joelfuller2016/claude-desktop-realtime-audio-mcp
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Claude Desktop Real-time Audio MCP is a server that facilitates real-time microphone input for Claude Desktop on Windows, integrating with the Model Context Protocol for seamless voice-driven AI interactions.
Claude Desktop Real-time Audio MCP
A Model Context Protocol (MCP) server that enables real-time microphone input for Claude Desktop on Windows. This project bridges the gap between Claude's conversational AI and live voice input through Windows Audio Session API (WASAPI) integration and real-time speech recognition.
π Features
- Real-time Audio Capture: Low-latency microphone input using Windows WASAPI
- Multiple Speech-to-Text Engines: Support for OpenAI Whisper, Azure Speech, and Google Speech
- MCP Integration: Seamless integration with Claude Desktop through the Model Context Protocol
- Voice Activity Detection: Intelligent silence detection and audio chunking
- Device Management: Automatic audio device enumeration and selection
- Cross-format Support: Support for multiple audio formats and sample rates
- Performance Optimized: Minimal latency for natural conversation flow
ποΈ Project Status
π§ Under Active Development
This project is currently in the research and development phase. See the Project Roadmap below for detailed milestones and progress tracking.
π― Vision
Enable natural, voice-driven conversations with Claude Desktop by providing:
- Sub-500ms latency from speech to text
- Robust error handling and graceful degradation
- Easy installation and configuration
- Support for multiple audio input sources
- Extensible architecture for future enhancements
πΊοΈ Project Roadmap
Phase 1: Research & Architecture (Target: June 15, 2025)
- Research Windows WASAPI APIs and real-time audio capture methods
- Design MCP server architecture for audio streaming
- Create proof-of-concept WASAPI audio capture in C++
- Evaluate speech-to-text integration options
- Set up development environment and toolchain
Phase 2: Core Audio Implementation (Target: July 1, 2025)
- Implement WASAPI audio capture module in C++
- Create Node.js FFI bindings for audio module
- Develop real-time audio buffering and streaming system
- Implement audio format conversion and processing pipeline
- Create device enumeration and selection functionality
Phase 3: MCP Server Development (Target: July 20, 2025)
- Implement MCP server using TypeScript SDK
- Create audio capture tools for MCP interface
- Implement speech-to-text integration tools
- Develop configuration and device management resources
- Add error handling and graceful shutdown mechanisms
Phase 4: Speech Recognition Integration (Target: August 10, 2025)
- Integrate OpenAI Whisper for local processing
- Add Azure Speech Services integration
- Implement Google Speech-to-Text support
- Develop real-time transcription with chunking strategies
- Create voice activity detection and silence handling
Phase 5: Claude Desktop Integration (Target: August 25, 2025)
- Test integration with Claude Desktop configuration
- Optimize latency and performance for real-time use
- Implement user preferences and configuration UI
- Create installation and setup automation
- Develop usage examples and demo scenarios
Phase 6: Testing & Documentation (Target: September 15, 2025)
- Create comprehensive test suite for all components
- Write detailed installation and usage documentation
- Develop troubleshooting guides and FAQ
- Perform security and performance audits
- Prepare release packages and distribution
ποΈ Architecture Overview
βββββββββββββββββββ ββββββββββββββββββββ βββββββββββββββββββ
β Claude β β MCP Server β β Audio Module β
β Desktop βββββΊβ (TypeScript) βββββΊβ (C++ WASAPI) β
β β β β β β
βββββββββββββββββββ ββββββββββββββββββββ βββββββββββββββββββ
β β
βΌ βΌ
ββββββββββββββββββββ βββββββββββββββββββ
β Speech-to-Text β β Windows Audio β
β Services β β System β
β (Whisper/Azure/ β β (Microphone) β
β Google) β β β
ββββββββββββββββββββ βββββββββββββββββββ
π οΈ Technology Stack
- Core MCP Server: TypeScript with @modelcontextprotocol/sdk
- Audio Capture: C++ with Windows WASAPI
- Node.js Integration: node-gyp for native module compilation
- Speech Recognition:
- OpenAI Whisper (local processing)
- Azure Speech Services (cloud)
- Google Speech-to-Text (cloud)
- Build System: node-gyp, TypeScript compiler
- Documentation: Markdown with GitHub Pages
π Prerequisites
- Windows 10/11 (Windows 7+ with WASAPI support)
- Node.js 16+ with npm
- Visual Studio Build Tools (for native compilation)
- Python 3.8+ (for node-gyp)
- Git for version control
π¦ Quick Start
Note: This project is under development. Installation instructions will be available with the first release.
# Clone the repository
git clone https://github.com/joelfuller2016/claude-desktop-realtime-audio-mcp.git
cd claude-desktop-realtime-audio-mcp
# Install dependencies
npm install
# Build the project
npm run build
# Configure Claude Desktop
# (Instructions will be provided in setup documentation)
π€ Contributing
We welcome contributions of all kinds! Whether you want to:
- π Report bugs or issues
- π‘ Suggest new features or improvements
- π§ Submit code contributions
- π Improve documentation
- π§ͺ Help with testing
Please see our for detailed information on how to get started.
π Research & References
This project builds upon extensive research in:
- MCP Protocol: Model Context Protocol Documentation
- Windows Audio: WASAPI Documentation
- Speech Recognition: Real-time speech processing and chunking strategies
- Node.js Native Modules: FFI and node-gyp integration patterns
π License
This project is licensed under the MIT License - see the file for details.
π Acknowledgments
- Anthropic for Claude and the Model Context Protocol
- OpenAI for Whisper speech recognition
- The Node.js and TypeScript communities for excellent tooling
- Microsoft for comprehensive WASAPI documentation and examples
π Support & Community
- Issues: GitHub Issues
- Discussions: GitHub Discussions
- Documentation: Wiki
β Star this repository if you find it interesting or useful!
This project aims to make voice-driven AI conversations more natural and accessible. Join us in building the future of human-AI interaction.