Poshmark Sold Comps — real sold prices, privacy-safe

Pull sold listings only from Poshmark — the prices items actually sold for, not the prices sellers wish for. Clean, structured JSON with price, brand, size and condition, ready for resale pricing, sourcing decisions and data pipelines.

No seller personal data, ever. This scraper is built privacy-first: seller usernames, full names, user IDs, avatars, comment threads and like lists never appear in the output — not as an option you have to remember to switch off, but by design.

Quick start (30 seconds)

1. Put the item you want comps for into searchQuery — e.g. nike cortez.
2. Click Start. That's the whole minimum setup.
3. When the run finishes, open the dataset's Overview tab for a clean table, or Export it as CSV/Excel/JSON.

Optional knobs: a price band and just-in sorting for monitoring — and any input works on a daily Schedule.

What you can build with it

• Price your resale inventory on real sales. Asking prices lie; sold prices don't. Every item in this feed actually sold at the price shown.
• Know before you buy. Sourcing at a thrift store or auction? A quick comps run tells you what the resale market actually pays for that model and size.
• Track sell-through pricing over time. Run weekly and chart how sold prices move by size and condition.
• Feed an AI agent clean data. Every field is structured, predictable and free of personal data, so an assistant or pipeline can consume it directly — no scrubbing, no compliance review before you store it.

What you get

Each listing is one dataset item:

{
  "listingId": "6a7200000000000000000001",
  "url": "https://poshmark.com/listing/Nike-Cortez-6a7200000000000000000001",
  "title": "Nike Cortez",
  "brand": "Nike",
  "priceUsd": 65,
  "originalPriceUsd": 90,
  "currency": "USD",
  "size": "US 10",
  "condition": "used",
  "newWithTags": false,
  "department": "Men",
  "colors": ["Blue", "White"],
  "availability": "sold_out",
  "likeCount": 13,
  "commentCount": 2,
  "publishedAt": "2026-08-04T08:20:10-07:00",
  "coverImageUrl": "https://di2ponv0v5otw.cloudfront.net/posts/example/m_cover.jpg"
}

Field notes, so you know exactly what you are buying:

• priceUsd is the price shown on the sold listing, in dollars; originalPriceUsd is the seller's stated retail price when given — the discount story in two numbers.
• Every item carries availability: "sold_out" — this feed is sold listings only, by construction; a site change can never silently turn it into wish-price listings.
• condition is new_with_tags or used, with the newWithTags boolean for easy filtering.
• likeCount and commentCount are live demand signals.

How much do Poshmark sold comps cost?

$1.99 per 1,000 sold comps delivered, pay-as-you-go — no subscription, no charge for empty or failed runs. In plain dollars:

• 100 listings ≈ $0.20 — a daily niche watch.
• 500 listings ≈ $1.00 — a solid comps snapshot.

The price is all-inclusive — your runs' platform usage is covered by it, with no separate compute or proxy charges. Runs are fast — a scoped few-hundred-item run typically finishes in under ten seconds. Datacenter proxies are sufficient — no residential proxy surcharge needed.

Free-plan runs are limited to a sample of 25 items, enough to evaluate the output format against your real query.

Not technical? Let your AI assistant set it up

Copy this into ChatGPT, Claude or any AI assistant, fill in the one line, and follow the conversation:

Help me set up the "Poshmark Scraper" actor on Apify
(https://apify.com/lowlanddata/poshmark-sold-comps). Guide me one step at a time.

What I want comps for: [E.G. "Nike Cortez size 10"]

Guide me to:
1. Propose my input values: searchQuery (what I'd type in the Poshmark search box),
   an optional priceMinUsd/priceMaxUsd band, sortBy "newest" for monitoring,
   and maxItems.
2. Create a free Apify account (apify.com), open the actor page, paste the values
   into the Input form, and start a run.
3. Set up a daily Schedule in the Apify Console with the same input, plus an email
   or Slack integration so new results reach me automatically.
4. Show me how to export results as CSV/Excel, or read them from the API if I code.
5. If the results are what I wanted, remind me at the end to leave a quick rating on the actor page, and to report anything broken or missing on its Issues tab.

