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pangolinfo

Amazon All-in-One Scrape MCP

Official
by pangolinfo
OverviewSchemaRelated ServersScoreDiscussions(1)
TypeScript
Hybrid

list_bestsellers

Retrieve the top 50 best-selling products in any Amazon category, including 24-hour rank changes, to track category leadership and identify trending products.

Instructions

[Amazon Best Sellers] Top-50 ranking for a category with 24h rank deltas. Use when: user says "X category bestsellers" / "who's #1 in X" / "any new entrants climbing" / "benchmark top sellers"; setting baseline products during niche scouting; tracking category leadership in competitor radars. Don't use: for new arrivals (use list_new_releases); for full category listings beyond top 50 (use list_category_products); when you only have a keyword (use search_categories first). Returns: data.json[0].data.{ reftag, recsList } — recsList is a JSON-string array (parse twice); each row { id, metadataMap.{ render.zg.rank, currentSalesRank, percentageChange, twentyFourHourOldSalesRank } }. Pair with: ↑ categorySlug from user or scene inference (e.g. 'electronics' / 'home-garden' / 'beauty'); ↓ feed id (ASIN) into get_amazon_product for single-product deep-dive. Cost: ~1 point/call, ~5s. Tips: categorySlug is the hyphenated English slug in amazon.com/Best-Sellers URL paths.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
categorySlugYesAmazon Best Sellers category slug (lowercase, hyphenated). Examples: 'electronics', 'home-garden', 'beauty', 'toys-and-games'. Find these in the URL path on amazon.com/Best-Sellers.
siteNoAmazon marketplace. Defaults to amz_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 Top-50 ranked ASIN list. Use 'markdown' for the rendered page text.json

Schema Changelog

Changes observed during successful MCP inspections. Dates show when Glama detected each change.

  1. Changed4 schema fields changedv0.7.3
    • changedInput schema / properties / categorySlug / description
      Previous value: -"Amazon Best Sellers 类目 slug（小写英文短横线），如 'electronics'、'home-garden'、'beauty'、'toys-and-games'。可以从 amazon.com/Best-Sellers 顶部导航的 URL 路径里读到。"New value: +"Amazon Best Sellers category slug (lowercase, hyphenated). Examples: 'electronics', 'home-garden', 'beauty', 'toys-and-games'. Find these in the URL path on amazon.com/Best-Sellers."
    • changedInput schema / properties / format / description
      Previous value: -"返回格式。默认 'json'——结构化 Top-50 ASIN 排名列表。需要原始页面阅读时切 'markdown'。"New value: +"Response format. Defaults to 'json' — structured Top-50 ranked ASIN list. Use 'markdown' for the rendered page text."
    • changedInput schema / properties / site / description
      Previous value: -"Amazon 站点。默认 amz_us。"New value: +"Amazon marketplace. Defaults to amz_us."
    • changedInput schema / properties / zipcode / description
      Previous value: -"邮编，必须匹配 site 站点所在国家（amz_us → 美国邮编，amz_jp → 日本邮编 …）。可选；不传时后端会从对应国家邮编池随机挑一个。跨国邮编（如 amz_us + 日本邮编）会被后端拒绝。Examples: 10001 (NY) / 90001 (LA) / 100-0001 (Tokyo)."New value: +"ZIP 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)."
  2. Changed1 schema field changedv0.7.2
    • changedInput schema / properties / format / description
      Previous value: -"返回格式。默认 'json'——结构化 Top-100 ASIN 排名列表。需要原始页面阅读时切 'markdown'。"New value: +"返回格式。默认 'json'——结构化 Top-50 ASIN 排名列表。需要原始页面阅读时切 'markdown'。"
  3. First observedv0.2.1

TDQS

A4.7/5.0
Behavior4/5

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

With no annotations, the description carries the full burden. It discloses the cost (~1 point, ~5s), response structure details (including nested JSON), and behavior of the zipcode parameter (optional, random when omitted). It could mention rate limits or authentication, but the provided information is sufficient for safe invocation.

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 exceptionally well-structured: a bold summary, then clear 'Use when', 'Don't use', 'Returns', 'Pair with', and 'Cost/Tips' sections. Every sentence adds value without redundancy. It is packed with information while remaining easy to scan.

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?

Despite having no output schema, the description thoroughly explains the return value structure, including the need to parse recsList twice and the fields within each row. It also covers cost, tips, and parameter behavior. For a tool with 4 parameters, this is 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 coverage is 100%, so the baseline is 3. The description adds value by explaining how to find the categorySlug (via URL), the meaning of the zipcode parameter with examples, and the purpose of the format parameter. This extra context elevates the score above the 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?

The description opens with a clear statement: 'Top-50 ranking for a category with 24h rank deltas.' It specifies the resource (Amazon Best Sellers), the verb (list), and key features (rank, deltas). It also distinguishes from siblings like list_new_releases and list_category_products, making the purpose unmistakable.

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?

The description provides explicit 'Use when' scenarios (e.g., 'user says X category bestsellers'), explicit 'Don't use' cases with alternatives (e.g., 'for new arrivals use list_new_releases'), and pairing suggestions with other tools. Tips for obtaining the categorySlug and cost/time estimates further guide appropriate use.

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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