Skip to main content
Glama
ansua79

ScienceON-MCP

by ansua79

scienceon_papers

Read-only

Search scientific papers from KISTI ScienceON by keyword. Retrieve bibliographic details, abstracts, DOI, keywords, and links, with options to control result count and include full abstracts.

Instructions

KISTI ScienceON에서 논문을 검색합니다.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
pageNo페이지 번호 (기본 1)
queryYes검색 키워드
max_resultsNo최대 결과 수 (기본 10, 최대 100)
include_bodyNo초록 등 긴 본문 포함 여부 (기본 True). False면 초록을 제외하고 서지정보·DOI·키워드·링크만 반환합니다 (목록 훑기용).

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
resultYes
Behavior2/5

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

With annotations declaring readOnlyHint=true, the description adds no behavioral context beyond that (e.g., no mention of pagination, result size limits, or that include_body toggles abstract inclusion). The one-line description merely restates the function, and the schema already communicates most parameter behavior, leaving no added transparency value.

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?

The description is a single, short sentence with no redundancy, which is structurally concise. However, it is so minimal that it borders on under-specification rather than effective conciseness. It could include a bit more context (e.g., search scope or output type) while still remaining brief.

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?

Given the tool has 4 parameters, an output schema, and multiple sibling tools, the one-line description is incomplete. It does not explain what fields are searched, whether the result is a list, or how it relates to other paper tools. The presence of an output schema reduces the need to describe return values, but the description still lacks essential context for an agent to select this tool confidently.

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

Parameters3/5

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

Schema description coverage is 100% (all parameters have descriptions), so the baseline is 3. The tool description does not add any additional parameter meaning; it relies on the schema for details like page, max_results, and include_body. This meets the baseline but does not exceed it.

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?

The description clearly states the tool searches for papers in KISTI ScienceON ('KISTI ScienceON에서 논문을 검색합니다'). This is a specific verb+resource combination that communicates the primary function, and it is naturally distinguishable from sibling tools like 'scienceon_paper_details' by the search vs. details distinction.

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?

No guidance is provided about when to use this tool versus alternatives. It does not mention that it is for keyword-based search, that details of a specific paper should use scienceon_paper_details, or any exclusions or prerequisites. The user must infer usage from the tool name and schema.

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

Install Server

Other Tools

Latest Blog Posts

MCP directory API

We provide all the information about MCP servers via our MCP API.

curl -X GET 'https://glama.ai/api/mcp/v1/servers/ansua79/scienceon-mcp'

If you have feedback or need assistance with the MCP directory API, please join our Discord server