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by ClawyPro

elevenlabs_tts

Convert text to high-quality speech with AI voice synthesis, supporting multiple languages and voices for audio generation.

Instructions

Convert text to speech using ElevenLabs AI voice synthesis. Returns high-quality audio. Supports multiple languages and voices.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
textYesText to convert to speech (max 5000 chars)
voice_idNoElevenLabs voice ID (default: Rachel)
model_idNoModel: eleven_multilingual_v2 (default), eleven_turbo_v2
output_formatNoAudio format (default: mp3_44100_128)

Implementation Reference

  • The handler function for all MCP tools, including 'elevenlabs_tts', which routes requests to a gateway service.
    server.tool(
      tool.name,
      tool.description,
      tool.inputSchema.shape,
      async (params) => {
        const method = tool.method || "POST";
        const result = await gatewayRequest(method, tool.endpoint, params as Record<string, unknown>);
    
        if (result.error) {
          return {
            content: [{ type: "text" as const, text: `Error (${result.status}): ${result.error}` }],
            isError: true,
          };
        }
    
        const text = typeof result.data === "string"
          ? result.data
          : JSON.stringify(result.data, null, 2);
    
        return {
          content: [{ type: "text" as const, text }],
        };
      },
    );
  • Input schema definition for the elevenlabs_tts tool.
    inputSchema: z.object({
      text: z.string().describe("Text to convert to speech (max 5000 chars)"),
      voice_id: z.string().optional().describe("ElevenLabs voice ID (default: Rachel)"),
      model_id: z.string().optional().describe("Model: eleven_multilingual_v2 (default), eleven_turbo_v2"),
      output_format: z.enum(["mp3_44100_128", "mp3_22050_32", "pcm_16000", "pcm_44100"]).optional()
        .describe("Audio format (default: mp3_44100_128)"),
    }),
  • Tool definition and registration for 'elevenlabs_tts'.
    export const elevenlabsTools: ToolDef[] = [
      {
        name: "elevenlabs_tts",
        description: "Convert text to speech using ElevenLabs AI voice synthesis. Returns high-quality audio. Supports multiple languages and voices.",
        inputSchema: z.object({
          text: z.string().describe("Text to convert to speech (max 5000 chars)"),
          voice_id: z.string().optional().describe("ElevenLabs voice ID (default: Rachel)"),
          model_id: z.string().optional().describe("Model: eleven_multilingual_v2 (default), eleven_turbo_v2"),
          output_format: z.enum(["mp3_44100_128", "mp3_22050_32", "pcm_16000", "pcm_44100"]).optional()
            .describe("Audio format (default: mp3_44100_128)"),
        }),
        endpoint: "/v1/elevenlabs/tts",
      },
Behavior2/5

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

With no annotations provided, the description carries the full burden of behavioral disclosure. It mentions the tool 'Returns high-quality audio' which gives some output context, but fails to address critical behavioral aspects like rate limits, authentication requirements, cost implications, error handling, or latency. For a cloud-based AI service tool, this is a significant gap in transparency.

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 appropriately concise with three clear sentences. The first sentence states the core purpose, the second describes output quality, and the third mentions additional capabilities. There's no wasted language, though it could be slightly more structured with bullet points for the features mentioned.

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 of a cloud AI service tool with no annotations and no output schema, the description is insufficiently complete. It doesn't explain what format the audio is returned in (e.g., base64, file URL), doesn't mention authentication requirements, rate limits, or error conditions. For a tool that likely involves API calls with potential costs and limitations, more contextual information is needed.

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 already documents all parameters thoroughly. The description doesn't add any parameter-specific information beyond what's in the schema. It mentions 'Supports multiple languages and voices' which relates to the voice_id and model_id parameters, but doesn't provide additional semantic context. This meets the baseline for high schema coverage.

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: 'Convert text to speech using ElevenLabs AI voice synthesis.' It specifies the action (convert), resource (text), and technology (ElevenLabs), though it doesn't differentiate from siblings since there are no other TTS tools in the list. The mention of 'high-quality audio' and 'multiple languages and voices' adds useful context about output quality and capabilities.

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 any prerequisites, limitations, or scenarios where other tools might be more appropriate. While it hints at capabilities ('Supports multiple languages and voices'), it lacks explicit usage instructions or comparisons with sibling tools.

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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