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Voicevox MCP Server

Voicevox MCP Server

by Dosugamea
OverviewSchemaSourceRelated ServersDiscussionsAdmin
TypeScript
Hybrid

Voicevox MCP 서버

VOICEVOX 호환 음성 합성 서버(AivisSpeech/VOICEVOX/COEIROINK)를 MCP(Model Context Protocol)를 통해 이용하기 위한 서버입니다. Cursor등에서의 Claude 3.7을 사용한 에이전트 모드에서의 음성 합성에 이용할 수 있습니다.

요건

Windows 환경

Docker 환경(WSL2)

  • Docker 및 Docker Compose

  • WSL2

  • VOICEVOX ENGINE 등 (로컬 또는 Docker에서 실행)

  • sudo apt install libsdl2-dev pulseaudio-utils pulseaudio 된 Linux 환경

  • /mnt/wslg 에 대한 액세스 권한

Related MCP server: TTS-MCP

설치 및 설정

  1. 리포지토리 복제

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

  1. 종속성 설치

npm install

  1. 환경 변수 설정 .env_example 을 복사하여 .env 파일을 만들고 필요에 따라 설정을 변경합니다.

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

실행 방법

Windows 환경에서 실행

에디터와 별도로 아래 절차에 따라 서버를 시작하십시오.

npm run build
npm start

Docker 환경에서 실행

에디터와 별도로의 조작은 불필요합니다. stdio 모드에서 상승하기 때문에 직접 실행할 수 없습니다.

설정 방법

Windows 환경에서 실행하는 경우

mcp.json에 다음을 추가하십시오. 연결이 불안정하기 때문에 연결이 끊어지면 다시 연결하십시오.

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

Docker 환경에서 실행하는 경우

mcp.json에 다음을 추가하십시오. (작가 환경에서의 동작은 확인할 수 없습니다)

{
    "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"
            }
        }
    }
}

스피커 ID 정보

스피커 ID는 사용하는 VOICEVOX 모델에 따라 다릅니다. 기본적으로 "1"(시코쿠 메탄)을 사용합니다. 다른 화자 ID를 사용하는 경우 환경 변수 VOICEVOX_SPEAKER_ID 를 변경합니다.

화자 ID 목록은 VOICEVOX ENGINE API의 /speakers 엔드포인트에서 확인할 수 있습니다. 예: curl http://localhost:50021/speakers

문제해결

  • VOICEVOX와의 연결 오류 : VOICEVOX ENGINE이 실행 중이고 API URL이 올바르게 설정되어 있는지 확인하십시오.

  • 오디오가 재생되지 않음 : VLC가 올바르게 설치되어 있고 경로가 통과하는지 확인합니다.

  • Docker 환경에서 오디오 출력 문제 : pulseaudio 설정이 올바른지 확인하십시오.

개발자를 위한 정보

  • 소스 코드에 기여하는 경우 Issue를 작성하거나 Pull Request를 제출하십시오.

  • 버그 보고 및 기능 요청은 GitHub의 Issue 기능을 이용해 주십시오.

라이센스

MIT License

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

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
Deploy Server
One endpoint for every MCP toolRayrun runs every MCP server behind one URL and holds the credentials. Each call is decided per client, tool, and argument, then recorded.ray.runAd

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
ResponsivenessSyncing

Resources

Related MCP Connectors

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    quality
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