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Darshan972

Scrapingdog MCP Server

by Darshan972

Google Images API

google_images

Retrieve Google Images search results with image sources and thumbnails. Specify a query and use filters for size, color, time, domain, country, and language to refine output.

Instructions

Get Google Images search results with sources and thumbnails.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
tbsNoAdvanced filter (size, color, type, time range).
htmlNoReturn raw HTML instead of parsed JSON. (API default: false)
safeNoAdult-content filter. (API default: off)
queryYesImage search query.
startNoResult offset (e.g. 20 skips the first 20).
domainNoCountry-specific Google domain (e.g. google.co.uk, google.co.in). (API default: google.com)
countryNoTwo-letter ISO country code to geo-target results (e.g. us, gb, in, de). (API default: us)
languageNoResult language code (e.g. en, es, fr, de). (API default: en)
Behavior2/5

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

With no annotations provided, the description carries full responsibility for behavioral disclosure. It only mentions 'sources and thumbnails' but does not explain any constraints, rate limits, pagination behavior, or response structure. This is insufficient for a tool with 8 parameters and no output schema.

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 a single, well-structured sentence that is immediately informative. Every word contributes value, with no redundant phrases or unnecessary context, making it highly concise and easy to parse.

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

Completeness2/5

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

Despite covering the core purpose, the description omits crucial context: usage guidelines, behavioral nuances, and details about the return format. Since there is no output schema, the description should at least indicate the structure or content of the response beyond 'sources and thumbnails', but it does not.

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?

The input schema covers all 8 parameters with descriptions (100% coverage), so the description does not need to repeat parameter details. However, it also does not add any extra meaning beyond the schema, such as example values or parameter interactions, warranting the baseline score of 3.

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 uses a specific verb 'Get' and identifies the exact resource 'Google Images search results', clearly distinguishing it from general search tools like google_search. It also highlights the key output components ('sources and thumbnails'), giving a precise understanding of what the tool does.

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

Usage Guidelines2/5

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

There is no guidance on when to use this tool versus alternatives like google_lens or google_search. No context is provided about use cases, exclusions, or preferred scenarios, leaving the agent to infer usage solely from the tool name.

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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