MCP Simple AivisSpeech

English | 日本語

🙏 Special Thanks
This project is based on mcp-simple-voicevox by @t09tanaka.
We deeply appreciate their excellent work in creating the original MCP server for VOICEVOX, which served as the foundation for this AivisSpeech adaptation.

A Model Context Protocol (MCP) server for seamless integration with AivisSpeech text-to-speech engine. This project enables AI assistants and applications to convert text to natural-sounding Japanese speech with customizable voice parameters.

✨ Features

• 🎙️ Text-to-Speech Conversion: High-quality Japanese speech synthesis using AivisSpeech
• 👥 Multiple Voice Characters: Support for various speakers and voice styles (default: Anneli ノーマル)
• ⚙️ Configurable Parameters: Adjust speed, pitch, volume, and intonation
• 🔊 Cross-Platform Audio: Automatic audio playback on macOS, Windows, and Linux
• 🔔 Task Notifications: Voice notifications for process completion
• 🚀 Easy Integration: Simple MCP protocol for AI assistant integration
• 📊 Engine Status Monitoring: Real-time status checking of AivisSpeech engine
• 🛡️ Smart Error Handling: Helpful error messages with speaker suggestions

📋 Prerequisites

• Node.js: Version 18.0.0 or higher
• AivisSpeech Engine: Running on http://127.0.0.1:10101 (default port)
• Audio System: System audio capabilities for playback

MCP Simple AivisSpeech Configuration

Using Claude Code

The easiest way to add this MCP server is using Claude Code:

✨ Using npx ensures you always get the latest version automatically - no manual updates needed!

claude mcp add aivisspeech -e AIVISSPEECH_URL=http://127.0.0.1:10101 -- npx @shinshin86/mcp-simple-aivisspeech@latest

By default, the server is added to the local scope (current project only). To make it available across all projects, use the -s user option:

claude mcp add aivisspeech -s user -e AIVISSPEECH_URL=http://127.0.0.1:10101 -- npx @shinshin86/mcp-simple-aivisspeech@latest

You can also add voice notifications to your CLAUDE.md file to automate task completion notifications:

## Task Completion Behavior
- When all tasks are completed, always use the aivisspeech mcp tool to announce "Tasks completed" via voice
- When user input or decision is needed, use the aivisspeech mcp tool to announce "Awaiting your decision" via voice

### Notification Timings
- When asking the user a question
- When all tasks are completed
- When errors or issues occur

Using Claude Desktop

For manual configuration with Claude Desktop:

✨ Using npx ensures you always get the latest version automatically - no manual updates needed!

{
  "mcpServers": {
    "aivisspeech": {
      "command": "npx",
      "args": ["@shinshin86/mcp-simple-aivisspeech@latest"],
      "env": {
        "AIVISSPEECH_URL": "http://127.0.0.1:10101"
      }
    }
  }
}

⚙️ AivisSpeech Engine Setup

Before using this MCP server, you need to have AivisSpeech running locally:

1. Download AivisSpeech from https://aivis-project.com/
2. Launch AivisSpeech on your local machine
3. The engine will start on the default port 10101
4. Verify the engine is running by visiting http://127.0.0.1:10101/docs

📖 Other Usage Methods

For Local Development

# Run the MCP server
npm start

# For development with hot reload
npm run dev

# Check if everything is working
npm test

For cloning the repository, installing dependencies, and building:

# Clone repository
git clone https://github.com/shinshin86/mcp-simple-aivisspeech.git
cd mcp-simple-aivisspeech

# Install dependencies
npm install

# Build the project
npm run build

🛠️ Available Tools

🎤 speak

Convert text to speech and play audio with customizable voice parameters.

Parameters:

• text (required): Text to convert to speech
• speaker (optional): Speaker/voice ID (default: 888753760 - Anneli ノーマル)
• speedScale (optional): Speech speed multiplier (0.5-2.0, default: 1.0)
• pitchScale (optional): Pitch adjustment (-0.15-0.15, default: 0.0)
• volumeScale (optional): Volume level (0.0-2.0, default: 1.0)
• playAudio (optional): Whether to play the generated audio (default: true)

Example:

{
  "text": "こんにちは、世界！",
  "speaker": 888753760,
  "speedScale": 1.2,
  "pitchScale": 0.05,
  "volumeScale": 1.5
}

👥 get_speakers

Retrieve a list of all available voice characters and their styles.

