# Poshmark Scraper — Listings, Prices & Brands (No API Key) (`jamhimself/poshmark-search-scraper`) Actor Scrape Poshmark resale listings as clean JSON: title, price, original price, brand, size, category, condition, likes, image, and URL. Bulk, no API key. - **URL**: https://apify.com/jamhimself/poshmark-search-scraper.md - **Developed by:** [Jaime Martinez](https://apify.com/jamhimself) (community) - **Categories:** E-commerce, Agents, Developer tools - **Stats:** 2 total users, 1 monthly users, 100.0% runs succeeded, 0 bookmarks - **User rating**: No ratings yet ## Pricing $5.00 / 1,000 resale listings 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 ## Poshmark Search Scraper — Listings, Prices & Brands (No API Key) Scrape Poshmark search results into a clean, structured dataset — no API key, no login. This Poshmark scraper pulls listing titles, brands, asking prices, original retail prices, sizes, conditions, colors, and engagement counts from any search query or Poshmark search URL. Built for developers, analysts, and AI pipelines that need secondhand fashion data and resale price research in bulk, pay per result. Works as a lightweight Poshmark API alternative for market and pricing analysis. Under the hood it uses Chrome TLS impersonation with residential US proxies and automatic session rotation to clear anti-bot walls, so you don't manage proxies or logins. ### What you get | Field | Description | |---|---| | `title` | Listing title | | `brand` | Brand | | `price` | Listing (asking) price | | `originalPrice` | Seller-stated retail price, when given | | `size` / `category` / `department` | Item attributes | | `condition` | Listing condition | | `colors` | Colors | | `likeCount` / `commentCount` | Engagement | | `available` | Whether it's still available | | `publishedAt` | First published date | | `image` | Cover photo URL | | `url` | Poshmark listing page | ### Use cases - Resale price research — compare asking vs. original retail across a brand or category - Secondhand fashion market research and demand signals from likes and comments - Brand and competitor monitoring on the Poshmark marketplace - Sourcing and reselling — find listings by search term for dropshipping and flips - Build datasets of resale fashion listings for analysis - Feed listing data into an LLM or RAG pipeline for pricing and trend queries ### Input - **searchQuery** — what to search for, e.g. `coach bag`, `nike air force 1`, `lululemon leggings` - **startUrls** — (optional) paste Poshmark search URLs directly, e.g. `https://poshmark.com/search?query=coach` (overridden by searchQuery if both are set) - **maxResults** — how many listings to return; first page yields ~48 and it paginates automatically (default 60, up to 1000) ### Pricing Pay per listing delivered. No subscription. *A quick review on the Apify Store really helps other builders find it.* # Actor input Schema ## `searchQuery` (type: `string`): What to search Poshmark for, e.g. "coach bag", "nike air force 1", "lululemon leggings". ## `startUrls` (type: `array`): Alternatively, paste Poshmark search URLs directly (e.g. https://poshmark.com/search?query=coach). Overridden by searchQuery if both are set. ## `maxResults` (type: `integer`): Maximum number of listings to return (the first page yields ~48; paginates automatically). ## Actor input object example ```json { "searchQuery": "coach bag", "maxResults": 60 } ```` # Actor output Schema ## `listings` (type: `string`): One row per listing. # 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 = { "searchQuery": "coach bag" }; // Run the Actor and wait for it to finish const run = await client.actor("jamhimself/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 = { "searchQuery": "coach bag" } # Run the Actor and wait for it to finish run = client.actor("jamhimself/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 '{ "searchQuery": "coach bag" }' | apify call jamhimself/poshmark-search-scraper --silent --output-dataset ``` ## MCP server setup ```json { "mcpServers": { "apify": { "command": "npx", "args": [ "mcp-remote", "https://mcp.apify.com/?tools=jamhimself/poshmark-search-scraper", "--header", "Authorization: Bearer " ] } } } ``` ## OpenAPI specification ```json { "openapi": "3.0.1", "info": { "title": "Poshmark Scraper — Listings, Prices & Brands (No API Key)", "description": "Scrape Poshmark resale listings as clean JSON: title, price, original price, brand, size, category, condition, likes, image, and URL. Bulk, no API key.", "version": "1.0", "x-build-id": "BkuHSvhJS8yj2vKDJ" }, "servers": [ { "url": "https://api.apify.com/v2" } ], "paths": { "/acts/jamhimself~poshmark-search-scraper/run-sync-get-dataset-items": { "post": { "operationId": "run-sync-get-dataset-items-jamhimself-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": { "$ref": "#/components/schemas/inputSchema" } } } }, "parameters": [ { "name": "token", "in": "query", "required": true, "schema": { "type": "string" }, "description": "Enter your Apify token here" } ], "responses": { "200": { "description": "OK" } } } }, "/acts/jamhimself~poshmark-search-scraper/runs": { "post": { "operationId": "runs-sync-jamhimself-poshmark-search-scraper", "x-openai-isConsequential": false, "summary": "Executes an Actor and returns information about the initiated run in response.", "tags": [ "Run Actor" ], "requestBody": { "required": true, "content": { "application/json": { "schema": { "$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": { "$ref": "#/components/schemas/runsResponseSchema" } } } } } } }, "/acts/jamhimself~poshmark-search-scraper/run-sync": { "post": { "operationId": "run-sync-jamhimself-poshmark-search-scraper", "x-openai-isConsequential": false, "summary": "Executes an Actor, waits for completion, and returns the OUTPUT from Key-value store in response.", "tags": [ "Run Actor" ], "requestBody": { "required": true, "content": { "application/json": { "schema": { "$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", "properties": { "searchQuery": { "title": "Search query", "type": "string", "description": "What to search Poshmark for, e.g. \"coach bag\", \"nike air force 1\", \"lululemon leggings\"." }, "startUrls": { "title": "Poshmark search URLs (optional)", "type": "array", "description": "Alternatively, paste Poshmark search URLs directly (e.g. https://poshmark.com/search?query=coach). Overridden by searchQuery if both are set.", "items": { "type": "object", "required": [ "url" ], "properties": { "url": { "type": "string", "title": "URL of a web page", "format": "uri" } } } }, "maxResults": { "title": "Max results", "minimum": 1, "maximum": 1000, "type": "integer", "description": "Maximum number of listings to return (the first page yields ~48; paginates automatically).", "default": 60 } } }, "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 } } } } } } } } } } ```