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Scholar Search

scholar_search

Searches Google Scholar through SearXNG to find scholarly results for a query; use when you need paper references, though arXiv search may provide richer abstracts and PDF links.

Instructions

Google Scholar search (via SearXNG, engines='google scholar'). No offline fallback. Returns {"engine": "searxng-scholar", "results": [...]}. For papers, arxiv_search is usually richer (abstracts + PDF links).

Tool call template

Replace each placeholder with a value matching the input schema. Only required parameters are included; add optional parameters as needed.

{
  "id": 1,
  "jsonrpc": "2.0",
  "method": "tools/call",
  "params": {
    "arguments": {
      "query": "<query>"
    },
    "name": "scholar_search"
  }
}

Input Schema

Name	Required	Description	Default
`query`	Yes
`num_results`	No

Output Schema

Name	Required	Description	Default
No arguments

Schema Changelog

Changes observed during successful MCP inspections.

First observedv0.1.0Oct 25, 2026

TDQS

A3.9/5.0

Behavior3/5

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

With no annotations, the description carries the full burden of behavioral disclosure. It usefully states the backend, that there is no offline fallback, and gives a basic response shape, but it does not mention rate limits, authentication, result quality constraints, or other operational behavior.

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 short, front-loaded with the core purpose, and every sentence contributes useful routing or behavioral context. There is no wasted text.

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

Completeness4/5

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

For a simple two-parameter search tool with an output schema, the description covers the core purpose, backend constraint, no-fallback behavior, and a useful sibling alternative. Parameter guidance and deeper operational details are the main remaining gaps.

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%, and the description does not explain query or num_results semantics at all. While both parameters are relatively self-explanatory, the description adds no meaning about result count limits, formatting, or query expectations.

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 states a specific verb and resource: Google Scholar search via SearXNG with engines='google scholar'. It also distinguishes the tool from a relevant sibling by noting that arxiv_search is usually richer for papers.

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?

It gives clear usage context and explicitly points agents to arxiv_search when richer paper metadata such as abstracts and PDF links are needed. It does not fully specify when to prefer scholar_search over web_search or other search siblings beyond the Google Scholar scope.

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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