apiguru-amazon-data

Products listed by a seller

seller_products

Read-onlyIdempotent

Search one Amazon seller's storefront by keyword, price, brand, condition, category or deals, and get paginated product rows plus applied and available filters.

Instructions

Products listed by a seller: a storefront search. Takes the same filters as search -- query, page, sort_by, category_id, min_price / max_price, product_condition, brand, today_deals, deal_type -- and answers with filters_applied, filters_ignored and available_filters like search does. Price: $0.003 per call. Unlike seller_profile_batch, seller_id format is not pattern-validated here. metadata.total_pages says how far page goes (48 rows a page). Invalid sort_by, price, product_condition or deal_type is a free 400 that lists the allowed values.

Input Schema

TableJSON Schema

Name	Required	Description	Default
`geo`	No	Marketplace country code.	US
`page`	No	Result page, 1-based. metadata.total_pages says how far it goes.
`brand`	No	Brand name as Amazon spells it (case-insensitive), e.g. Samsung.
`limit`	No	How many the seller's products to return from this page (0 = all of them). A full page is up to 48 rows and about 54 KB, which most clients spill to a file instead of showing inline. The answer carries _truncated with the true count when it trims.
`query`	No	Optional keywords to search within this seller's storefront.
`fields`	No	Comma-separated row fields to return instead of the light set, e.g. "asin,product_title,product_price". Rows list what they left out under _omitted_fields.
`compact`	No	Return light rows: identity, price, rating, badges and one delivery_date, dropping the long delivery prose that repeats itself across three fields. false returns every field the REST API sends (roughly 3x the size).
`sort_by`	No	Result ordering.	RELEVANCE
`deal_type`	No	A specific promotion refinement: today_deals, all_discounts, coupons or buy_more_save_more. available_filters.deal_type lists the ones this marketplace has.
`max_price`	No	Highest price, in the marketplace currency.
`min_price`	No	Lowest price, in the marketplace currency; decimals such as 19.99 are fine.
`seller_id`	Yes	Restrict results to one seller's offers (Amazon seller id).
`category_id`	No	Amazon browse node id to restrict to, e.g. 172282 (Electronics on US). Take one from a best_sellers answer's available_subcategories, a product's category_path, or node= in an Amazon URL. Ids differ per marketplace.
`today_deals`	No	Only items in Today's Deals, using that marketplace's own refinement. Where a marketplace has none (amazon.fr on 2026-09-08) it is reported under filters_ignored.
`product_condition`	No	NEW, USED or RENEWED (case-insensitive). Applied with the marketplace's own condition node; where a marketplace does not offer one, the answer's filters_ignored says so and available_filters lists what it does offer.

Output Schema

TableJSON Schema

Name	Required	Description	Default
`data`	No
`success`	No
`request_id`	No

Schema Changelog

Changes observed during successful MCP inspections.

First observedv0.1.0Sep 27, 2026

TDQS

A4.6/5.0

Behavior5/5

Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

Beyond the read-only/idempotent annotations it discloses cost ($0.003 per call), pagination granularity (48 rows/page via metadata.total_pages), truncation behavior (_truncated) and the light-vs-full row size tradeoff. It also documents a distinctive behavioral trait: invalid sort_by/price/product_condition/deal_type yields a free 400 listing allowed values.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness4/5

Is the description appropriately sized, front-loaded, and free of redundancy?

Front-loaded with the purpose, then dense factual clauses on filters, cost, pagination and error behavior. Every sentence carries information, though the filter/response sentence runs long and could be split for scanability.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness5/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

For a 15-parameter open-world search with an output schema, it covers cost, paging, truncation, field projection and error handling. Return-value structure is left to the output schema, which is the correct division of labor.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters4/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Schema coverage is 100% so the baseline is 3, but the description adds cross-parameter semantics the schema lacks: how filters map to filters_applied/filters_ignored/available_filters, and that unvalidated seller_id format differs from seller_profile_batch. It does not restate most per-field syntax, so it is modestly above baseline.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Purpose5/5

Does the description clearly state what the tool does and how it differs from similar tools?

States a specific verb and resource ('Products listed by a seller: a storefront search'), which immediately separates it from generic `search` and from `seller_profile_batch`. An agent can tell what it returns and what it is scoped to without opening the schema.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines4/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

Positions the tool against siblings by noting it 'takes the same filters as search' but is scoped to one seller, and contrasts it with seller_profile_batch on seller_id validation. It does not explicitly say when to prefer it over `search` or `best_sellers`, so routing is clear but not fully spelled out.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

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