Canopy API alternative

A Canopy API alternative with a warehouse behind it.

Product History <100ms Cached Responses Starting from $0.15 / 1k

Canopy is one of the better-liked Amazon APIs — clean docs, REST and GraphQL, honest pricing. But it still scrapes live per request, the free tier is 100 calls a month, and volume pricing climbs to $400/mo territory fast. We answer from a continuously refreshed 24M+ product warehouse in under 100ms, include multi-seller offers and price and stock history, cover Walmart in the same schema, and stay cheap at volume. Try the live demo.

Get Logimu access — API or dashboard

14-day money-back guarantee. $19 buys 25,000 credits a month: 25,000 live product scrapes with every seller on the listing, 50,000 stored lookups with rank, seller and Buy Box history, or 500,000 lookups of the history alone. Failed requests are never billed.

Start for $19/month Check your products in the demo

✓Best products in each matching category
✓Warehouse product data with history
✓Live scrape for current Amazon data
✓Continuously refreshed warehouse of 24M+ products
✓Bulk: up to 20,000 ASINs per batch, priced before you run
✓11 Amazon marketplaces + US Walmart
✓Warehouse answers by default — live scrape only when you ask

Live demo · no signup

Search your own products. See what the API returns.

The demo doubles as a coverage check: enter one of your ASINs, a barcode, a keyword or an Amazon product link. A product we hold shows its full record and history; one we don’t hold yet is fetched live from Amazon.

Start for $19/month

Live proof · derived intelligence

The operator network behind a brand, live.

This is the real Nike seller network — every brand below shares Amazon buy-box sellers with Nike, drawn from our observed daily record. The Logimu API serves exactly this object: GET /v1/brand/network?brand=Nike&country=us returns the nodes[] and weighted edges[] you see drawn here, one credit per hop. Hover a brand for its numbers; click one to recenter; type any brand to map it.

Node colour is the brand’s heat (seller pressure: how many sellers per listing and how fast that is rising), size is its catalogue, distance is how many sellers two brands share. Counts and shares from observed buy-box data, refreshed daily — never estimates. Available on every paid plan. Endpoint reference →

Side-by-side comparison.

	Logimu	Canopy API
Architecture	Maintained warehouse index	Live scrape per request
Typical search response	under 100 ms	Seconds — scrape at request time
Result shape	Ranked groups, price tiers, brand facets	Raw results
Price / BSR / seller history	BSR since Oct 2023 and the daily Buy Box price since Nov 2023 (US) — same API	Not held
Multi-seller offers & seller identity	Standard — full list, inside the half-credit record	Limited
Walmart	Yes, same schema	No — Amazon only
Free to try: live demo + MCP, no account	Free tier: 100 requests/mo	100 requests/mo
Cost at volume	Published prices, cheaper at scale	~$400/mo at 100k requests

Credit where due: Canopy's docs and developer experience are genuinely good, and a live scrape fetches the page at request time. If purchase-moment accuracy on arbitrary long-tail ASINs is your whole use case, that architecture has a place — our on-demand fresh fetch covers it case by case.

Where we differ, in practice.

Barcode lookup Pass any UPC, EAN, GTIN or ISBN-13 instead of an ASIN — /v1/product?gtin=, /v1/offers?gtin= or a bare barcode as the /v1/shopping query. The product endpoints find any barcode, inside the marketplace you asked for: from the listings we observe, the same product on another Amazon marketplace, or Amazon’s own search (organic results only), and every answer says how and whether the barcode is printed on that listing. A barcode that maps to several ASINs returns every match; one nothing resolves is never billed.
Speed you can put in an interactive UI A search that answers in under 100ms works in an autocomplete, an agent tool call, or a page render. A live scrape that answers in seconds doesn't. If your product search sits in front of a user or an LLM, warehouse speed is the difference in kind, not degree.
History nobody scrapes live Price, stock and seller-count history attached to any product, included in the call. A per-request scraper structurally cannot offer this — it wasn't there when the request came in. We were.
Volume economics Our data comes from a warehouse we already maintain, so marginal cost per read is near zero and pricing stays flat as you scale. Per-request scrape providers carry per-request proxy costs, and their price ladders show it.
Two marketplaces beyond Amazon US amazon.co.uk, amazon.de, amazon.ca, amazon.com.au, and walmart.com in the same API and schema today, with more Amazon marketplaces shortly — one integration instead of many.

What a product response includes.

One ASIN in, the full record out — /v1/product.

Current snapshot Price, BSR, rating, review count, stock state, UPC, parent ASIN, brand stats — and Amazon's own "bought in past month" figure where it publishes one.
Every seller, in the same call The full live offer list is standard, not a separate endpoint: seller name and ID, price, FBA and Prime flags, feedback score, and buy-box days. Gathering offers is the slow part of any live scrape, which is why most APIs bill them separately.
Price and stock history The full price series plus price-change and stock-change events, in the base call.
Rank history, per category Add bsr_history=true for daily rank in every category the product sits in. Included in the record, like the seller history below.
Seller history — who held the buy box, and when Add offer_history=true for a buy-box timeline plus a per-seller price series, each with first seen, last seen and buy-box days. Included in the record too.
Warehouse or live scrape — your call mode=cache answers in under 100ms for half a credit, batch or single call. mode=live scrapes the listing on demand when it has to be current, for one credit. Failed scrapes are never billed.

Eleven Amazon marketplaces plus US Walmart, in one schema.

Beyond the product record

Derived intelligence: what the observations add up to.

Every product we observe is also an observation about a brand, a seller and a category. The same key serves those aggregates — computed daily from observed buy-box data, never estimated, with data_source on every answer.

Brand dossier — GET /v1/brand: how many sellers win the buy box on a brand, Amazon’s own share, FBA penetration, seller concentration and churn, trend grades, benchmarks against its category, the top sellers; monthly history on request.
Seller map — GET /v1/brand/network: the brands connected to a brand because the same third-party sellers win the buy box on both — weighted edges and node metrics, one hop per call. See it drawn live on the homepage →
Operator footprint & category landscape — GET /v1/seller/brands, /v1/seller/network, /v1/category: every brand a seller was observed winning on, the sellers that win beside it, and a category’s size, Amazon share, FBA share and concentration — plus ranked lists of brands, sellers and categories.

1 credit per record, 1 per page of 25 rows, lookups and misses free; part of every paid plan. Endpoint reference →

Canopy’s GraphQL queries return product, search-result and category-page objects, one page per query; there is no brand, seller-network or category-level aggregate to ask for.

Related.

Amazon stats inside Claude & ChatGPT.

Prefer tool calls in your assistant over raw API calls? Webotee AI Connect puts this same Amazon data to work inside Claude & ChatGPT — product search and shopping lookups like this API’s, plus a wide set of Amazon market stats and research tools: brand intelligence, seller networks, niche & category discovery, and AI-assisted evaluations grounded in observed data. Built by the team behind Logimu; plans from $19/month.

Compare us on your real workload.

Sign up — your key is issued instantly — then run your Canopy query mix against our endpoints, and compare the latency, the payloads, and the monthly bill.

Start for $19/month