list_seller_products

com.pangolinfo/amazon-mcp · Verify this server

[Amazon seller storefront] List all listings under a merchant ID, paginated (24 rows/page). Use when: user says "show me this seller's products" / "how many SKUs does store X carry" / "competitor storefront category breadth" / "what is this seller pushing" / "research a seller's catalog strategy". Don't use: without a merchant ID (find 'sold by' link on any product PDP first); for a single product (use get_amazon_product). Returns: data.json[0].data.{ pageIndex, maxPage, nextPage, results[{ asin, title, price, star, rating, rank, img }] } — 24 rows/page. **Every row carries rank** (its display order in the storefront, ≈ that seller's in-store popularity ranking) plus star/rating, so **this single call is enough to rank and tabulate the seller's listings — no need to re-fetch each PDP**. **Two pagination modes**: ① page locates a specific page (default 1); ② pageCount accumulates the first N pages in one call (N≤3, flat-merged into the same results). When pageCount>1, pageIndex/nextPage are blanked (pages already merged). **Category filter**: categoryId filters the seller's products by category. Pair with: ↑ sellerId usually from get_amazon_product's seller.id field, or from amazon.com/sp?seller=... URL; categoryId extractable from the storefront URL's rh=n:<id>; ↓ feed asin into get_amazon_product to deep-dive hero products. **Chaining pitfall — "what does this seller carry + sort by sales/rank"**: ❌ Do NOT "run get_amazon_product on every ASIN to pull each small-category BSR, then sort" — a storefront often has dozens-to-hundreds of SKUs; fanning out one PDP per ASIN hits the 2-QPS rate wall, bills N times, and blows the Fast-tier budget. ✅ Correct: **the results[] from one call (or pageCount≤3) already carry rank; sort by rank ascending for the in-store order and tabulate with star/rating**. Only when the user explicitly wants exact global small-category BSR should you run get_amazon_product on a **small head set (e.g. the top 5-10 pre-filtered by list rank)** to read bestSellersRankItems[], batched at ≤2 concurrent — never fan out across the whole store. Cost: ~1 point/page, ~5s; pageCount=N billed by pages actually crawled (failed pages refunded). Tips: use pageCount to grab the full multi-page SKU set in one shot (max 3 pages); use page to view one specific page; the first page is enough to glance at what the store sells. For sorting, prefer results[].rank (free, already in this response) — don't fan out PDP fetches just to sort. Amazon first-party sellerId = 'ATVPDKIKX0DER'.