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amazon_product_scraper

Read-only

Scrape Amazon product listings with configurable domains, locales, currencies, and parsing options to obtain accurate pricing data.

Instructions

Scrape Amazon products.

Supports content parsing, different user agent types, domain, geolocation, locale parameters and different output formats. Supports Amazon specific parameters such as currency and getting more accurate pricing data with auto select variant.

Input Schema

TableJSON Schema

Name	Required	Description
`parse`	No	Should result be parsed. If the result is not parsed, the output_format parameter is applied.
`query`	Yes	Keyword to search for.
`domain`	No	Domain localization for Google. Use country top level domains. For example: - 'co.uk' for United Kingdom - 'us' for United States - 'fr' for France
`locale`	No	Set 'Accept-Language' header value which changes your Google search page web interface language. Examples: - 'en-US' for English, United States - 'de-AT' for German, Austria - 'fr-FR' for French, France
`render`	No	Whether a headless browser should be used to render the page. For example: - 'html' when browser is required to render the page.
`currency`	No	Currency that will be used to display the prices.
`geo_location`	No	The geographical location that the result should be adapted for. Use ISO-3166 country codes. Examples: - 'California, United States' - 'Mexico' - 'US' for United States - 'DE' for Germany - 'FR' for France
`output_format`	No	The format of the output. Works only when parse parameter is false. - links - Most efficient when the goal is navigation or finding specific URLs. Use this first when you need to locate a specific page within a website. - md - Best for extracting and reading visible content once you've found the right page. Use this to get structured content that's easy to read and process. - html - Should be used sparingly only when you need the raw HTML structure, JavaScript code, or styling information.
`user_agent_type`	No	Device type and browser that will be used to determine User-Agent header value.
`autoselect_variant`	No	To get accurate pricing/buybox data, set this parameter to true.

Output Schema

TableJSON Schema

Name	Required	Description	Default
`result`	Yes

Schema Changelog

Changes observed during successful MCP inspections.

Addedv0.8.1May 6, 2026

TDQS

A3.5/5.0

Behavior3/5

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

The readOnlyHint annotation already signals a safe read operation. The description adds some functional context (content parsing, output formats, user agents) but does not disclose potential side effects, rate limits, or return behavior beyond what the schema implies. The annotation is not contradicted, and the added detail provides marginal value.

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

Conciseness5/5

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

The description is two sentences with the purpose front-loaded. The second sentence compactly enumerates capabilities without redundancy. Every word contributes to the overall understanding, and there is no filler or unnecessary detail.

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

Completeness3/5

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

Given the tool's complexity (10 parameters, 1 required) and rich schema/output schema, the description gives a reasonable high-level overview. However, it does not mention limitations, pagination, or differentiate from similar tools like amazon_search_scraper. The output schema and annotations fill in some gaps, making it minimally complete but not richly contextual.

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?

The input schema has 100% description coverage for all 10 parameters, so the schema carries the full semantic burden. The description groups parameters into categories and highlights Amazon-specific ones (currency, autoselect_variant), adding conceptual organization but no new factual information beyond the schema.

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

Purpose4/5

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

The description clearly states the tool scrapes Amazon products, providing a specific verb and resource. It does not explicitly differentiate from sibling tools like amazon_search_scraper or universal_scraper, so it stops short of a 5.

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 implies the tool is for scraping Amazon products but gives no explicit guidance on when to use it vs. alternatives. It lacks when-to-use/when-not-to-use criteria or exclusion notes, leaving the agent to infer based on the name and general purpose.

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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