StockX Trading Cards Flip-Margin Tracker — Pokemon TCG

Track per-size bid, ask, and last-sale prices on StockX over time and receive precise flip-margin signals. Unlike generic product-dump scrapers or StockX's own free catalog tools, this actor captures the time-series dimension: every scheduled run produces a snapshot, computes change-detection deltas vs the previous run, and emits a flip-margin signal (lastSale − lowestAsk − estimated fees) per size.

Why this actor

	Free StockX catalog APIs	Competitor dumps ($1.50–$4.50/1k)	This actor
Per-size bid/ask	Aggregated only	One-shot dump	Yes
Time-series / history	Paid €79+/mo	No	Yes (KV-persisted across runs)
Change-detection deltas	No	No	Yes — ask dropped %, new ATL
Flip-margin calc	No	No	Yes — lastSale − ask − fees
Scheduling-friendly	No	No	Yes — KV state survives across runs
Access	N/A	Breaks on rotation	Browser + residential (baked in)

Modes

stealth (default — no StockX account needed)

Launches a browser through an Apify RESIDENTIAL proxy. The actor uses behavioral page warming to pass StockX's protection before extracting script#__NEXT_DATA__, which contains the full variants[].market.bidAskData per-size market data.

On a 403 challenge, the actor automatically retries on a fresh residential IP (up to maxRetries attempts). Billing is per successful result only — failed attempts produce zero billed events.

api (optional — buyer-supplied StockX API key)

If you have access to the StockX developer API (apply at developer.stockx.com), supply your stockxApiKey and stockxApiToken. The actor routes market data through the official GetVariantMarketData endpoint at zero access friction, 25k requests/24h. Falls back to stealth mode automatically if the API call fails.

What you get (per size, per run)

• lowest_ask, highest_bid, last_sale, number_of_asks, number_of_bids
• sales_last_72h — recent velocity signal
• flip_margin_usd — lastSale − lowestAsk − estimated fees (configurable via feesPct)
• flip_roi_pct — margin as % of the ask price
• ask_delta_pct — change since last run (negative = ask dropped)
• ask_drop_alert — true if ask dropped by ≥ alertAskDropPct %
• new_low_alert — true if this is the lowest ask ever seen for this size
• margin_alert — true if flip margin exceeds alertFlipMarginMin USD

Scheduling

The actor is designed for repeated scheduled runs. Pair it with an Apify schedule (daily, every 12h, etc.) and set a fixed kvStoreName. On each run the actor loads the previous snapshot from the named KV store, computes deltas, then saves the new snapshot. History accumulates across runs (up to 365 data points per size).

Input example

These live StockX Pokemon TCG product slugs were verified by search and page fetch on 2026-07-15.

{
  "mode": "stealth",
  "slugs": [
    "pokemon-tcg-scarlet-violet-151-6pk-booster-bundle",
    "pokemon-tcg-scarlet-violet-15-elite-trainer-box",
    "pokemon-tcg-classic-special-set-japanese"
  ],
  "alertAskDropPct": 5,
  "alertNewLowAsk": true,
  "alertFlipMarginMin": 20,
  "feesPct": 12.5,
  "kvStoreName": "stockx-flip-state",
  "maxRetries": 3,
  "proxyConfiguration": { "useApifyProxy": true, "apifyProxyGroups": ["RESIDENTIAL"] }
}

Proxy requirement

StockX blocks all datacenter IPs. Apify RESIDENTIAL proxy is required in browser mode. In api mode, no proxy is needed.

Pricing

Pay-per-result: one billing event per successful per-size market row. Failed mint attempts (blocked pages) produce zero billed events.

Integrations

Built for trading-card resellers and collectors monitoring bid/ask spreads and size-level price movements of sealed Pokemon TCG products over time — the JSON/dataset output drops into the tools you already run, no glue code:

• n8n / Make / Zapier — trigger a run or pipe every new dataset item into 500+ apps (Google Sheets, Airtable, Slack, HubSpot, your database) with no code: n8n, Make, Zapier.
• Webhooks — fire your own endpoint the moment a run finishes, to push results straight into your pipeline (docs).
• MCP server — expose this actor as a tool to Claude, Cursor, or any MCP client so an AI agent can pull this data mid-conversation (guide).
• API & SDKs — fetch the dataset as JSON, CSV, or Excel through the Apify REST API or the Python / JS SDKs.

See all Apify integrations.

Usage statistics

This Actor creates a small, content-free summary at the end of each run. It is used only to monitor reliability and improve this Actor. A copy is saved as USAGE_STATS in your own Apify key-value store, so you can see the exact record created for your run.

Set disableUsageStats to true in the input to opt out. Nothing is sent then; your USAGE_STATS record only says that statistics were disabled.

Only these fields are recorded:

• schema version, Actor name and build number;
• UTC start and finish hour (not a precise timestamp);
• run duration, number of results and time to the first result, each as a coarse range;
• whether the result was empty, the end status, and an error type from a fixed list;
• memory setting and counts of charged events;
• names of the input fields you set, never their values;
• the selected option for input fields that offer a fixed list of choices (for example a sort order).

We do not collect input text, search terms, URLs, domains, usernames, email addresses, names, proxy credentials, tokens, scraped records, output items, raw error messages, stack traces, or hashes of any of those values. Records are kept for no longer than 13 months, used only as aggregated operational statistics, and never sold or shared.

Additional fields (Phase 2)

This Actor also records your Apify user ID, whether Apify marks the account as paying, the size range of list inputs, the selected country when the input offers a fixed list of countries, and one category from a fixed Actor taxonomy. We use these fields only for aggregate reliability, repeat-use and cross-Actor analysis; reports suppress any cell with fewer than five distinct users.

The same disableUsageStats: true input flag turns these fields off too. The user ID is removed after 13 months; we do not export, sell, share, or attempt to re-identify this data.

Run-outcome signals (v2)

To learn whether a run did what it was asked to do, the record also holds a few more coarse ranges and yes/no flags. None of them contains content:

• the result limit you asked for (a range, when the input has one) and what share of it was delivered;
• results delivered per input item you listed (a range);
• output quality as ranges: how fully the result fields were filled, the share of rows that look like errors, the share of duplicate rows, and how many different fields appeared. These are counted in memory while results are saved; no result content is kept;
• how the run was started (console, API, schedule, webhook, another Actor);
• how it ended: stopped by you, timed out, reached the requested limit, stopped by the charge limit, and how many times the platform moved the run;
• if this Actor reports it: how many items to process worked or failed (ranges) and one failure reason from a fixed list;
• a short code made from the names of the input fields you set, never their values.

Repeat-run fingerprint (v2)

When your Apify user ID is recorded (see above), the record also holds an 8-character one-way code made from your input (proxy settings left out) and this Actor's name. It only lets us see that the same account ran the same input again soon after an unsatisfying run; we never see the input itself. It is stored only in the database, never published, and reports use it in aggregate with the same five-user minimum. It is the one exception to the statement above that no hashes are collected, and disableUsageStats: true turns it off.