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Dosugamea

Voicevox MCP Server

by Dosugamea
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TypeScript
Hybrid

Server Quality Checklist

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

  • Latest release: v1.0.0

  • Disambiguation5/5

    With only one tool, there is no possibility of ambiguity or overlap between tools. The single tool 'voicevox' has a clear, distinct purpose for text-to-speech synthesis and playback.

    Naming Consistency5/5

    A single tool inherently exhibits perfect naming consistency, as there are no other tools to compare against. The tool name 'voicevox' is straightforward and matches the server's domain.

    Tool Count2/5

    A single tool is too few for a server's purpose, even for a focused domain like text-to-speech. This limits functionality, as agents cannot perform related operations like listing voices, adjusting parameters, or managing playback without additional tools.

    Completeness2/5

    The tool surface is severely incomplete for a text-to-speech domain. While the core synthesis and playback function is covered, there are obvious gaps such as fetching available voices, configuring speech parameters, pausing or stopping playback, or handling errors, which will likely cause agent failures.

  • Average 2.9/5 across 1 of 1 tools scored.

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

  • This repository is archived. Archived repositories automatically receive an F maintenance tier.

  • This repository is licensed under MIT License.

  • This repository includes a README.md file.

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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

  • 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. It mentions synthesis and playback but lacks details on behavioral traits like error handling, performance characteristics (e.g., latency), or system requirements (e.g., VOICEVOX installation). This leaves significant gaps for an AI agent.

    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, efficient sentence that directly states the tool's function. It is appropriately sized and front-loaded, with no unnecessary words, though it could be slightly more structured (e.g., separating synthesis and playback aspects).

    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 lack of annotations and output schema, the description is incomplete. It covers the basic purpose but omits critical context such as what the tool returns (e.g., success/failure, audio data), error conditions, or usage limitations, which are essential for a synthesis/playback tool.

    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?

    The description does not mention the 'text' parameter at all. However, schema description coverage is 100%, with the parameter documented as '合成する文章' (text to synthesize). Since the schema fully covers the parameter, the baseline score of 3 is appropriate, as the description adds no additional semantic value.

    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's purpose: 'VOICEVOXを使用して音声を合成し、ホストコンピュータで再生します' (Uses VOICEVOX to synthesize speech and play it on the host computer). It specifies the action (synthesize and play speech) and resource (VOICEVOX), but since there are no sibling tools, it doesn't need to distinguish from alternatives.

    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?

    The description provides no guidance on when to use this tool versus alternatives or any contextual prerequisites. It simply states what the tool does without indicating appropriate scenarios or constraints.

    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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