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Dosugamea

Voicevox MCP Server

by Dosugamea
OverviewSchemaSourceRelated ServersDiscussionsAdmin
TypeScript
Hybrid

Servidor MCP de Voicevox

Este es un servidor para utilizar servidores de síntesis de voz compatibles con VOICEVOX (AivisSpeech / VOICEVOX / COEIROINK) a través de MCP (Model Context Protocol). Se puede utilizar para la síntesis de voz en modo agente usando Claude 3.7 en Cursor, etc.

Prerrequisitos

Entorno de Windows

Entorno Docker (WSL2)

  • Docker y Docker Compose

  • WSL2

  • MOTOR VOICEVOX, etc. (se ejecuta localmente o en Docker)

  • sudo apt install libsdl2-dev pulseaudio-utils pulseaudio

  • Permisos de acceso a /mnt/wslg

Related MCP server: TTS-MCP

Instalación y configuración

  1. Clonar el repositorio

git clone https://github.com/Dosugamea/voicevox-mcp-server.git
cd voicevox-mcp-server

  1. Instalación de dependencias

npm install

  1. Configuración de variables de entorno Cree un archivo .env copiando .env_example y modificando la configuración según sea necesario:

VOICEVOX_API_URL=http://localhost:50021
VOICEVOX_SPEAKER_ID=1

Cómo hacerlo

Ejecución en entorno Windows

Inicie un servidor por separado del editor siguiendo los pasos a continuación.

npm run build
npm start

Ejecución en entorno Docker

No se requiere ningún editor ni operación independiente. No se puede ejecutar directamente porque se inicia en modo stdio.

Cómo configurarlo

Cuando se ejecuta en un entorno Windows

Agregue lo siguiente a mcp.json. La conexión es inestable, por lo que debe volver a conectarla si se desconecta.

        "voicevox": {
            "url": "http://localhost:10100/sse"
        }

Cuando se ejecuta en un entorno Docker

Agregue lo siguiente a mcp.json. (El entorno del autor no ha sido probado).

{
    "tools": {
        "voicevox": {
            "command": "cmd",
            "args": [
                "/c",
                "docker",
                "run",
                "-i",
                "--rm",
                "-v",
                "/mnt/wslg:/mnt/wslg",
                "-e",
                "PULSE_SERVER",
                "-e",
                "SDL_AUDIODRIVER",
                "-e",
                "VOICEVOX_API_URL",
                "-e",
                "VOICEVOX_SPEAKER_ID",
                "your-local-docker-image-name"
            ],
            "env": {
                "PULSE_SERVER": "unix:/mnt/wslg/PulseServer",
                "SDL_AUDIODRIVER": "pulseaudio",
                "VOICEVOX_API_URL": "http://host.docker.internal:50031",
                "VOICEVOX_SPEAKER_ID": "919692871"
            }
        }
    }
}

Acerca de la identificación del orador

La identificación del altavoz varía según el modelo de VOICEVOX que utilice. El valor predeterminado es utilizar "1" (Shikoku Metal). Si desea utilizar otro ID de altavoz, cambie la variable de entorno VOICEVOX_SPEAKER_ID .

La lista de identificaciones de oradores se puede encontrar en /speakers de la API VOICEVOX ENGINE. Ejemplo: curl http://localhost:50021/speakers

solución de problemas

  • Error de conexión con VOICEVOX : asegúrese de que VOICEVOX ENGINE se esté ejecutando y que la URL de la API esté configurada correctamente.

  • No se reproduce sonido : asegúrese de que VLC esté instalado correctamente y en su ruta.

  • Problema de salida de audio en el entorno Docker : verifique que pulseaudio esté configurado correctamente.

Información para desarrolladores

  • Para contribuir al código fuente, cree un problema o envíe una solicitud de extracción.

  • Para informar errores o solicitar funciones, utilice la función Problemas en GitHub.

licencia

Licencia MIT

Available Tools

1 tool
voicevoxC

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

ParametersJSON Schema
NameRequiredDescriptionDefault
textNo合成する文章

TDQS

C2.9/5.0
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.

Tool Schema Changelog

Recent tool additions, removals, and schema changes observed during successful MCP inspections.

  1. 1 tool updatev1.0.0
    • First observedvoicevox
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TDQS

B3.1/5.0

Scored across 1 tool

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.

Maintenance

ActivityInactive
ResponsivenessNo issues

Resources

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