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list_voices

Discover available text-to-speech voices to select options for speech generation in the Speech MCP Server.

Instructions

List all available voices for text-to-speech

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault

No arguments

Implementation Reference

  • MCP server request handler for the 'list_voices' tool. Invokes TTSClient.listVoices() and returns formatted list of voices.
    case "list_voices": {
      const voices = await ttsClient.listVoices();
      return {
        content: [{ 
          type: "text", 
          text: `Available voices:\n${voices.join('\n')}` 
        }],
      };
    }
  • Core logic in TTSClient class that lists and filters high-quality voices from the KokoroTTS instance after ensuring initialization.
    async listVoices(): Promise<KokoroVoice[]> {
      await this.waitForInit();
      if (!this.ttsInstance) {
        throw new Error("TTS model not initialized");
      }
      // @ts-ignore-line
      const allVoices = this.ttsInstance.voices as unknown as {[voice: string]: {overallGrade: string; gender: string}};
      const goodVoices = Object.keys(allVoices)
        .filter((voiceName) => ['A+', 'A', 'A-', 'B+', 'B', 'B-', 'C+'].includes(allVoices[voiceName].overallGrade))
      return goodVoices as unknown as KokoroVoice[];
    }
  • Tool schema definition including name, description, and empty input schema (no parameters required).
    const listVoicesTool: Tool = {
      name: "list_voices",
      description: "List all available voices for text-to-speech",
      inputSchema: {
        type: "object",
        properties: {},
        required: [],
      },
    };
  • src/index.ts:355-360 (registration)
    Registration of listVoicesTool in the array returned by ListToolsRequest handler, making it discoverable by MCP clients.
    tools: [
      textToSpeechTool,
      textToSpeechWithOptionsTool,
      listVoicesTool,
      getModelStatusTool,
    ],
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 lists voices but does not describe any behavioral traits such as rate limits, authentication needs, response format, or whether it's a read-only operation. This leaves significant gaps in understanding how the tool behaves beyond its basic function.

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, clear sentence that directly states the tool's purpose without any unnecessary words or fluff. It is front-loaded and efficiently communicates the essential information, making it highly concise and well-structured.

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's low complexity (0 parameters, no output schema, no annotations), the description is minimally adequate. It states what the tool does but lacks details on behavioral aspects like response format or usage context. For a simple list tool, this is acceptable but leaves room for improvement in guiding the agent fully.

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 input schema has 0 parameters with 100% coverage, so no parameter information is needed. The description appropriately does not discuss parameters, and since there are none, it meets the baseline expectation without requiring additional details, earning a score above the minimum.

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 all available voices') and the resource ('for text-to-speech'), providing a specific verb+resource combination. However, it does not differentiate from sibling tools like 'get_model_status' or 'text_to_speech', which might also relate to voice or model operations, so it lacks explicit sibling 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?

The description implies usage for retrieving voice options but offers no explicit guidance on when to use this tool versus alternatives like 'text_to_speech' or 'get_model_status'. There is no mention of prerequisites, exclusions, or specific contexts, leaving the agent to infer usage from the tool name alone.

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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