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Amazon Research JS: product database/query API

nexscope_data_js_product_database_query
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Amazon Research JS: product database/query API.

Input Schema

NameRequiredDescriptionDefault
sortNoSort field. Allowed values: `name`, `-name`, `category`, `-category`, `revenue`, `-revenue`, `sales`, `-sales`, `price`, `-price`, `rank`, `-rank`, `reviews`, `-reviews`, `lqs`, `-lqs`, `sellers`, `-sellers`, `-`. A leading `-` sorts in descending order.name
maxLqsNoHighest LQS score (1-10)
maxNetNohighest net profit
minLqsNoMinimum LQS score (1-10)
minNetNominimum net profit
maxRankNoHighest BSR Rank
minRankNoLowest BSR Rank
maxPriceNohighest price
maxSalesNoHighest monthly sales
minPriceNolowest price
minSalesNoMinimum monthly sales
maxRatingNoHighest rating (1.0-5.0)
maxWeightNoMaximum weight (lbs)
minRatingNoLowest rating (1.0-5.0)
minWeightNoMinimum weight (lbs)
needCountNoThe total number of results to be returned, automatic paging within the API
categoriesNoMain category names, separated by commas, must match the standard category names of the corresponding site. Examples of US sites: Appliances, Arts Crafts & Sewing, Automotive, Baby, Beauty & Personal Care, Books, CDs & Vinyl, Cell Phones & Accessories, Clothing Shoes & Jewelry, Collectibles & Fine Art, Computers, Digital Music, Electronics, Garden & Outdoor, Grocery & Gourmet Food, Handmade, Health Household & Baby Care, Home & Kitchen, Industrial & Scientific, Kindle Store, Kitchen & Dining, Movies & TV, Musical Instruments, Office Products, Pet Supplies, Sports & Outdoors, Tools & Home Improvement, Toys & Games, Video Games, etc.; other sites have corresponding local category names
maxRevenueNohighest monthly income
maxReviewsNoHighest number of comments
maxSellersNoMaximum number of sellers
minRevenueNominimum monthly income
minReviewsNoMinimum number of comments
minSellersNoMinimum number of sellers
marketplaceYesTarget market code. Optional values: `us`, `uk`, `de`, `in`, `ca`, `fr`, `it`, `es`, `mx`, `jp`us
sellerTypesNoSeller types, separated by commas. Optional values: `amz` (Amazon self-operated), `fba`, `fbm`
maxUpdatedAtNoData update deadline (YYYY-MM-DD)
minUpdatedAtNoData update start date (YYYY-MM-DD)
productTiersNoProduct size hierarchy, separated by commas. Optional values: `oversize`, `standard`
excludeKeywordsNoTitle/ASIN excluded keywords, comma separated, up to 100 items, each item can be up to 50 characters
includeKeywordsNoTitle/ASIN contains keywords, comma separated, up to 100 items, each item can be up to 50 characters
excludeTopBrandsNoWhether to exclude top brands
excludeUnavailableProductsNoWhether to exclude unpurchasable items

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observed

TDQS

C2.2/5.0
Behavior2/5

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

Annotations already declare readOnlyHint=true, destructiveHint=false, openWorldHint=true, so the safety profile is covered. The description adds nothing beyond that: no mention of result caps, how needCount/paging behaves, data freshness tied to updatedAt fields, or quota/cost considerations for a 32-parameter query endpoint.

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

Conciseness2/5

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

It is very short, but conciseness is not achieved through condensation of useful content — it is a title-like fragment with zero substantive information. Nothing is front-loaded because nothing is said.

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

Completeness2/5

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

A 32-parameter query tool with no output schema and many similar Amazon siblings needs far more than a restated title. The schema carries the parameter burden and annotations cover safety, but an agent gets no help on returned fields, result semantics, or sibling selection.

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

Parameters3/5

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

Schema description coverage is 100%, so every parameter including marketplace, categories, keyword filters, and min/max ranges is documented in the schema itself. The description provides no additional parameter meaning, which is acceptable but the baseline of 3 applies.

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

Purpose2/5

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

The description is 'Amazon Research JS: product database/query API,' which is essentially a restatement of the title and tool name. It does not say what the query returns (product list with sales, revenue, LQS metrics filtered by ranges) or how it differs from siblings like nexscope_amazon_product_database_search or nexscope_data_js_sales_estimates_query.

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

Usage Guidelines2/5

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

No guidance on when to use this tool versus the many adjacent Amazon/JS product tools in the sibling list. The only cue is the parameter names, which imply attribute-range filtering, but the description never states that or any exclusions.

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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