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suzuuuuu09

CiNii MCP Server

by suzuuuuu09
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Python
Remote

Server Quality Checklist

58%
Profile completionA complete profile improves this server's visibility in search results.

  • Latest release: v0.1.0

  • Disambiguation5/5

    Only one tool exists, so there is no possibility of confusion between tools. The tool's purpose is clear from its name and description.

    Naming Consistency5/5

    The single tool uses a descriptive snake_case name that aligns with common MCP naming conventions. With only one tool, there are no inconsistencies to evaluate.

    Tool Count3/5

    One tool is on the low end and feels thin for a server named CiNii, which typically implies a richer API surface. However, the tool itself is comprehensive enough to perform advanced searches, so it's borderline.

    Completeness2/5

    The server only offers a single search tool. It lacks dedicated operations for fetching paper details by ID, managing result pagination, or accessing related resources like authors or references, leaving significant gaps for a full CiNii integration.

  • Average 2.3/5 across 1 of 1 tools scored.

    See the Tool Scores section below for per-tool breakdowns.

    • No community issues in the last 6 months
    • 0 commits in the last 12 weeks
    • Last stable release on
    • No critical vulnerability alerts
    • No high-severity vulnerability alerts
    • No code scanning findings
    • CI status not available

  • This repository is licensed under Apache 2.0.

  • This repository includes a README.md file.

  • No tool usage detected in the last 30 days. Usage tracking helps demonstrate server value.

    Tip: use the "Try in Browser" feature on the server page to seed initial usage.

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How to sync the server with GitHub?

Servers are automatically synced at least once per day, but you can also sync manually at any time to instantly update the server profile.

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How is the quality score calculated?

The overall quality score combines two components: Tool Definition Quality (70%) and Server Coherence (30%).

Tool Definition Quality measures how well each tool describes itself to AI agents. Every tool is scored 1–5 across six dimensions: Purpose Clarity (25%), Usage Guidelines (20%), Behavioral Transparency (20%), Parameter Semantics (15%), Conciseness & Structure (10%), and Contextual Completeness (10%). The server-level definition quality score is calculated as 60% mean TDQS + 40% minimum TDQS, so a single poorly described tool pulls the score down.

Server Coherence evaluates how well the tools work together as a set, scoring four dimensions equally: Disambiguation (can agents tell tools apart?), Naming Consistency, Tool Count Appropriateness, and Completeness (are there gaps in the tool surface?).

Tiers are derived from the overall score: A (≥3.5), B (≥3.0), C (≥2.0), D (≥1.0), F (<1.0). B and above is considered passing.

Tool Scores

  • Behavior1/5

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

    No annotations are present, so the description carries the full burden of disclosing behavioral traits. It only states the action and provides no information about read-only status, pagination, rate limits, authentication, or any side effects, leaving the agent completely uninformed.

    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?

    The description is a single concise sentence that wastes no words and front-loads the core action. However, it is so brief that it borders on under-specification, though that is better captured in completeness.

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

    Completeness1/5

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

    With 19 optional parameters, no schema descriptions, and no annotations, a one-sentence description is severely inadequate. The output schema exists but does not help the agent understand when or how to use the tool, making the description far from complete.

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

    Parameters1/5

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

    The schema contains 19 parameters with zero description coverage, and the description mentions none of them. Without any explanation of parameters like issn, lang, sortorder, or max_results, an agent cannot correctly construct a valid search query.

    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 performs an advanced search on CiNii and retrieves paper information, using a specific verb (検索を行い) and resource (CiNii). However, with no sibling tools listed, it does not differentiate beyond the basic action.

    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 on when to use this tool versus alternatives, nor are there any use cases, prerequisites, or exclusions. The phrase 'advanced search' implies a general purpose but offers no concrete context for an agent to decide when to invoke it.

    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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  • Evaluate tool definition quality.

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