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
šÆ 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
š 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
š§ 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
š Quick Start
Option 1: Deploy to Smithery.ai (Recommended)
šÆ 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:
- ā Zero setup required
- ā Automatic scaling and updates
- ā No model downloads needed
- ā Enterprise-grade hosting
š Full Smithery Deployment Guide ā
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.
šļø 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 |
š 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
)
š ļø 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.
šļø 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)
šµ 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 |
š§ 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"
)
šļø Architecture
āāā src/advanced_tts/
ā āāā __init__.py # Package initialization
ā āāā server.py # MCP server implementation
ā āāā engine.py # Kokoro TTS engine wrapper
ā āāā models.py # Data models and validation
ā āāā utils.py # Utility functions
āāā pyproject.toml # Project configuration
āāā README.md # Documentation
āāā LICENSE # MIT License
š¤ Contributing
Contributions welcome! Areas for improvement:
- Additional voice models
- Real-time streaming synthesis
- Advanced audio effects
- Multi-language support
- Performance optimizations
š License
MIT License - see LICENSE for details.
š 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.
Related Servers
Mac Messages MCP
A Python bridge for interacting with the macOS Messages app.
Bluesky
Post to the Bluesky social network using the AT Protocol.
WhatsApp Web MCP
Connects AI models to WhatsApp Web using the Model Context Protocol (MCP) to automate and enhance interactions.
Prompt for User Input MCP Server
Enables AI models to prompt users for input directly within their code editor for interactive conversations.
Slack Notify
Send notifications to Slack using OAuth bot tokens.
Waroom MCP
Access the Waroom API through the Model Context Protocol.
Kakao Bot MCP Server
Connects an AI agent to a Kakao Official Account using the Kakao Developers API.
X (Twitter)
Create and publish posts and threads on X (Twitter) directly from your chat using LLMs.
Freshdesk MCP Server
An MCP server for interacting with the Freshdesk API v2, enabling management of customer support tickets and contacts.
AI Interaction Tool
An AI interaction tool with an advanced UI for the Model Context Protocol (MCP).