebay-sold-comps-scraper) | Recently sold comparables for any keyword — sale price and date. | | [GOAT Product Scraper](https://apify.com/goat-product-scraper) | Sneaker and apparel product detail, sizing, and pricing from GOAT. | | [Whatnot Live Scraper](https://apify.com/whatnot-live-scraper) | Live auction listings and pricing from Whatnot streams. | # Actor input Schema ## `queries` (type: `array`): Keywords to search on Poshmark (one per array entry). Each keyword is searched independently and yields its own listings. ## `maxPagesPerQuery` (type: `integer`): How many pages of results to collect per query (about 40 listings per page). The actor stops early once a query runs out of results. ## `sortBy` (type: `string`): Order in which listings are returned for each keyword. ## `maxConcurrency` (type: `integer`): Maximum number of parallel requests across all keywords. ## `maxRequestRetries` (type: `integer`): How many times a page request will be retried before giving up on that page. ## `proxyConfiguration` (type: `object`): Apify Proxy or your own proxy list. Datacenter proxies work fine for this source. ## Actor input object example ```json { "queries": [ "coach bag" ], "maxPagesPerQuery": 3, "sortBy": "added_desc", "maxConcurrency": 4, "maxRequestRetries": 5, "proxyConfiguration": { "useApifyProxy": true } } ``` # 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 = { "queries": [ "coach bag" ], "proxyConfiguration": { "useApifyProxy": true } }; // Run the Actor and wait for it to finish const run = await client.actor("xtracto/poshmark-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 = { "queries": ["coach bag"], "proxyConfiguration": { "useApifyProxy": True }, } # Run the Actor and wait for it to finish run = client.actor("xtracto/poshmark-search-scraper").call(run_input=run_input) # Fetch and print Actor results from the run's dataset (if there are any) print("💾 Check your data here: https://console.apify.com/storage/datasets/" + run["defaultDatasetId"]) for item in client.dataset(run["defaultDatasetId"]).iterate_items(): print(item) # 📚 Want to learn more 📖? Go to → https://docs.apify.com/api/client/python/docs/quick-start ``` ## CLI example ```bash echo '{ "queries": [ "coach bag" ], "proxyConfiguration": { "useApifyProxy": true } }' | apify call xtracto/poshmark-search-scraper --silent --output-dataset ``` ## MCP server setup ```json { "mcpServers": { "apify": { "command": "npx", "args": [ "mcp-remote", "https://mcp.apify.com/?tools=xtracto/poshmark-search-scraper", "--header", "Authorization: Bearer " ] } } } ``` ## OpenAPI specification ```json { "openapi": "3.0.1", "info": { "title": "Poshmark Search Scraper", "description": "Search Poshmark for any keyword and get clean resale listings with price, brand, size, condition, seller, and photos.", "version": "1.0", "x-build-id": "E7n98qRhoyoy4uQjM" }, "servers": [ { "url": "https://api.apify.com/v2" } ], "paths": { "/acts/xtracto~poshmark-search-scraper/run-sync-get-dataset-items": { "post": { "operationId": "run-sync-get-dataset-items-xtracto-poshmark-search-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": { "$ref": "#/components/schemas/inputSchema" } } } }, "parameters": [ { "name": "token", "in": "query", "required": true, "schema": { "type": "string" }, "description": "Enter your Apify token here" } ], "responses": { "200": { "description": "OK" } } } }, "/acts/xtracto~poshmark-search-scraper/runs": { "post": { "operationId": "runs-sync-xtracto-poshmark-search-scraper", "x-openai-isConsequential": false, "summary": "Executes an Actor and returns information about the initiated run in response.", "tags": [ "Run Actor" ], "requestBody": { "required": true, "content": { "application/json": { "schema": { "$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": { "$ref": "#/components/schemas/runsResponseSchema" } } } } } } }, "/acts/xtracto~poshmark-search-scraper/run-sync": { "post": { "operationId": "run-sync-xtracto-poshmark-search-scraper", "x-openai-isConsequential": false, "summary": "Executes an Actor, waits for completion, and returns the OUTPUT from Key-value store in response.", "tags": [ "Run Actor" ], "requestBody": { "required": true, "content": { "application/json": { "schema": { "$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": [ "queries" ], "properties": { "queries": { "title": "Search keywords", "type": "array", "description": "Keywords to search on Poshmark (one per array entry). Each keyword is searched independently and yields its own listings.", "items": { "type": "string" } }, "maxPagesPerQuery": { "title": "Max pages per query", "minimum": 1, "maximum": 50, "type": "integer", "description": "How many pages of results to collect per query (about 40 listings per page). The actor stops early once a query runs out of results.", "default": 3 }, "sortBy": { "title": "Sort results by", "enum": [ "added_desc", "price_asc", "price_desc", "like_count" ], "type": "string", "description": "Order in which listings are returned for each keyword.", "default": "added_desc" }, "maxConcurrency": { "title": "Max concurrency", "minimum": 1, "maximum": 20, "type": "integer", "description": "Maximum number of parallel requests across all keywords.", "default": 4 }, "maxRequestRetries": { "title": "Max retries", "minimum": 1, "maximum": 15, "type": "integer", "description": "How many times a page request will be retried before giving up on that page.", "default": 5 }, "proxyConfiguration": { "title": "Proxy configuration", "type": "object", "description": "Apify Proxy or your own proxy list. Datacenter proxies work fine for this source." } } }, "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 } } } } } } } } } } ```