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MCP Simple AivisSpeech

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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

Related MCP server: AivisSpeech MCP Server

📋 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

When using Claude Code, start the MCP server manually before using it.

Using npx ensures you always get the latest version automatically. No manual updates needed.

  1. Start the AivisSpeech MCP server manually in a separate terminal from the one where you're using Claude Code

npx @shinshin86/mcp-simple-aivisspeech@latest
  1. Register the MCP server with Claude Code

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
  1. Verify the tools are recognized

claude mcp list

# Or launch Claude Code and use
/mcp

If aivisspeech is displayed, the setup was successful.

💡 Tip: Claude Code doesn't auto-execute commands for safety. If you forget to start the server, the tools won't appear. During development, keep the above npx command running in a terminal, or use process managers like pm2 or systemd --user for persistent operation.

Using Claude Desktop

For manual configuration with Claude Desktop, you can simply add the following configuration:

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, complete these setup steps to ensure AivisSpeech is 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.

This tool accepts several configuration parameters, including the following options:

  • 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 usage:

{
  "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.

This function returns: List of speakers with their IDs, names, and available voice styles.

🔔 notify_completion

Play a voice notification when tasks are completed.

This tool accepts several configuration parameters, including the following options:

  • 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 usage:

{
  "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.

This function 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

When using MCP clients in production, use npx @shinshin86/mcp-simple-aivisspeech@latest in your MCP configuration. No local setup is required, and you always get the latest version.

For development, clone the repository and use npm run dev for hot reload, or 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 offers comprehensive functionality, providing several key capabilities:

  • 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

Consider these troubleshooting approaches to resolve this issue: Ensure AivisSpeech Engine is running on the correct port.

Audio Playback Fails

Error: Audio player exited with code 1

Consider these troubleshooting approaches to resolve this issue:

  • 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

Consider these troubleshooting approaches to resolve this issue: Check file permissions and system audio settings.

Debug Mode

To enable verbose logging, run the following command:

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 from the community. Contributors can get started by completing these essential 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

📞 Support


Made with ❤️ for the Japanese TTS community

Available Tools

1 tool
check_engine_statusB

Check if AivisSpeech engine is running

ParametersJSON Schema
NameRequiredDescriptionDefault

No parameters

TDQS

B3.1/5.0
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 checking engine status but fails to describe what 'running' means, potential error conditions, response format, or any side effects. This leaves significant gaps for an agent to understand the tool's behavior.

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, clear sentence with no wasted words. It directly states the tool's purpose without redundancy or unnecessary elaboration, making it optimally concise and well-structured.

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?

For a tool with no annotations and no output schema, the description is insufficient. It doesn't explain what the check returns (e.g., boolean status, detailed metrics, error messages), leaving the agent without crucial information to interpret results.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters4/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

The tool has zero parameters with 100% schema description coverage, so no parameter documentation is needed. The description appropriately doesn't discuss parameters, earning a high baseline score for not adding unnecessary information.

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 a specific verb ('Check') and resource ('AivisSpeech engine'), making it immediately understandable. However, with no sibling tools mentioned, there's no opportunity to differentiate from alternatives, preventing a perfect score.

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, prerequisites, or contextual constraints. It merely states what the tool does without indicating appropriate scenarios or limitations.

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 update
    • First observedcheck_engine_status

TDQS

B3.2/5.0

Scored across 1 tool

Disambiguation5/5

With only one tool, there is no possibility of ambiguity or overlap between tools. The tool's purpose is clearly distinct as it is the only one available.

Naming Consistency5/5

A single tool inherently has perfect naming consistency, as there are no other tools to compare against. The tool name follows a clear verb_noun pattern (check_engine_status).

Tool Count2/5

One tool is too few for a server named 'MCP Simple AivisSpeech', which implies speech-related functionality. The scope appears thin, lacking basic operations like text-to-speech or speech-to-text that would be expected in this domain.

Completeness1/5

The tool set is severely incomplete for a speech-related server. It only checks engine status, missing core functionalities such as generating speech, processing audio, or managing speech settings, which are essential for the apparent purpose.

Maintenance

ActivityInactive
ResponsivenessNo issues

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