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scraperapi

scraperapi-mcp-server

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amazon_search

Read-onlyIdempotent

Get parsed Amazon search results with product name, price, rating, review count, and Prime status for any keyword, enabling product discovery and price research.

Instructions

Retrieve parsed Amazon search results for a query.

    Returns structured search results — product name, price, rating, review
    count, URL, image, Prime/best-seller/sponsored flags — plus pagination,
    for a keyword search on Amazon.

    When to use:
    - Discovering products and their ASINs for a search term
    - Price/market research and catalog building across a category

    When NOT to use:
    - You already have an ASIN (use 'amazon_product' / 'amazon_offers')

    Args:
        params (AmazonSearchParams): query (required) plus optional page,
            sort_by, department, ref, tld, country_code, language, and
            output_format.

    Returns:
        str: JSON (default) or CSV containing the structured search results.

    Raises:
        ToolError: If the API key is missing, the rate limit is exceeded, or
            the request fails.
    

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
paramsYes

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
resultYes
Behavior5/5

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

Discloses return structure (product name, price, etc.), pagination, and error conditions (missing API key, rate limit, request failure). No contradiction with annotations which declare readOnlyHint, idempotentHint, not destructive.

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?

Well-structured with sections, front-loaded with purpose, and every sentence adds value. No fluff.

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?

Covers purpose, usage, return format, errors, and parameter list. Given the richness of annotations and output schema, the description is complete and aids correct invocation.

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

Parameters2/5

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

Description only lists parameter names without adding meaning beyond what the schema already provides. Schema coverage is 0%, but the description does not compensate; it merely repeats parameter names in the Args section.

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?

Clearly states the tool retrieves parsed Amazon search results for a query. Distinguishes from siblings by mentioning that if you already have an ASIN, use 'amazon_product' or 'amazon_offers'.

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?

Explicit 'When to use' and 'When NOT to use' sections. Specifies discovering products and price research as use cases, and explicitly names alternative tools for known ASINs.

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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