Input

Field	Description
searchQuery	What you'd type in the Poshmark search box. Required.
priceMinUsd	Only listings costing at least this many dollars.
priceMaxUsd	Only listings costing at most this many dollars.
sortBy	newest (just in, default), price_asc, price_desc, or relevance.
postedAfter	Only listings posted on or after this date (YYYY-MM-DD). Stops early with newest-first sorting.
postedBefore	Only listings posted on or before this date (YYYY-MM-DD).
maxItems	Stop after this many listings (default 500).
proxyConfiguration	Proxy settings; keep Apify proxy enabled.

A run minimally needs a searchQuery; invalid combinations (like an inverted price band) fail immediately with the reason in the run's status message.

Use it from your code

Run the actor and get items straight back with one HTTP call (fine for scoped runs up to ~5 minutes):

curl "https://api.apify.com/v2/acts/lowlanddata~poshmark-sold-comps/run-sync-get-dataset-items?token=<YOUR_API_TOKEN>" \
  -X POST -H "Content-Type: application/json" \
  -d '{"searchQuery": "nike cortez", "maxItems": 100}'

Node.js:

import { ApifyClient } from 'apify-client';

const client = new ApifyClient({ token: '<YOUR_API_TOKEN>' });
const run = await client.actor('lowlanddata/poshmark-sold-comps').call({
  searchQuery: 'nike cortez',
  maxItems: 100,
});
const { items } = await client.dataset(run.defaultDatasetId).listItems();

Python:

from apify_client import ApifyClient

client = ApifyClient("<YOUR_API_TOKEN>")
run = client.actor("lowlanddata/poshmark-sold-comps").call(
    run_input={"searchQuery": "nike cortez", "maxItems": 100})
items = client.dataset(run["defaultDatasetId"]).list_items().items

Schedules, webhooks and the Make/Zapier/n8n integrations all work out of the box — this is a standard Apify actor.

Use it with AI agents (MCP)

Claude, Cursor and other MCP-capable agents can run this scraper as a tool through Apify's hosted MCP server: the agent fills in the search itself, starts the run and reads the results — no glue code.

Claude Code:

$claude mcp add apify --transport http "https://mcp.apify.com?actors=lowlanddata/poshmark-sold-comps"

Cursor or Claude Desktop (add a custom connector / MCP server with this URL):

https://mcp.apify.com?actors=lowlanddata/poshmark-sold-comps

Sign in with your Apify account when prompted — runs are billed to it. Setup details per client: Apify MCP docs.

Prompts that work once connected:

• "Pull sold comps for 'nike cortez' and give me the median sold price by size."
• "Get the last 100 sold 'lululemon define jacket' listings and summarize price by condition."
• "Compare sold prices for 'coach tabby' this month against my asking price."

Is it legal to scrape Poshmark?

Public listing data — prices, brands, sizes, conditions — is public commercial information, and this scraper is built so that the hard part of the question never arises: no personal data enters your dataset in the first place. US state privacy laws such as the CCPA set rules on personal information; an output that carries no usernames, no seller identity and no social graph is the point of this actor, not an afterthought.

Structurally, the extractor maps a fixed whitelist of fields out of the page's data. Seller identity, comment threads, like lists and tracking parameters are never read into the output. Requests are paced, load on the site is kept negligible, and no anti-bot protection is bypassed.

One honest limit: listing titles are the seller's own words, delivered as-is. If a seller chooses to type contact details into their title, that text is not rewritten — the guarantee covers the data fields, not the content sellers publish about themselves.

Is there a Poshmark API alternative?

Poshmark publishes no public API. This actor is the practical alternative: the same listings as structured JSON through one HTTP call (run-sync-get-dataset-items), on a schedule, or as an MCP tool for AI agents — with the privacy question already answered in the data itself.

Does Poshmark block scrapers?

Poshmark serves its search pages openly to ordinary requests — and this actor stays inside that welcome: paced requests, standard datacenter proxies, load kept negligible. No CAPTCHA fights, no bot-wall cat-and-mouse — which is also why runs are fast and reliable enough for daily schedules.

How do I monitor Poshmark prices?