Returns: List of speakers with their IDs, names, and available voice styles.

🔔 notify_completion

Play a voice notification when tasks are completed.

Parameters:

• message (optional): Completion message to announce (default: "処理が完了しました")
• speaker (optional): Speaker ID for the notification voice (default: 888753760 - Anneli ノーマル)

Example:

{
  "message": "データ処理が完了しました",
  "speaker": 888753760
}

📊 check_engine_status

Check the current status and version of the AivisSpeech engine.

Returns: Engine status, version information, and connectivity details.

🖥️ Platform Support

Audio Playback Systems

Platform	Audio Command	Requirements
macOS	afplay	Built-in (no additional setup)
Windows	PowerShell Media.SoundPlayer	Windows PowerShell
Linux	aplay	ALSA utils (sudo apt install alsa-utils)

Tested Environments

• ✅ macOS 12+ (Intel & Apple Silicon)
• ✅ Windows 10/11
• ✅ Ubuntu 20.04+
• ✅ Node.js 18.x, 20.x, 21.x

🧪 Development

Available Scripts

# Development & Building
npm run dev          # Run with hot reload (tsx)
npm run build        # Compile TypeScript to dist/
npm start           # Run compiled server

# Code Quality
npm run lint        # Run ESLint
npm run test        # Run Vitest tests (single run)
npm run test:watch  # Run tests in watch mode
npm run test:ui     # Run tests with UI
npm run test:coverage # Run tests with coverage

# Utilities
npm run clean       # Clean dist/ directory

Local vs NPX Usage

For MCP clients (Production):

• Use npx @shinshin86/mcp-simple-aivisspeech@latest in your MCP configuration
• No local setup required, always gets latest version

For development:

• Clone repository and use npm run dev for hot reload
• Use npm run build && npm start for testing production builds

Project Architecture

mcp-simple-aivisspeech/
├── src/
│   ├── index.ts                  # MCP server & tool handlers
│   └── aivisspeech-client.ts     # AivisSpeech API client
├── tests/
│   └── aivisspeech-client.test.ts # Unit tests
├── dist/                         # Compiled output
├── docs/                         # Documentation
└── config files                  # TS, ESLint, Vitest configs

API Client Architecture

The AivisSpeechClient class provides:

• HTTP Client: Axios-based API communication
• Error Handling: Comprehensive error catching and reporting
• Type Safety: Full TypeScript interfaces for all API responses
• Connection Management: Health checks and status monitoring

Adding New Features

1. New Tool: Add handler in src/index.ts CallToolRequestSchema
2. API Methods: Extend AivisSpeechClient class
3. Types: Update interfaces in aivisspeech-client.ts
4. Tests: Add corresponding test cases

🔧 Troubleshooting

Common Issues

AivisSpeech Engine Not Found

Error: Failed to get version: connect ECONNREFUSED 127.0.0.1:10101

Solution: Ensure AivisSpeech Engine is running on the correct port.

Audio Playback Fails

Error: Audio player exited with code 1

Solutions:

• macOS: Check if afplay is available
• Linux: Install ALSA utils: sudo apt install alsa-utils
• Windows: Ensure PowerShell execution policy allows scripts

Permission Denied

Error: spawn afplay EACCES

Solution: Check file permissions and system audio settings.

Debug Mode

Enable verbose logging:

DEBUG=mcp-aivisspeech npm run dev

📄 License

This project is licensed under the Apache License 2.0 - see the LICENSE file for details.

🤝 Contributing

We welcome contributions! Please follow these steps:

1. Fork the repository
2. Create a feature branch (git checkout -b feature/amazing-feature)
3. Commit your changes (git commit -m 'Add amazing feature')
4. Push to the branch (git push origin feature/amazing-feature)
5. Open a Pull Request

Development Guidelines

• Follow existing TypeScript/ESLint configurations
• Add tests for new functionality
• Update documentation for API changes
• Ensure cross-platform compatibility

🙏 Acknowledgments

• AivisSpeech Project for the excellent TTS engine
• Model Context Protocol for the integration framework
• VOICEVOX MCP for inspiration and reference

📞 Support

• Issues: GitHub Issues
• Discussions: GitHub Discussions
• Documentation: AivisSpeech API Docs

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Made with ❤️ for the Japanese TTS community