Claude Desktop Real-time Audio MCP

What is Claude Desktop Real-time Audio MCP?

A Model Context Protocol (MCP) server that enables real-time microphone input for Claude Desktop on Windows. It bridges the gap between Claude's conversational AI and live voice input by integrating the Windows Audio Session API (WASAPI) and multiple speech-to-text engines.

How to use Claude Desktop Real-time Audio MCP?

Clone the repository, install dependencies with npm install, build with npm run build, and then configure Claude Desktop to use the server. Detailed installation and setup documentation will be provided with the first release. Note that the project is currently under active development and not yet ready for production use.

Key features of Claude Desktop Real-time Audio MCP

• Real-time audio capture using Windows WASAPI with low latency
• Multiple speech-to-text engines: OpenAI Whisper, Azure Speech, Google Speech
• Intelligent voice activity detection and silence handling
• Automatic audio device enumeration and selection
• Multiple audio format and sample rate support
• MCP integration for seamless use with Claude Desktop

Use cases of Claude Desktop Real-time Audio MCP

• Voice-driven conversations with Claude Desktop for hands-free interaction
• Real-time transcription of microphone input using local or cloud STT engines
• Building accessibility tools that rely on natural voice input for AI assistants
• Rapid prototyping of AI voice interfaces on Windows with minimal latency
• Integrating live speech recognition into any MCP-compatible application

FAQ from Claude Desktop Real-time Audio MCP

What platforms does Claude Desktop Real-time Audio MCP support?

Windows 10/11 (Windows 7+ with WASAPI support) are required. No macOS or Linux support is currently planned.

What are the runtime dependencies?

Node.js 16+ with npm, Visual Studio Build Tools (for native C++ compilation via node-gyp), Python 3.8+, and Git.

Is this project ready for production use?

No — it is under active development (Phase 1 of 6 as of the roadmap) and should be considered experimental. Installation instructions and a stable release are targeted for September 2025.

Which speech-to-text engines are supported?

OpenAI Whisper (local), Azure Speech Services (cloud), and Google Speech-to-Text (cloud) are planned for integration in Phase 4 of the roadmap.

Where does audio data get processed?

Audio capture occurs locally via WASAPI. Speech transcription can be performed locally (Whisper) or sent to cloud services (Azure, Google). No details on data retention or encryption are provided in the current documentation.