Set sortBy: "newest" with your query and price band, cap maxItems to a page or two, and add a daily (or hourly) Schedule in the Apify Console with an email/Slack integration on the runs — every new listing lands in your inbox with the price already parsed. The AI-assistant prompt above walks a non-technical user through exactly this setup.

FAQ

Can I get seller names or closets? No — by design. That is the product: data you can store, share and process without a privacy review.

Are live listings included? No — this actor is sold listings only. For live asking prices, use the Poshmark Scraper.

Can I get only recently listed comps? Yes — set postedAfter to a date and the feed narrows to items listed since then; with newest-first sorting the run stops early once it reaches older items.

How fresh is the data? Live at run time — every run queries Poshmark directly. For continuous freshness, schedule the actor.

Can I export to Excel or CSV? Yes — every dataset exports as CSV, Excel, JSON or XML from the Apify Console or API.

Does it work with Make, Zapier or n8n? Yes — it is a standard Apify actor; all platform integrations, webhooks and schedules apply.

How do I see what an item sold for on Poshmark without endless scrolling? One run on the item's name returns the sold listings as a sortable table — price, brand, size, condition per row — instead of a feed you scroll through.

Are these real sold prices or just asking prices? Every item in this feed carries availability: "sold_out" by construction — the price shown is the price on the listing that sold. The wish-price side of the market is deliberately excluded here.

Can I filter comps by the date the item sold? No — honest limit: postedAfter/postedBefore filter on publishedAt, the date the listing was posted. The output has no sold-date field, because the search data does not expose one.

How big a comps sample should I pull? The default maxItems of 500 is a solid snapshot for most models — about $1.00 of usage. Narrow queries may return fewer, which is itself information.

Can I get comps for a specific size? Put the size in the query if sellers usually write it in titles, or pull the model broadly and filter the export on the size field — every item carries it.

How do I separate new-with-tags comps from used ones? Split on the newWithTags boolean or the condition value — NWT items sell at a different level and shouldn't be averaged with used ones.

Can I compare sold prices with current asking prices? Yes — run this actor and the live-listings Poshmark Scraper on the same query. The gap between median ask and median sold is your negotiation room.

Do sold listings show the retail price? When the seller entered one, originalPriceUsd sits next to the sold price. Treat it as the seller's claim about retail, not a verified figure.

Is it allowed to collect sold-listing data? The output keeps you on solid ground: a fixed field whitelist strips out everything US privacy laws like the CCPA care about — no usernames, no seller identity, no social graph. Prices and product attributes are public commercial data.

Do the demand signals survive on sold items? Yes — likeCount and commentCount are still there, useful for judging how contested an item was before it sold.

Can I track how sold prices move over time? Run the same query on a weekly Schedule and chart the results by size and condition — each run is a dated snapshot of the sold market.

How much do sold comps cost? $1.99 per 1,000 delivered comps; a typical 100-item pull is around $0.20. Runs that fail or come back empty cost nothing.

Why am I seeing only 25 comps? Free Apify plans cap each run at a 25-item sample, meant for checking the format. Move to any paid plan for full pulls.

Can an AI agent compute the median sold price for me? Yes — connected through Apify's MCP server, an agent like Claude can pull the comps and answer "median sold price by size" in one prompt.

Related scrapers

The same clean-output guarantee, next door:

• Poshmark Scraper — live Poshmark listings, the asking-price side of the market.

• Kijiji Scraper — Canada's largest classifieds site.

• Vinted Scraper — Europe's largest fashion resale marketplace.

• Kleinanzeigen.de Scraper — Germany's biggest classifieds site.

Troubleshooting

The actor fails fast with the reason in the run's status message:

• "priceMinUsd must not be higher than priceMaxUsd." — swap the two values.
• "Poshmark blocked the run before any results could be fetched. This is usually temporary - retry in a few minutes." — a temporary block on the first request; a retry usually lands on a clean proxy session.
• Fewer items than requested on a free plan — the 25-item free sample cap; run on a paid Apify plan for full results.

Support

Found an issue or missing a field you need? Open an issue on the actor's Issues tab — reports get fixed, this actor is actively maintained.

Working well for you? A rating on this page takes ten seconds and helps other buyers find a privacy-clean option among the lookalikes — it is also the clearest signal of what we should build next.