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voice_changer

Convert audio files to different voices using AI voice models. Upload audio, select a target voice ID, and transform vocal characteristics for creative or practical applications.

Instructions

Convert audio from one voice to another using AI voice models

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
audio_urlYesURL of the audio file to convert
voice_idYesTarget voice model ID (use get_all_voices to find IDs)
webhook_urlNoURL for callback upon completion

Implementation Reference

  • The handler function that implements the core logic for the voice_changer tool. It validates inputs, makes a POST request to the MusicGPT API's /voicetovoice endpoint, and returns the task details with instructions for status checking.
    private async handleVoiceChanger(args: any) {
      if (!args.audio_url || !args.voice_id) {
        throw new McpError(ErrorCode.InvalidParams, "audio_url and voice_id are required");
      }
    
      const response = await this.axiosInstance.post("/voicetovoice", {
        audio_url: args.audio_url,
        voice_id: args.voice_id,
        webhook_url: args.webhook_url,
      });
    
      return {
        content: [
          {
            type: "text",
            text: `Voice conversion started!\n\n${JSON.stringify(response.data, null, 2)}\n\nUse get_conversion_by_id with the task_id to check the status.`,
          },
        ],
      };
    }
  • Input schema defining the parameters for the voice_changer tool: audio_url (required), voice_id (required), and optional webhook_url.
    type: "object" as const,
    properties: {
      audio_url: {
        type: "string",
        description: "URL of the audio file to convert",
      },
      voice_id: {
        type: "string",
        description: "Target voice model ID (use get_all_voices to find IDs)",
      },
      webhook_url: {
        type: "string",
        description: "URL for callback upon completion",
      },
    },
    required: ["audio_url", "voice_id"],
  • src/index.ts:207-228 (registration)
    Tool registration entry in the TOOLS array, which is returned by the listTools handler. Includes name, description, and input schema.
    {
      name: "voice_changer",
      description: "Convert audio from one voice to another using AI voice models",
      inputSchema: {
        type: "object" as const,
        properties: {
          audio_url: {
            type: "string",
            description: "URL of the audio file to convert",
          },
          voice_id: {
            type: "string",
            description: "Target voice model ID (use get_all_voices to find IDs)",
          },
          webhook_url: {
            type: "string",
            description: "URL for callback upon completion",
          },
        },
        required: ["audio_url", "voice_id"],
      },
    },
  • src/index.ts:677-678 (registration)
    Switch case in the CallToolRequestSchema handler that routes execution to the specific handleVoiceChanger method.
    case "voice_changer":
      return await this.handleVoiceChanger(args);
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 states the tool 'convert[s] audio' but doesn't mention whether this is a synchronous or asynchronous operation (though 'webhook_url' hints at async), what permissions are required, rate limits, or what happens to the original audio. This leaves significant gaps for a mutation tool with zero annotation coverage.

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 front-loads the core purpose without unnecessary details. Every word earns its place, making it highly concise and well-structured for quick understanding.

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 an AI voice conversion tool with no annotations and no output schema, the description is incomplete. It lacks information on behavioral traits (e.g., async nature, error handling), output format, or usage constraints, making it inadequate for safe and effective tool invocation.

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 adds no parameter-specific information beyond what's in the schema, which has 100% coverage. It doesn't explain the format of 'audio_url' (e.g., supported file types), how 'voice_id' relates to 'get_all_voices', or the callback mechanism for 'webhook_url'. With high schema coverage, the baseline is 3, but no extra value is provided.

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 with specific verbs ('convert audio') and resources ('from one voice to another using AI voice models'), distinguishing it from siblings like 'change_audio_speed' or 'convert_audio_format'. However, it doesn't explicitly differentiate from 'sing_over_instrumental' or 'text_to_speech', which also involve voice transformations, so it falls short of a perfect 5.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines3/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

The description implies usage for voice conversion tasks, but provides no explicit guidance on when to use this tool versus alternatives like 'sing_over_instrumental' or 'text_to_speech'. It mentions 'voice models' but doesn't specify prerequisites or exclusions, leaving usage context somewhat vague.

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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