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da-okazaki

MCP FishAudio Server

by da-okazaki
OverviewSchemaRelated ServersScoreDiscussions
TypeScript
Remote

Server Quality Checklist

67%
Profile completionA complete profile improves this server's visibility in search results.

  • Latest release: v1.0.0

  • Disambiguation5/5

    The two tools have clearly distinct purposes: one lists voice references (a read-only operation), and the other generates speech (a synthesis operation). There is no overlap or ambiguity between these functions, making it easy for an agent to select the correct tool.

    Naming Consistency5/5

    Both tools follow a consistent snake_case naming pattern with a 'fish_audio_' prefix, followed by a descriptive verb_noun combination (list_references and tts). This uniformity enhances readability and predictability across the tool set.

    Tool Count2/5

    With only two tools, the server feels under-scoped for a TTS API domain. Key operations like managing references (e.g., create, update, delete) or configuring TTS parameters are missing, limiting the server's utility and forcing agents to work around gaps.

    Completeness2/5

    The tool set is severely incomplete for a TTS API. While it covers listing references and generating speech, it lacks essential CRUD operations for references (e.g., create, update, delete) and configuration tools (e.g., set parameters, list voices). This will likely cause agent failures in common workflows.

  • Average 3.1/5 across 2 of 2 tools scored.

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

    • 0 of 1 community issues answered or closed in the last 6 months
    • 0 commits in the last 12 weeks
    • No stable releases found
    • No critical vulnerability alerts
    • No high-severity vulnerability alerts
    • No code scanning findings
    • CI is failing

  • 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 of behavioral disclosure. It states the tool generates speech but doesn't cover critical aspects like rate limits, authentication requirements, error handling, or what the output looks like (e.g., audio file, URL, or stream). For a TTS tool with 13 parameters and no output schema, this is a significant gap.

    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 a single, efficient sentence that directly states the tool's purpose without unnecessary words. It's appropriately sized and front-loaded, with zero waste.

    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 complexity (13 parameters, no annotations, no output schema), the description is incomplete. It doesn't explain the return value (e.g., audio data or file path), error conditions, or behavioral traits like streaming implications. For a TTS tool with many optional parameters, more context is needed to guide effective use.

    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%, so the schema fully documents all 13 parameters. The description adds no additional parameter information beyond what's in the schema. According to the rules, when coverage is high (>80%), the baseline score is 3 even with no param info in the description.

    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: 'Generate speech from text using Fish Audio TTS API.' It specifies the verb ('Generate speech') and resource ('from text'), but doesn't differentiate from its sibling tool 'fish_audio_list_references', which appears to serve a different function (listing references rather than generating speech).

    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. It doesn't mention the sibling tool or any other TTS options, nor does it specify prerequisites or contexts for use. The agent must infer usage from the tool name and parameters alone.

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

  • 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 of behavioral disclosure. It states it's a list operation, implying it's likely read-only and non-destructive, but doesn't confirm this or add details like pagination, rate limits, or authentication needs. The description is minimal and lacks rich behavioral context beyond the basic action.

    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 a single, efficient sentence that directly states the tool's purpose with no wasted words. It's appropriately sized and front-loaded, making it easy for an agent to parse quickly.

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

    Completeness3/5

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

    Given the tool has 0 parameters, no annotations, and no output schema, the description is minimal but covers the basic purpose. However, for a tool with no structured data support, it lacks details on return values, error handling, or behavioral traits, making it adequate but with clear gaps in completeness.

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

    Parameters4/5

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

    The tool has 0 parameters, and schema description coverage is 100%, so there are no parameters to document. The description doesn't need to add parameter semantics, and it appropriately doesn't mention any. A baseline of 4 is applied as it handles the zero-parameter case adequately without unnecessary information.

    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 action ('List') and the resource ('all configured voice references'), providing a specific verb+resource combination. However, it doesn't differentiate from its sibling tool 'fish_audio_tts', which appears to be a text-to-speech tool rather than a listing tool, so the distinction is inherent but not explicitly stated.

    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. It doesn't mention the sibling tool 'fish_audio_tts' or any other context for usage, leaving the agent without explicit when/when-not instructions or alternatives.

    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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