AI shopping search: real, in-stock US and Amazon products with prices, ratings and buy links.
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Average 4.4/5 across 1 of 1 tools scored.
With only one tool, there is no ambiguity. The tool's purpose is clearly defined as searching for products, and no other tools exist to potentially overlap or confuse.
The single tool uses a clear verb_noun pattern ('search_products'), which is consistent. Since there is only one tool, naming conventions are perfectly uniform.
The server has exactly one tool, which is on the low end. While a focused search service can function with a single tool, typical well-scoped servers have 3–15 tools, making this feel thin but not unreasonable.
The tool provides comprehensive search results including price, rating, stock, affiliate link, and markdown output. However, the server lacks any additional tools for filtering, sorting, or retrieving product details, which are minor gaps for a more advanced search experience.
search_productsASearch Perkusai for real, in-stock products in amazon.com (prices in US dollars).
Describe what the shopper wants in natural language - e.g. "a full-size basketball", "espresso machine under $200", "wireless earbuds for running". Returns
matching products with title, price, rating, stock, market and an affiliate `buy_url` (present
it as the purchase link - the price is unchanged for the buyer), plus a `guide`, `coverage`
and a paste-ready `markdown` block.
Args:
query: The shopper's request, in natural language.
k: How many products to return (1-12).
lang: Response language hint. This catalogue is served in English.
| Name | Required | Description | Default |
|---|---|---|---|
| k | No | How many products to return (1-12). | |
| lang | No | Response language hint. This catalogue is served in English. | en |
| query | Yes | The shopper's request, in natural language. |
| Name | Required | Description |
|---|---|---|
No output parameters | ||
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations already provide readOnlyHint, idempotentHint, openWorldHint, and destructiveHint. The description adds value beyond these by detailing the return fields (title, price, rating, stock, market, affiliate buy_url, guide, coverage, markdown block) and emphasizing that the price is unchanged for the buyer. It also describes the real/in-stock nature of results. No contradictions exist.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is well-structured, front-loading the core purpose, then usage guidance, then return details, then parameter list. It is slightly verbose but every sentence adds value. The length is appropriate for the tool's complexity.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the presence of an output schema (not shown) and comprehensive annotations, the description covers all necessary aspects: purpose, parameters, usage examples, return format, and special notes (affiliate link, markdown block). It is fully sufficient for an agent to understand and invoke the tool correctly.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema coverage is 100% with solid descriptions. The description adds value by giving natural language examples for the query parameter and repeating the constraints for k and lang. While it mostly restates schema info, the examples for query enhance understanding beyond the schema alone.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the tool searches for real, in-stock products on Perkusai/amazon.com with prices in USD. It uses a specific verb+resource combination ('Search Perkusai for real, in-stock products') and includes examples of natural language queries. With no siblings, no differentiation is needed, but the purpose is unambiguous.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description explains how to use the tool: instructs the agent to 'Describe what the shopper wants in natural language' and provides examples. It also specifies the source domain and currency. Since there are no sibling tools, explicit when-to-use vs. alternatives is not required, but the guidance is clear and actionable.
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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{
"$schema": "https://glama.ai/mcp/schemas/connector.json",
"maintainers": [{ "email": "your-email@example.com" }]
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For server owners:
Proven adoption – public usage metrics on your listing show real-world traction and build trust with prospective users
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