By use case · Price monitoring

Price monitoring API for competitor price tracking and MAP monitoring

The short answer

A price monitoring API returns the current price of a product page as a structured record instead of HTML: price, list price, currency, promotion, stock status and seller. ClawEngine renders each product page, fills a schema you define, and returns the same fields from every retailer, so you can re-run the same watchlist on a schedule and diff the results. That diff is the actual product: price cuts, competitor undercutting, stockouts and minimum advertised price violations, detected the day they happen rather than the week you notice. Plans start at $39 a month with no free tier.

Clean markdown & JSON · JavaScript rendered · robots.txt respected

Last updated July 2026

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Pricing teams do not have a data problem so much as a shape problem. The prices you need are visible on public product pages right now, but every retailer renders them differently: one puts the number in a JSON-LD block, another builds it client-side after a variant selector loads, a third shows a strike-through list price plus a cart-only promotional price. Writing a parser per retailer works for a week and then breaks silently, which is worse than not having it, because your pricing decisions quietly go stale.

A price monitoring API removes the parser layer. You send a product URL and the fields you want, and ClawEngine renders the page in a real browser, reads the price wherever it lives, and returns a typed record. The same call shape works on the next retailer, so adding a competitor is a row in a config file rather than a sprint. Run your watchlist nightly, store one observation per run instead of overwriting, and you get a price history you can actually reason about: how deep a competitor discounts, how long promotions run, when a SKU goes out of stock, and which resellers are selling below your minimum advertised price.

Two boundaries worth stating up front, because they decide whether this works for you. First, we crawl public and permitted pages only and we do not defeat anti-bot systems or logins, so marketplaces that actively block automated access are not a durable source no matter which vendor you buy. Second, the pages we are good at are the ones most US brands actually care about: direct-to-consumer sites, specialty and regional retailers, distributor catalogs, authorized reseller storefronts and your own channel. That is where MAP enforcement and competitive pricing decisions are won.

CRAWL RENDER JS EXTRACT MARKDOWN JSON

Any URL in LLM-ready data out

robots.txt respected public data only

Why it works

What you get with Price monitoring

One schema across every retailer

Price, list price, currency, promo, stock status and seller come back in the same shape from a DTC site, a specialty retailer and a distributor catalog. No parser per source.

Renders client-side pricing

Prices that appear only after a variant selector or a pricing widget loads are read after the page renders, so you get the real number rather than an empty placeholder.

Built for scheduled diffs

Re-run the same watchlist on an interval and compare. Price cuts, promo starts, stockouts and MAP violations fall out of the diff with timestamps attached.

What it handles

Any URL in, clean structured data out

Point ClawEngine at a public page and it crawls, renders the JavaScript and extracts clean markdown or typed JSON in one call. Define a schema for structured fields, and respect robots.txt and Terms of Service by default.

Extracts price, list price, promo and currency
Captures stock status and seller name
Renders JavaScript pricing widgets
Runs the same watchlist on a schedule
Flags MAP violations with timestamped evidence
Reads robots.txt and stays on permitted pages

POST /v1/extract extraction result

200 · JSON

{
  "url": "https://example.com/products/atlas",
  "title": "Atlas Field Notebook",
  "markdown": "# Atlas Field Notebook\n\nDurable...",
  "data": {
    "name": "Atlas Field Notebook",
    "price": 24.00,
    "currency": "USD",
    "rating": 4.7
  },
  "links": [ "/products", "/cart" ],
  "metadata": { "rendered": true }
}

JS rendered · boilerplate stripped ✓ robots.txt respected

Why ClawEngine

One API that crawls, renders and extracts

Not a raw HTML dump, not a headless browser fleet to run, and not a brittle parser to maintain. One call crawls a public page, renders its JavaScript and returns clean markdown or typed JSON, built for RAG pipelines and AI agents.

LLM-ready output

Clean markdown or typed JSON with the boilerplate stripped, so the data drops straight into a vector store, a prompt or an agent without a cleanup step.

JavaScript rendered

Each page loads in a real browser environment before extraction, so single-page apps and client-rendered content come back complete, not as an empty shell.

Compliance-first

ClawEngine works on public, permitted data only. It respects robots.txt and site Terms of Service and honors crawl-delay, so responsible scraping is the default.

Code examples

Watch a price list in a few lines

Send a product URL and the fields you want. ClawEngine renders the page and returns a typed record. Run the same list on a schedule and diff the results to get price cuts, stockouts and MAP violations.

curl Extract a product price (POST /v1/extract)

curl https://api.clawengine.ai/v1/extract \
  -H "Authorization: Bearer $CLAWENGINE_API_KEY" \
  -H "Content-Type: application/json" \
  -d '{
    "url": "https://shop.example.com/products/trail-runner-gtx",
    "format": "json",
    "render": true,
    "schema": {
      "product_name": "string",
      "mpn": "string",
      "price": "number",
      "list_price": "number",
      "currency": "string",
      "promo_text": "string",
      "in_stock": "boolean",
      "seller": "string"
    }
  }'

python Detect MAP violations across resellers

import os, requests, datetime

BASE = "https://api.clawengine.ai/v1"
headers = {"Authorization": f"Bearer {os.environ['CLAWENGINE_API_KEY']}"}
schema = {
    "product_name": "string", "mpn": "string", "price": "number",
    "promo_text": "string", "in_stock": "boolean", "seller": "string",
}

