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pangolinfo

Amazon All-in-One Scrape MCP

Official

search_amazon

Run Amazon keyword searches to retrieve first-page ASIN lists with product details including price, rating, and sales. Use for identifying top results and competitors for any product keyword.

Instructions

[Amazon SERP scrape] Run a real Amazon keyword search and return the first-page ASIN list. Use when: user says "search Amazon for X" / "who sells X" / "top results for keyword X" / "competitors for X"; or you need a list of ASINs for a keyword as upstream input to deeper analysis. Don't use: for a single ASIN detail (use get_amazon_product); for category bestseller ranks (use list_bestsellers); for Google/external demand on the term (use ai_search or keyword_trends). Returns (format='json', default): data.json[0].data.{ pageIndex, nextPage, keyword, results[{ asin, title, price, star, rating, sales, badge, rank, sponsored, image, delivery }] } — ~22 rows/page. Pagination: use the 'page' param (default 1, 1-based); response's 'nextPage' holds the next page number, 'nextPage=null' means last page reached. Pair with: ↓ feed results[].asin into get_amazon_product / get_amazon_reviews for single-product deep-dive; ↓ feed the same keyword into keyword_trends to compare in-site vs external demand. Cost: ~1 point/page, ~5s. Only paginate when the user explicitly asks for more / Top-N (N>22) / all results — otherwise the first page is enough.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
keywordYesSearch keyword. Examples: 'wireless earbuds' / 'stanley quencher' / 'iphone 16 case' / 'kitchen knife set'.
siteNoAmazon marketplace. Defaults to 'amz_us' (US).amz_us
zipcodeNoZIP code that must match the site country (amz_us → US zip, amz_jp → JP zip, ...). Optional; backend picks a random one from the per-country pool when omitted. Cross-country zips (e.g. amz_us + JP zip) are rejected by the backend. Examples: 10001 (NY) / 90001 (LA) / 100-0001 (Tokyo).
formatNoResponse format. Defaults to 'json' — structured search rows (asin, title, price, star, rating, sales, badge, rank, ...) ready for programmatic use. Use 'markdown' if you want the rendered SERP text instead.json
pageNoPage number, 1-based. ~22 ASINs per page. Use response's pageIndex/nextPage to decide whether to continue: nextPage holds the next page number; nextPage=null (or absent) means last page reached. **Only paginate when the user explicitly asks for more / Top-N where N exceeds one page / all results** — otherwise the first page is enough.
Behavior5/5

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

With no annotations, the description fully covers behavioral traits: pagination details (nextPage, page param), response structure, cost (~1 point/page, ~5s), and when to paginate (only on explicit user request). No contradictions.

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 dense and well-structured, front-loading purpose and usage. While every sentence is informative, it is slightly verbose due to extensive usage guidelines and pairing info. Could be more concise but still effective.

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?

Given no output schema, the description covers return structure, pagination, cost, and pairing with siblings. All parameter details are thorough, and the context of sibling tools is addressed. Complete for a search tool.

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

Parameters5/5

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

All 5 parameters have schema descriptions (100% coverage). The description adds value by explaining format choices, zipcode cross-country rejection, and pagination guidance beyond schema.

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 begins with a clear verb and resource: 'Run a real Amazon keyword search and return the first-page ASIN list.' It also distinguishes from siblings by explicitly listing tools for single ASIN detail, bestseller ranks, and external demand.

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

Usage Guidelines5/5

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

Provides explicit when-to-use triggers (e.g., 'user says "search Amazon for X"') and when-not-to-use alternatives (e.g., 'Don't use: for a single ASIN detail (use get_amazon_product)'). Also includes pairing instructions for deeper analysis.

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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