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ScrapingBot

Google search

googleSearch
Read-only

Google results as JSON: web (default), images, videos, news, shopping, places or maps (type), for any country (gl) and language (hl). Places and maps results include a cid for googleReviews. 10 credits.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
qYes
glNo
hlNo
llNoMaps/places viewport, e.g. @30.27,-97.74,12z
numNo
tbsNo
pageNo
typeNoWhat to search: web results (default), images, videos, news, shopping, places or maps.
sortByNo
autocorrectNo

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observed

TDQS

A3.7/5.0
Behavior4/5

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

Annotations already declare readOnlyHint and openWorldHint, so the description's job is to add context. It does: output format is JSON, cost is 10 credits, and places/maps results carry a cid usable with googleReviews. It omits pagination/rate-limit behavior, but the cost and cross-tool linkage are genuinely useful additions.

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?

A single dense sentence with the core purpose front-loaded, followed by type enumeration, localization axes, the googleReviews linkage, and cost. Nothing is wasted.

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

Completeness3/5

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

With 10 parameters, no output schema, and minimal annotation detail, the description covers cost, output format, and types but leaves most parameters and pagination behaviour unexplained. Adequate for a quick call, not for invoking the advanced parameters correctly.

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 description coverage is only 20% across 10 parameters, so the description must compensate. It explains gl, hl, and the type enum, but leaves num, page, tbs, sortBy, ll, and autocorrect entirely undocumented in both places. It adds real meaning for three params but not enough to cover the gap.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Purpose4/5

Does the description clearly state what the tool does and how it differs from similar tools?

States a specific verb+resource ('Google results as JSON') and enumerates the result types the tool can return, which lets an agent distinguish it from the platform-specific siblings (amazonSearch, instagramSearch, tiktokSearch). It does not explicitly say how it differs from googleReviews, though it hints at the connection via cid.

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

Usage Guidelines3/5

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

Usage is implied by the enumerated result types (use type=images for images, type=news for news), but there is no explicit when-to-use guidance and no named alternative such as googleReviews or scrapeWebsite. The cid mention is the only routing hint.

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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