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Maybeyes111

google-scrape-mcp

by Maybeyes111

Google Scholar Search

google_scholar_search

Search Google Scholar for papers, authors, venues, citations, and PDF links; filter by year and result count.

Instructions

Scrape Google Scholar: papers, authors/venue, citations, PDF links.

start: 0-based result offset (unified google_search computes it from page). engine: auto | http | proxy | browser (lihat google_web_search).

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
hlNoen
numNo
queryYes
startNo
engineNoauto
year_lowNo
year_highNo

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault

No arguments

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv0.7.2

TDQS

C2.7/5.0
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 burden. 'Scrape' implies a fragile/rate-limited operation but nothing is said about blocking, quotas, auth, or failure modes. The engine enum (auto|http|proxy|browser) does add some real behavioral context but not enough for a scraping tool.

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?

Front-loads the purpose in one line and follows with terse parameter notes; no wasted sentences. The mixed-language fragment ('lihat google_web_search') is slightly awkward but does not bloat the text.

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 re-explained, but with 7 parameters at 0% coverage, no annotations, and 5 undocumented params, the definition is not complete enough for an agent to invoke it confidently.

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 7 parameters exist. The description documents only start (0-based offset) and engine (enum values); hl, num, query, year_low, and year_high remain unexplained in both schema and description, so it only partially compensates for the coverage gap.

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 Scholar) and lists what it returns (papers, authors/venue, citations, PDF links), so an agent knows the surface. It does not differentiate itself from siblings like google_scholar_cited_by or google_search, so it stops short of a 5.

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?

It references google_web_search (for engine) and mentions that unified google_search computes start, which hints at a relationship between tools. However, it never states when to use this tool versus google_search, google_web_search, or google_scholar_cited_by, leaving selection entirely to inference.

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