Local Speech-to-Text MCP Server
About
A high-performance Model Context Protocol (MCP) server providing local speech-to-text transcription using whisper.cpp, optimized for Apple Silicon.
Details
- Author
- SmartLittleApps
- Downloads
- 476
- Categories
- Other
Jump to
- 100% local processing with complete privacy
- 15x+ real‑time transcription speed on Apple Silicon
- Speaker diarization to identify and separate multiple speakers
- Universal audio support with automatic format conversion (MP3, M4A, FLAC, etc.)
- Multiple output formats: txt, json, vtt, srt, csv
- Low memory footprint (<2GB) and TypeScript implementation
Setting up with Highlight
This MCP is not yet compatible with Highlight’s one-click setup. However, you can still use it with Highlight by following these steps:
- Download and install Highlight from highlightai.com/download
- Navigate to the plugins tab and select "Add Custom Plugin"
-
Configure the plugin with the settings below
Plugin Name
Local Speech-to-Text MCP ServerCommand (node, npx, python, etc.)Please refer to the README for specific instructions on how to obtain API keys or other required environment variables.
- Enable "Start Automatically" if you want the plugin to start when Highlight launches
From the repository
Install Node.js 18+, whisper.cpp, ffmpeg, and optionally Python 3.8+ for speaker diarization. Clone the repository, run npm install, npm run build, and npm run setup:models. Set the HF_TOKEN environment variable for speaker diarization. Add the server path to your MCP client configuration. Available tools include transcribe, transcribe_long, transcribe_with_speakers, list_models, health_check, and version.
Claude Desktop / Cursor
Paste into your MCP client config file to install this server.
{
"mcpServers": {
"local speech-to-text mcp server": {
"whisper-mcp": {
"command": "node",
"args": [
"path/to/local-stt-mcp/mcp-server/dist/index.js"
]
}
}
}
}McpServers
{
"whisper-mcp": {
"command": "node",
"args": [
"path/to/local-stt-mcp/mcp-server/dist/index.js"
]
}
}Local Speech-to-Text MCP Server
A high-performance Model Context Protocol (MCP) server providing local speech-to-text transcription using whisper.cpp, optimized for Apple Silicon.
🎯 Features
- 🏠 100% Local Processing: No cloud APIs, complete privacy
- 🚀 Apple Silicon Optimized: 15x+ real-time transcription speed
- 🎤 Speaker Diarization: Identify and separate multiple speakers
- 🎵 Universal Audio Support: Automatic conversion from MP3, M4A, FLAC, and more
- 📝 Multiple Output Formats: txt, json, vtt, srt, csv
- 💾 Low Memory Footprint: <2GB memory usage
- 🔧 TypeScript: Full type safety and modern development
🚀 Quick Start
Prerequisites
- Node.js 18+
- whisper.cpp (brew install whisper-cpp)
- For audio format conversion: ffmpeg (brew install ffmpeg) - automatically handles MP3, M4A, FLAC, OGG, etc.
- For speaker diarization: Python 3.8+ and HuggingFace token (free)
Supported Audio Formats
- Native whisper.cpp formats: WAV, FLAC
- Auto-converted formats: MP3, M4A, AAC, OGG, WMA, and more
- Automatic conversion: Powered by ffmpeg with 16kHz/mono optimization for whisper.cpp
- Format detection: Automatic format detection and conversion when needed
Installation
```bash
git clone https://github.com/your-username/local-stt-mcp.git
cd local-stt-mcp/mcp-server
npm install
npm run build
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