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pangolinfo

Amazon All-in-One Scrape MCP

Official

scrape_url

Scrape Amazon pages that standard tools don't support. Provide a content fragment or a full URL with filters, sorting, and pagination to extract structured data.

Instructions

[Generic Amazon scrape — power-user escape hatch] Scrape pages the 5 purpose-built tools don't cover. Two input modes (pick one): ① content=bare fragment (keyword / nodeId / sellerId / ASIN) + site — backend builds a basic URL per parserName. content mode carries NO filter/sort/pagination — it's just the bare fragment. Best for simple pages when you only have the fragment. ② url=full Amazon link — put ANY filter/sort/pagination into this url (the only way, since content mode can't). Filter syntax examples: price $25-50 → '/s?k=earbuds&low-price=25&high-price=50'; sort by reviews → '&s=review-rank'; paginate → '&page=2'; category+price → '/s?i=aps&rh=n%3A172282&fs=true&low-price=25'. Use when: a standard tool can't build the target URL — "search X but only $25-50" / "results sorted by reviews" / "category filtered by price"; or the user already has a specific Amazon link. For any filtering, use url mode. Don't use: when a purpose-built tool fits — plain keyword search → search_amazon, single ASIN → get_amazon_product, seller → list_seller_products, category ranks → list_bestsellers/list_new_releases. Returns (format='json'): data.json[0].data.{ ... results[] ... }, shape depends on parserName. ⚠️ If content/url doesn't match parserName, the backend returns data.{ status_code, rawHtml, url } (unparsed). Pair with: ↓ feed asin into get_amazon_product / get_amazon_reviews. Cost: ~1 point/call, ~5s. ⚠️ Pass exactly one of content / url (both or neither errors); filtering/pagination requires url mode; parserName must match the page type.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
parserNameYesParser deciding how the backend extracts the page AND builds the URL from content. Must match the page type: amzKeyword=keyword search (content=keyword) / amzProductOfCategory=category (content=nodeId) / amzProductOfSeller=seller storefront (content=sellerId) / amzProductDetail=single product (content=ASIN) / amzBestSellers / amzNewReleases / amzReviewV2=reviews / amzFollowSeller=follow-seller / amzVariantAsin=variant.
contentNoBare fragment (backend builds the URL per parserName). Pass this OR url. Examples: 'wireless earbuds' (amzKeyword) / '172282' (nodeId for amzProductOfCategory) / 'ATVPDKIKX0DER' (sellerId for amzProductOfSeller) / 'B09B8V1LZ3' (ASIN for amzProductDetail). Users/AI usually only have the fragment — prefer this.
urlNoFull Amazon URL (https://). Pass this OR content. Use when you already have a ready link (e.g. a filtered/sorted SERP copied from the browser). Example: 'https://www.amazon.com/s?k=earbuds&rh=p_36%3A2500-5000&s=review-rank'. Must match parserName.
siteNoAmazon site (in content mode the backend picks the domain from this). Defaults to amz_us. Optional in url mode (the URL already has the domain).amz_us
formatNoResponse format. Defaults to 'json' (structured results). Use 'markdown' for the rendered page text.json
zipcodeNoZIP code matching the site's country. Optional; backend picks one if omitted.
Behavior5/5

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

Despite no annotations, the description discloses behavioral traits: input modes, that content mode carries no filter/sort/pagination, that exactly one of content/url must be provided, that parserName must match the page type, the return shape, error behavior when mismatch, cost (~1 point, ~5s), and pairing advice. This is thorough disclosure.

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 well-structured with sections (①②), bullet points, and clear warnings. Every sentence adds value; it is efficient and not verbose. The structure makes it easy to parse quickly.

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 the tool's complexity (6 parameters, 9 parserName options, two modes), the description covers all necessary aspects: input modes, limitations, prerequisites (parserName match), return shape, cost, pairing with other tools, and error behavior. No gaps are apparent.

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?

Schema coverage is 100%, but the description adds significant meaning beyond the schema: it explains the two input modes with examples, when to use each, filter syntax examples for url, parserName mappings, optionality of site and zipcode, and default values. This far exceeds the schema's descriptions.

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 clearly states that this is a generic Amazon scrape for pages not covered by 5 purpose-built tools, and explicitly names those sibling tools. It distinguishes itself as a 'power-user escape hatch' with two input modes, making the purpose very specific and unambiguous.

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 guidance on when to use each mode (content vs url), including filter/sort/pagination requirements, and explicitly states when not to use it (when a purpose-built tool fits), listing exact alternatives like search_amazon, get_amazon_product, etc. This is comprehensive.

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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