Advanced TTS MCP Server
A high-quality, feature-rich Text-to-Speech (TTS) server for generating natural and expressive speech with advanced controls.
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
🚀 Quick Start
Option 1: Deploy to Smithery.ai (Recommended)
🎯 One-Click Deployment to Smithery Platform
- Deploy Now: Visit Smithery.ai and import this repository
- Configure: Set your preferred voice and speech settings
- 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:
- Clone the repository
git clone https://github.com/samihalawa/advanced-tts-mcp.git
cd advanced-tts-mcp
- Install dependencies
npm install
- 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"
}
}
}
- Start using!
# Build TypeScript
npm run build
# Start server
npm start
Restart Claude Desktop and start synthesizing with natural, expressive voices.
🎙️ Available Voices
| Voice ID | Name | Gender | Description |
|---|---|---|---|
af_heart | Heart | Female | Warm, friendly voice (default) |
af_sky | Sky | Female | Clear, bright voice |
af_bella | Bella | Female | Elegant, sophisticated voice |
af_sarah | Sarah | Female | Professional, confident voice |
af_nicole | Nicole | Female | Gentle, soothing voice |
am_adam | Adam | Male | Strong, authoritative voice |
am_michael | Michael | Male | Friendly, approachable voice |
bf_emma | Emma | Female | Young, energetic voice |
bf_isabella | Isabella | Female | Mature, expressive voice |
bm_lewis | Lewis | Male | Deep, resonant voice |
📚 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 segmentsmerge_output- Combine into single filesegment_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
| Format | Quality | Use Case |
|---|---|---|
| WAV | Uncompressed | Highest quality, editing |
| MP3 | Compressed | Web, streaming, sharing |
| FLAC | Lossless | Archival, high-quality storage |
| OGG | Compressed | Open source alternative |
🔧 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.
Verwandte Server
AgentRPC
Connect to any function, any language, across network boundaries using AgentRPC.
ChatSum
Summarize chat messages from a local database file.
Zundamon Voice Synthesis
A voice synthesis server for Zundamon using the VOICEVOX engine.
Discord MCP
An MCP server for interacting with Discord.
Gemini Email Subject Generator MCP
Generates engaging email subjects and detailed thinking processes using Google's Gemini AI model.
Slack
An MCP server for interacting with the Slack API, allowing for sending messages, managing channels, and other workspace actions.
Inbox MCP
An intelligent, LLM-powered email assistant using the Nylas v3 API.
Say MCP Server
A server for voice notifications using VoiceBox, with a fallback to the Mac 'say' command.
LGTM Images
Fetches random LGTM (Looks Good To Me) images for use in code reviews and developer communications.
Telegram MCP Server
Connect to your Telegram account to read and send messages.