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BACH-AI-Tools

Real Time Amazon Data MCP Server

product_offers

Retrieve Amazon product details and offers for ASINs, with pagination, country selection, and filters for condition and delivery options.

Instructions

Get all Amazon product details as available via the Product Details endpoint with an additional offers array containing product offers (The first offer in the array is the pinned offer returned by the Search endpoint). Supports pagination using the page and limit parameters.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
asinYesProduct ASIN for which to get offers. Supports batching of up to 10 ASINs in a single request, separated by comma. Example: B08PPDJWC8,B07ZPKBL9V,B08BHXG144 Note that each ASIN in a batch request is counted as a single request against the plan quota.
pageNoResults page to return. Default: 11
limitNoMaximum number of offers to return. Default: 100100
fieldsNoA comma separated list of product and offer fields to include in the response (field projection). By default all fields are returned. Example: product_price,product_information,product_condition,ships_from
countryNoSets the Amazon domain, marketplace country, language and currency. Default: US Allowed values: US, AU, BR, CA, CN, FR, DE, IN, IT, MX, NL, SG, ES, TR, AE, GB, JP, SA, PL, SE, BE, EG
deliveryNoFind products with specific delivery option, specified as a comma delimited list of the following values: PRIME_ELIGIBLE,FREE_DELIVERY. Examples: FREE_DELIVERY PRIME_ELIGIBLE,FREE_DELIVERY
languageNoThe language of the results. In case not specified, results will be returned in the default domain language. Supported languages per country: US: en_US, es_US AU: en_AU BR: pt_BR CA: en_CA, fr_CA FR: fr_FR, en_GB DE: de_DE, en_GB, cs_CZ, nl_NL, pl_PL, tr_TR, da_DK IN: en_IN, hi_IN, ta_IN, te_IN, kn_IN, ml_IN, bn_IN, mr_IN IT: it_IT, en_GB MX: es_MX NL: nl_NL, en_GB SG: en_SG ES: es_ES, pt_PT, en_GB TR: tr_TR AE: en_AE, ar_AE GB: en_GB JP: ja_JP, en_US, zh_CN SA: ar_AE, en_AE PL: pl_PL SE: sv_SE,
product_conditionNoFind products in specific conditions, specified as a comma delimited list of the following values: NEW, USED_LIKE_NEW, USED_VERY_GOOD, USED_GOOD, USED_ACCEPTABLE. Default: NEW, USED_LIKE_NEW, USED_VERY_GOOD, USED_GOOD, USED_ACCEPTABLE Examples: NEW,USED_LIKE_NEW USED_VERY_GOOD,USED_GOOD,USED_LIKE_NEW
autoselect_variantNoExample value:
Behavior4/5

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

No annotations are provided, so the description carries the burden of behavioral disclosure. The description clearly states pagination support, the pinned-offer behavior (first offer comes from Search endpoint), and batching semantics. It does not disclose rate limits, what happens with invalid ASINs, or whether the operation is read-only, but for a query tool the disclosed behaviors are fairly complete.

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?

The description is a single focused sentence that covers the endpoint, the key offers-array behavior, and pagination. It is front-loaded with the main purpose and adds the important pinned-offer distinction. No wasted words.

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

Completeness4/5

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

The tool has 9 parameters (though most are scoping/filter options), no output schema, and no annotations. The description explains the core behavior including the important 'first offer is the pinned offer from Search' detail, plus pagination. Given no output schema, it could mention what the response contains, but the description references the Product Details endpoint as context. For a multi-parameter offers tool, this is reasonably complete.

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 description coverage is 100%, so the schema already documents all 9 parameters well. The description adds the pagination semantics ('page' and 'limit') reference and the batching behavior that clarifies the asin param. It successfully complements rather than repeats the schema, which meets the baseline-3-plus expectation.

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?

The description uses a specific verb-resource structure: 'Get all Amazon product details... with an additional offers array containing product offers'. It clearly identifies the endpoint, what it returns, and distinguishes itself from siblings like product_details (which presumably lacks the offers array) and product_reviews. The pinned-offer clarification further disambiguates.

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

Usage Guidelines3/5

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

The description implicitly establishes when to use this tool (when you need offers alongside product details) versus product_details alone, but it does not explicitly name alternatives or say when not to use it. The pinned-offer note and pagination hints give some usage context, but no explicit when/when-not guidance is present.

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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