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Google search results

google_search
Read-only

Run a Google search through the ScrapeUnblocker API (https://docs.scrapeunblocker.com) and return the results page as JSON: organic results with their real URLs, favicons, sitelinks and star ratings, ads, the AI Overview, People also ask, related searches with their links, the knowledge panel, top stories, videos, local and shopping results.

Input Schema

NameRequiredDescriptionDefault
keywordYesThe search query.
proxy_countryNoOptional ISO country code to search from, e.g. 'US'.
pages_to_checkNoHow many result pages to collect (default 1).

Schema Changelog

Changes observed during successful MCP inspections.

  1. Changed1 schema field changed
    • removedInput schema / additionalProperties
      Removed value: -false
  2. First observed

TDQS

A3.5/5.0
Behavior3/5

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

Annotations already declare readOnlyHint=true, openWorldHint=true and destructiveHint=false, so the safety profile is covered. The description adds useful context that results come from the ScrapeUnblocker API as JSON with a docs link, but discloses nothing about rate limits, cost, latency, or how pages_to_check affects the response beyond the schema's own wording.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness4/5

Is the description appropriately sized, front-loaded, and free of redundancy?

One front-loaded sentence with the action first and the return payload after; nothing is redundant. The long enumeration of result sections is dense but each element carries informational value, so it is not padded.

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?

With no output schema, the description's enumeration of returned sections is genuinely necessary and supplies it well; all three parameters are self-documented in the schema. Remaining gaps — pagination behavior, error/failure modes, and cost of multi-page scraping — are minor for a read-only search tool.

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 100%, so the schema already documents keyword, proxy_country (ISO code) and pages_to_check (default 1, max 10). The description adds no per-parameter meaning such as how proxy_country influences results or what happens when multiple pages are requested, so the baseline 3 applies.

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 ('Run a Google search') and resource, and enumerates the returned content types (organic results, ads, AI Overview, knowledge panel, etc.), which makes the tool's scope unmistakable. It does not explicitly distinguish itself from vertical siblings like google_images, google_local, google_shopping, or the broader search_and_read, so differentiation is only implied.

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 only implied: the agent can infer this is the general web-search tool versus the vertical (images/local/shopping) and page-fetch siblings. There is no explicit when-to-use or when-not-to-use guidance and no mention of alternatives such as search_and_read.

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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