A cross-platform desktop All-in-One assistant for Claude Code, Codex, OpenCode, OpenClaw, Grok Build & Hermes Agent. Only official website: ccswitch.io
Kokoro MCP Server
TTS toolkit built on Kokoro-82M with librosa audio enhancement, MCP server for Claude/Cursor, CLI & Python API. Free & open-source for YouTube creators.
Install
brew install espeak ffmpegInstall command taken from the project's README or registry entry. Always review code before running it.
README excerpt
Read full README on GitHub →Kokoro MCP SERVER: Text To Speech (TTS)
A comprehensive Text-to-Speech toolkit built on Kokoro-82M with audio enhancement, Model Context Protocol (MCP) server integration, CLI interface, and Docker deployment.
📺 Demo Video
Features
- Kokoro-82M TTS Engine: Open-weight model with 82M parameters (510 tokens per pass)
- 🌐 Streamlit Web UI: Enterprise-grade management interface with real-time preview (OPTIONAL)
- Audio Enhancement: Professional processing with librosa (normalization, noise reduction, fade in/out)
- MCP Server: Model Context Protocol integration for Claude Desktop, Cursor, and other AI tools (OPTIONAL)
- CLI Interface: Command-line tools for quick generation (OPTIONAL)
- Batch Processing: Generate multiple audio files efficiently
- Script Processing: Convert complete video scripts with automatic text chunking
- Docker Support: Containerization with docker-compose
- Enterprise Features: Structured logging, configuration management, comprehensive testing
- CI/CD: GitHub Actions pipeline with automated testing
Streamlit Web Interface (Optional)
Beautiful web UI for managing all TTS functionality:
- 🎯 Single Generation - Convert text with real-time preview
- 📦 Batch Processing - Process multiple texts in one go
- 📄 Script Processing - Complete video script conversion
- 🔍 Voice Explorer - Compare all 12 voices side-by-side
- ⚙️ Configuration - Manage settings visually
- 📊 Analytics - Track generations with charts and statistics
Install with: pip install -e ".[streamlit]" or pip install -e ".[complete]"
Quick Start:
python run_streamlit.py
# Opens at http://localhost:8501
📚 See STREAMLIT_README.md for complete Streamlit documentation.
Building on Kokoro-82M
What Kokoro-82M Provides Out-of-the-Box: Kokoro-82M is an exceptional open-weight TTS model that delivers: core neural TTS inference with 82M parameters, a basic Python inference library (KPipeline), 10 professional voice packs (male/female, American/British), phonemization (G2P) system, and raw 24kHz audio output with a 510-token processing limit per pass.
What aparsoft-tts Adds: We integrate Kokoro-82M's excellent TTS inference with comprehensive development tooling and workflow enhancements. This toolkit adds:
- Audio post-processing - Normalization, noise reduction, silence trimming, and fade in/out using librosa
- Automated script workflows - Direct script-to-voiceover conversion with paragraph detection and gap management
- IDE-native generation - MCP server integration eliminates context switching for Claude Desktop and Cursor users
- Deployment infrastructure - Docker deployment, structured logging, configuration management, and comprehensive testing
- Batch processing - CLI and Python APIs for processing multiple segments efficiently
Technical Implementation
Audio Enhancement (librosa Integration):
This toolkit adds an audio processing pipeline on Kokoro generated TTS output:
# Without enhancement - raw Kokoro output
audio = kokoro_pipeline(text)
# With enhancement
audio = enhance_audio(
kokoro_output,
normalize=True, # Consistent volume
trim_silence=True, # Remove dead air
noise_reduction=True, # Spectral gating
add_fade=True # Smooth transitions
)
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