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Byski

mcp-searchapi

by Byski

google_shopping

google_shopping

Search for products across retailers to compare prices, sellers, and ratings. Use for price comparison and availability checks.

Instructions

Search Google Shopping for products with prices, sellers and ratings. Use this for price comparison and product availability questions.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
glNoTwo-letter country code for the search, for example 'ie', 'us', 'gb'.
hlNoTwo-letter language code for the results, for example 'en', 'fr'.
numNoHow many results to request from the engine. Defaults to the engine's own default.
pageNoPage number for paginating through results. Starts at 1.
limitNoMaximum results to return to you. Kept low by default because search payloads are large; raise it only when you genuinely need more.
queryYesThe product to search for.
locationNoGeographic location to search from, as 'City,Country' (for example 'Dublin,Ireland'). Results are localised to this place.
Behavior2/5

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

No annotations are provided, so the description must fully disclose behavioral traits. It only states what is searched and returned, but does not mention localization effects (despite location parameter), pagination, result limits, price currency, or potential variability in availability/ratings. This is a significant transparency gap.

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 two sentences with no filler. The first sentence front-loads the core action ('Search Google Shopping for products with prices, sellers and ratings') and the second adds a clear use case. Every word earns its place.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness4/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

No output schema exists, so the description should hint at return content; 'products with prices, sellers and ratings' does that. However, it omits important behavioral context like pagination, result limits, and localization effects that the schema documents but the description does not reinforce. For a straightforward search tool it is mostly complete, but lacks edge-case disclosure.

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

Parameters3/5

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

Schema coverage is 100% with detailed descriptions for all 7 parameters, so the baseline is 3. The tool description adds no additional meaning beyond the schema, but the schema already does a solid job, so a mid score is appropriate.

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 the verb 'Search' and resource 'Google Shopping', and specifies the returned data: 'products with prices, sellers and ratings'. It also differentiates from siblings by saying 'Use this for price comparison and product availability questions', which is distinct from generic Google search tools.

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

Usage Guidelines4/5

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

The description provides explicit usage context: 'Use this for price comparison and product availability questions'. However, it does not mention when not to use the tool or name alternative tools, so it lacks full exclusion guidance.

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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