Advanced TTS MCP Server

A high-quality, feature-rich Text-to-Speech MCP server with native TypeScript implementation. Designed for professional applications requiring natural, expressive speech synthesis with advanced controls and zero external dependencies.

✨ Features

🎯 Advanced Voice Control

• 10 High-Quality Voices - Male and female voices with distinct personalities

• Emotion Control - Neutral, happy, excited, calm, serious, casual, confident

• Dynamic Pacing - Natural, conversational, presentation, tutorial, narrative modes

• Speed & Volume - Precise control from 0.25x to 3.0x speed, 0.1x to 2.0x volume

🚀 Professional Capabilities

• Streaming Audio - Real-time synthesis and playback

• Batch Processing - Handle multiple text segments efficiently

• Multiple Formats - WAV, MP3, FLAC, OGG output support

• Natural Speech Enhancement - Automatic pause insertion and emotion markers

• Queue Management - Handle multiple concurrent requests

🔧 MCP Integration

• 6 Powerful Tools - Complete synthesis, batch processing, voice management

• 2 Rich Resources - Voice capabilities and usage examples

• Real-time Status - Track processing progress and manage requests

• File Management - Save, list, and organize audio outputs

Related MCP server: Say MCP Server

🚀 Quick Start

Option 1: Deploy to Smithery.ai (Recommended)

🎯 One-Click Deployment to Smithery Platform

1. Deploy Now: Visit Smithery.ai and import this repository

2. Configure: Set your preferred voice and speech settings

3. Use Instantly: Access via Claude Desktop or any MCP-compatible client

Benefits:

• ✅ Zero setup required

• ✅ Automatic scaling and updates

• ✅ No model downloads needed

• ✅ Enterprise-grade hosting

📋 Full Smithery Deployment Guide →

Option 2: Local Installation

Prerequisites:

• Node.js 18+

Installation:

1. Clone the repository

git clone https://github.com/samihalawa/advanced-tts-mcp.git
cd advanced-tts-mcp

2. Install dependencies

npm install

3. Configure Claude Desktop

Add to your claude_desktop_config.json:

{
  "mcpServers": {
    "advanced-tts": {
      "command": "node",
      "args": ["dist/index.js"],
      "cwd": "/path/to/advanced-tts-mcp"
    }
  }
}

4. Start using!

# Build TypeScript
npm run build

# Start server
npm start

Restart Claude Desktop and start synthesizing with natural, expressive voices.

🎙️ Available Voices

📚 Usage Examples

Basic Synthesis

# Simple text-to-speech
await synthesize_speech(
    text="Hello! Welcome to Advanced TTS.",
    voice_id="af_heart"
)

Emotional Expression

# Excited announcement
await synthesize_speech(
    text="This is amazing news! You're going to love this new feature!",
    voice_id="af_heart",
    emotion="excited",
    pacing="conversational",
    speed=1.1
)

Professional Presentation

# Tutorial narration
await synthesize_speech(
    text="Step one: Open your browser. Step two: Navigate to the website.",
    voice_id="am_adam", 
    emotion="calm",
    pacing="tutorial",
    speed=0.9
)

Batch Processing

# Multiple segments with pauses
await batch_synthesize(
    segments=[
        "Welcome to our presentation.",
        "Today we'll cover three main topics.", 
        "Let's begin with the first topic."
    ],
    voice_id="af_sarah",
    emotion="confident",
    pacing="presentation",
    merge_output=True,
    segment_pause=1.0,
    save_file=True
)

🛠️ Available Tools

synthesize_speech

Convert text to natural speech with full control over voice characteristics.

Parameters:

• text - Text to synthesize (max 10,000 chars)

• voice_id - Voice selection (see table above)

• speed - Speech rate (0.25-3.0)

• emotion - Voice emotion (neutral, happy, excited, calm, serious, casual, confident)

• pacing - Speech style (natural, conversational, presentation, tutorial, narrative, fast, slow)

• volume - Audio volume (0.1-2.0)

• output_format - File format (wav, mp3, flac, ogg)

• save_file - Save to file (boolean)

• filename - Custom filename

batch_synthesize

Process multiple text segments efficiently with optional merging.

Parameters:

• segments - List of text segments

• merge_output - Combine into single file

• segment_pause - Pause between segments (0.0-5.0s)

• All synthesis parameters from above

get_voices

Retrieve complete voice information and capabilities.

get_status

Check processing status for synthesis requests.

cancel_request

Cancel active synthesis operations.

list_output_files

Browse saved audio files with metadata.

🎛️ Voice Controls

Emotions

• Neutral - Standard, professional tone

• Happy - Upbeat, cheerful expression

• Excited - Enthusiastic, energetic delivery

• Calm - Relaxed, soothing tone

• Serious - Formal, authoritative delivery

• Casual - Relaxed, conversational style

• Confident - Assured, professional tone

Pacing Styles

• Natural - Balanced, human-like rhythm

• Conversational - Casual discussion pace

• Presentation - Professional speaking rhythm

• Tutorial - Educational, clear delivery

• Narrative - Storytelling pace

• Fast - Quick delivery (1.2x base speed)

• Slow - Deliberate delivery (0.8x base speed)

🎵 Audio Formats

🔧 Configuration

Environment Variables

# Model paths (optional)
KOKORO_MODEL_PATH=./kokoro-v1.0.onnx
KOKORO_VOICES_PATH=./voices-v1.0.bin

# Output settings
TTS_OUTPUT_DIR=./audio_output
TTS_MAX_QUEUE_SIZE=100

# Audio settings  
TTS_DEFAULT_VOICE=af_heart
TTS_ENABLE_STREAMING=true

Server Configuration

config = ServerConfig(
    model_path="./kokoro-v1.0.onnx",
    voices_path="./voices-v1.0.bin", 
    output_dir="./audio_output",
    max_queue_size=100,
    enable_streaming=True,
    default_voice="af_heart"
)

🏗️ Architecture

├── src/advanced_tts/
│   ├── __init__.py          # Package initialization
│   ├── server.py            # MCP server implementation  
│   ├── engine.py            # Kokoro TTS engine wrapper
│   ├── models.py            # Data models and validation
│   └── utils.py             # Utility functions
├── pyproject.toml           # Project configuration
├── README.md               # Documentation
└── LICENSE                 # MIT License

🤝 Contributing

Contributions welcome! Areas for improvement:

• Additional voice models

• Real-time streaming synthesis

• Advanced audio effects

• Multi-language support

• Performance optimizations

📄 License

MIT License - see LICENSE for details.

🙏 Acknowledgments

• Kokoro TTS - High-quality neural voice synthesis

• MCP Protocol - Seamless AI model integration

• FastMCP - Efficient server framework

Developed by Sami Halawa

Transform your text into natural, expressive speech with Advanced TTS MCP Server.