# your MAP policy, keyed by manufacturer part number
map_policy = {"TR-GTX-11": 149.00, "TR-GTX-12": 159.00}

reseller_urls = [
    "https://reseller-a.example.com/p/trail-runner-gtx",
    "https://reseller-b.example.com/shop/trail-runner-gtx-11",
]

for url in reseller_urls:
    rec = requests.post(f"{BASE}/extract", headers=headers,
                        json={"url": url, "format": "json",
                              "render": True, "schema": schema}).json()["data"]
    floor = map_policy.get(rec.get("mpn"))
    if floor and rec["price"] < floor:
        print(f"MAP violation: {rec['seller']} at {rec['price']} "
              f"(policy {floor}) on {url}")
    # append every observation, never overwrite, so you keep the history
    store_observation(url, rec, datetime.datetime.utcnow())

node Diff today against yesterday

// The value is in the diff, not the snapshot. Compare the newest
// observation to the previous one and emit only the changes.
const today = await extractAll(watchlist);          // your wrapper over /v1/extract
const events = [];

for (const [url, now] of Object.entries(today)) {
  const prev = await lastObservation(url);          // your own store
  if (!prev) continue;

  if (now.price < prev.price) {
    const pct = (((prev.price - now.price) / prev.price) * 100).toFixed(1);
    events.push({ url, type: "price_cut", pct, from: prev.price, to: now.price });
  }
  if (prev.in_stock && !now.in_stock) {
    events.push({ url, type: "stockout", seller: now.seller });
  }
  if (!prev.promo_text && now.promo_text) {
    events.push({ url, type: "promo_started", promo: now.promo_text });
  }
}

console.log(`${events.length} pricing events since the last run`);

Price monitoring API: the questions buyers ask

What is a price monitoring API?

A price monitoring API is a service that returns product pricing as structured data rather than a web page. You send a product URL and the fields you want, and it returns price, list price, currency, promotion text, stock status and seller as typed JSON. Because the output shape is identical across retailers, you can compare and diff prices without writing a parser for each site.

How do I track competitor prices automatically?

Build a watchlist of competitor product URLs matched to your own SKUs, extract each one on a schedule, and store every observation as its own row keyed by URL and timestamp. Comparing the newest row to the previous one produces the events that matter: a price cut, a new promotion, a stockout, or a competitor moving below you. Daily is enough for most categories; fast-moving electronics and travel justify hourly.

What is MAP monitoring software?

MAP monitoring software watches the advertised prices your resellers publish and flags anyone selling below the minimum advertised price in your policy. Mechanically it is price monitoring plus a rule: extract the advertised price from each authorized reseller page, compare it to the MAP for that SKU, and record a violation with the URL, price and timestamp as evidence. The screenshot-and-timestamp evidence trail is what makes an enforcement letter stick.

Is it legal to scrape competitor prices?

Collecting publicly displayed prices is broadly lawful in the United States, and courts have repeatedly declined to treat access to public web pages as unauthorized access under the Computer Fraud and Abuse Act. What binds you is each site's Terms of Service and robots.txt, plus antitrust law: gathering public prices is fine, but coordinating prices with a competitor is not. Read the terms per source and keep the collection unilateral. This is general information, not legal advice.

How often should I check competitor prices?

Match the interval to how fast the category moves. Consumer packaged goods and furniture shift weekly, so a daily crawl is generous. Consumer electronics, tickets and anything with algorithmic repricing can change several times a day, which justifies hourly checks on a short priority list. Crawling everything hourly mostly buys you noise and a larger bill, so tier the watchlist instead.

Can I get price history instead of just the current price?

Only if you store it. A scraping API returns the price as of the request, so history is something you build by appending one row per observation rather than updating a single price column. Keep the URL, the timestamp, the price, the promotion text and the stock status. Six months of that is far more useful than a snapshot, because it shows discount depth, promotion cadence and how competitors respond to your own moves.

Good questions

Questions about Price monitoring

Matching is the hard part, not extraction. Start with the strongest identifier the page publishes, usually a GTIN, UPC or MPN, which many retailers expose in their JSON-LD product markup. Fall back to brand plus model number, and only then to fuzzy title matching, which needs human review. Extract the identifiers as their own fields and store the match as a reviewable mapping rather than recomputing it every run.

Treat both as data, not as errors. A 404 usually means the SKU was discontinued or the URL changed, and silently dropping the row makes it look like the competitor never sold it. Write an observation with a null price and a status of gone or out_of_stock, keep the row, and alert if a high-priority URL fails several runs in a row so someone can re-map it.

No, and we would rather say so than sell you something that breaks. Large marketplaces run aggressive anti-bot systems and their terms restrict automated access, so we do not target them. If marketplace buy-box data is the core of your product, license it from a provider that has an agreement in place. ClawEngine covers the open retail web around it: brand sites, authorized resellers, specialty retailers and distributor catalogs.

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