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SkillfulElectro

googlesearch-mcp

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Perform Google searches to retrieve web results. Configure number of results, language, deduplication, and safe search settings.

Instructions

Search Google and return web results. Powered by the googlesearch-python library (no API key needed).

Args: query: The search query. num_results: How many results to return (default 10). lang: Language code for results, e.g. "en", "fr", "de" (default "en"). unique: Deduplicate result URLs when True (default False). safe: Safe-search filter. Use "active" to enable, "" to disable (default "active").

Returns: A list of result objects with keys: index, title, url, description.

Raises: ValueError: If query is empty/blank or num_results is not positive.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
langNoen
safeNoactive
queryYes
uniqueNo
num_resultsNo

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
resultYes
Behavior5/5

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

With no annotations, the description fully discloses behavior: it uses a specific library, returns a list of results with detailed fields, and raises ValueError for invalid inputs. It also explains parameters like deduplication and safe search.

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 concise yet complete, with clear sections (Args, Returns, Raises). Every sentence adds value, and the main purpose is front-loaded.

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

Completeness5/5

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

Given the 5 parameters and presence of an output schema, the description covers all necessary context: parameter semantics, return format, error conditions. It is fully self-contained.

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

Parameters5/5

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

Schema description coverage is 0%, so the description must provide all parameter info. It does so comprehensively, listing each parameter with default values and usage context (e.g., 'lang' as language code, 'unique' for deduplication).

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 tool searches Google and returns web results, using specific verbs and resources. It is unambiguous and distinct from any potential siblings.

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 explains when to use this tool (for web search) and highlights a key benefit (no API key needed). However, it does not explicitly mention when not to use it or provide alternatives, though no siblings exist.

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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