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Maybeyes111

google-scrape-mcp

by Maybeyes111

Google Web Search

google_web_search

Scrape web search results without an API key: collect organic listings, featured snippets, and related searches, using HTTP fast path with browser fallback when blocked.

Instructions

Scrape Google Web Search: organic results, featured snippet, related searches.

engine: auto (HTTP cepat, fallback browser bila diblokir) | http (tanpa browser) | proxy (paksa pool proxy) | browser (langsung Camoufox headless, tanpa proxy/API key).

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
glNous
hlNoen
numNo
queryYes
startNo
engineNoauto

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault

No arguments

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv0.7.2

TDQS

B3.1/5.0
Behavior3/5

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

With no annotations, the description carries the full burden. It does disclose meaningful scraping behavior: HTTP may be blocked and falls back to a browser, a forced proxy pool exists, and browser mode bypasses proxy/API keys. It does not state auth needs, rate limits, or reliability caveats, leaving notable gaps for a scraper.

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?

Two compact sentences, purpose front-loaded before the engine detail, with no filler. The engine clause is dense and mixes Indonesian with English, which slightly hurts readability but not length.

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?

An output schema exists so return values need not be described, but with 6 undocumented parameters and no annotations, an agent lacks the semantic context (locale, result count, pagination via start) needed to invoke it well. The description covers only one of several open questions.

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

Parameters2/5

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

Schema description coverage is 0% across 6 parameters, so the description must compensate. It explains only 'engine' (with four modes); gl, hl, num, start, and even query are left entirely unexplained, so most parameters gain no meaning beyond their names and defaults.

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 ('Scrape') and resource ('Google Web Search') and enumerates the output surface (organic results, featured snippet, related searches), so the agent knows what it retrieves. However, it offers no differentiation from the near-identical sibling 'google_search' (or the other vertical search tools), so it is clear but not sibling-distinguishing.

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?

The 'engine' clause gives per-mode guidance about which retrieval strategy to pick (auto/http/proxy/browser), which is useful context. But there is no statement of when to select this tool over its many search siblings, nor any exclusions or prerequisites, so usage is only implied.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.