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Maybeyes111

google-scrape-mcp

by Maybeyes111

Google Video Search

google_video_search

Search Google Video results and scrape video titles, URLs, and snippets from a query without an API key.

Instructions

Scrape Google Video Search (tbm=vid): title, URL, snippet.

engine: auto | http | proxy | browser (lihat google_web_search).

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

C2.8/5.0
Behavior2/5

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

No annotations are provided, so the description carries the full behavioral burden. It discloses the output shape but says nothing about scraping reliability, rate limits, blocking, auth needs, or pagination behavior; delegating the engine explanation to another tool's description does not compensate.

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

Conciseness3/5

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

It is short and front-loads the core action, which is good, but the second line is telegraphic and half-Indonesian ('lihat google_web_search'), making it weaker as a standalone instruction despite the brevity.

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 no explanation, but with 0% parameter coverage and no annotations the definition leaves five of six parameters and the entire behavioral profile unaddressed — incomplete for a scraping tool with locale and pagination knobs.

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 coverage is 0% and there are 6 parameters. The description only clarifies one — engine (auto | http | proxy | browser) — which the schema leaves as a bare string with a default and no enum, so that addition is genuinely useful. But gl, hl, num, start, and query are entirely undocumented in both places.

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 concrete verb and resource ('Scrape Google Video Search (tbm=vid)') and enumerates the returned fields (title, URL, snippet), which is specific enough to distinguish it from the sibling search tools at a glance. It stops short of explicitly contrasting itself with google_web_search or google_image_search, so it lands at 4 rather than 5.

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?

Purpose implies when to reach for it (video results only), and the reference to google_web_search for the engine semantics is a mild cross-reference. However, there is no explicit when-to-use / when-not guidance or stated alternatives among the ~20 sibling search tools.

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