Busca na web pelo Google e devolve os resultados orgânicos com título, link e trecho, mais a resposta direta e o painel de conhecimento quando existem. Aceita até 100 consultas por chamada.
| Name | Required | Description | Default |
|---|---|---|---|
| pais | No | ||
| local | No | ||
| idioma | No | ||
| limite | No | ||
| pagina | No | ||
| periodo | No | ||
| consultas | Yes |
Changes observed during successful MCP inspections. Dates show when Glama detected each change.
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations already mark the tool as read-only, idempotent, and non-destructive. The description adds useful behavioral detail beyond those: it accepts up to 100 queries per call and returns direct answers/knowledge panels only when they exist. This gives an agent meaningful expectations about batch behavior and optional content.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
Two sents with no filler. The main action and result types are front-loaded, and the batch capacity is stated efficiently in the second sentence.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Despite having no output schema, the description does succinctly describe the principal return components. It is less complete on parameter semantics and on selecting among the many sibling tools, so an agent would still need to infer or probe several details before a fully informed call.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 0%, so the description must compensate for the seven parameters. The only parameter-related detail is the batch limit ('até 100 consultas'), which sheds light on 'consultas' but not on pais, local, idioma, limite, pagina, or periodo. Most parameters remain unexplained by both schema and description.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
The description states a specific verb ('Busca na web'), the resource (Google), and the concrete output (organic results with title, link, and snippet, plus direct answer and knowledge panel). It also differentiates from sibling tools by being the general web search among specialized verticals like academic, images, and news.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description implies when to use it (any general web search), but it doesn't explicitly name alternatives or exclusion criteria such as 'use busca_google_academico for academic searches.' Sibling names provide context, but the description itself offers no direct routing guidance.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Add one secure layer between your agents and this server.
The twelve busca_google_* tools are each tied to a distinct Google vertical, so selecting the right one for a search task is usually straightforward. The only real ambiguity is between busca_google_lugares and busca_google_mapas, and between authenticate/connect, but the descriptions do clarify their different use cases.
The core search tools follow a highly consistent busca_google_<category> snake_case pattern in Portuguese. However, the six platform-management tools use generic English names like authenticate, connect, marketplace, and toolkit_info, creating a mixed convention across the set.
At 18 tools, the server is in the borderline-heavy range. The 12 search tools are individually justified, but the inclusion of 6 unrelated platform/metadata tools makes the overall count feel inflated for a server titled 'Buscador Google'.
The search surface is impressively broad: web, news, images, videos, shopping, academic, patents, places, maps, reviews, suggestions, and page reading are all covered. Minor niche Google surfaces like Trends or Books are absent, but core search workflows have no dead ends.