Watching your own price across your own channels answers "am I underselling myself." It doesn't answer "what is everyone else charging for the same thing." That's a different question, and it starts from the opposite end — not a fixed set of ASINs and store URLs you already own, but a category you don't yet know the players in.
If you're an agent (or building one) reading this rather than a human, the full machine-readable schema for every endpoint below lives at mindcase.co/skills.md.
What does competitive price intelligence actually require?
Two steps that answer two different questions:
- Who's actually selling this, and at what headline price? A single category query needs to surface every merchant carrying a comparable product, not just the one or two competitors you already track by name.
- What does one specific competitor's listing actually look like? Once you know who's in the market, you need full detail on their listing — discount status, stock, rating — not just the price a search result shows.
Watching your own Amazon listing or Shopify storefront answers neither of these on its own — both need you to already know which product URL to check. Competitive intelligence starts one step earlier, from a category, not a URL.
How do you discover which competitors are selling a product?
Google Shopping takes a plain keyword query and returns listings from every merchant Google has indexed for it — not one seller's catalog, the whole competitive set at once.
curl -X POST "https://api.mindcase.co/v1/data/google/shopping/run?wait=true" \
-H "Authorization: Bearer $MINDCASE_API_KEY" \
-H "Content-Type: application/json" \
-d '{
"params": {
"queries": "wireless earbuds noise cancelling",
"country": "us",
"maxResults": 20
}
}'
# $0.003 per resultGoogle Shopping returns a deliberately lean 10
fields per result — title, merchant, price, rating, reviewCount,
position, and a productUrl back to the actual listing. That's enough to
answer "who's in this market and roughly what are they charging," and the
merchant field is the one that matters here: it's what turns a single
query into a list of named competitors, most of which you probably didn't
already have on a tracked list.
How do you get full detail on a specific competitor's listing?
A Shopping result tells you a competitor exists and roughly what they
charge. It doesn't tell you if that price is currently discounted, whether
they're in stock, or what their rating actually is — for that, follow the
productUrl into a full detail call. If it's an Amazon listing, that's
Amazon Products; if it's a Shopify storefront,
Shopify Products.
curl -X POST "https://api.mindcase.co/v1/data/amazon/products/run?wait=true" \
-H "Authorization: Bearer $MINDCASE_API_KEY" \
-H "Content-Type: application/json" \
-d '{
"params": {
"urls": ["B0CHX3QBCH"]
}
}'
# $0.0015 per productAmazon Products returns 36 fields for that one
listing — discount status, onDeal, availability, boughtPastMonth,
full review summary. Shopify Products works the
same way for a competitor's own storefront: point it at the store URL (or
a single product URL from that store) and it returns 21 fields including
priceFrom/priceTo, onSale, and inStock — no login, no per-store
integration to build.
How do you set this up as an agent workflow?
The category query and the detail calls are separate steps because they
answer separate questions, and an agent is what connects them: run the
Google Shopping query for a category, take the merchant and productUrl
from every result worth watching, and fan out a detail call to whichever of
Amazon Products or Shopify Products matches that URL. Re-run the whole
sequence on a schedule and the interesting signal isn't any single price —
it's a competitor's price moving between runs, or a new merchant showing up
in the category query who wasn't there last time. Point Claude Code or
another coding agent at mindcase.co/skills.md and the schema
for all three endpoints is machine-readable, so the agent can wire the
hand-off itself.
What can't you get from Mindcase?
Two cases.
A merchant outside Amazon, Shopify, and what Google Shopping indexes. If a competitor sells exclusively through a platform none of these three cover, nothing here surfaces them — Google Shopping only returns what Google itself has indexed, which isn't every storefront on the internet.
Price history for a listing you weren't already watching. Same limitation as every other pricing endpoint in this catalog: there's no archive. The first time you query a competitor is the first data point you have on them — there's no way to see what they charged last month before you started watching.
Which endpoint should you use for which job?
| Endpoint | Input | Price | Best for |
|---|---|---|---|
| Google Shopping | A category/product keyword | $0.003 / result | Discovering who's selling a product |
| Amazon Products | Product URLs/ASINs, or a keyword search | $0.0015 / product | Full detail on an Amazon listing |
| Shopify Products | Store URL, or a single product URL | $0.001 / product | Full detail on a competitor's own storefront |
FAQ
No. That post watches your own product across channels you already sell on. This one starts from a category you don't yet know the sellers in, using Google Shopping to find competitors before pulling detail on any of them.
A summary — 10 fields, enough to see who's selling and roughly what they charge. For full detail (discount status, stock, review breakdown) you follow the listing's URL into Amazon Products or Shopify Products.
You still get its title, merchant name, and price from the Google Shopping result itself — you just can't pull the deeper detail call for it, since that step only covers Amazon and Shopify listings.
Live on every call across all three endpoints. Nothing is cached — each pull reads the current state of the search results or listing page at the moment you ask.
