Whisper Speech Recognition MCP Server
@BigUncle
关于 Whisper Speech Recognition MCP Server
A high-performance speech recognition MCP server based on Faster Whisper, providing efficient audio transcription capabilities.
基本信息
配置
使用下面的配置,将此服务器添加到你的 MCP 客户端。
{
"mcpServers": {
"Fast-Whisper-MCP-Server": {
"command": "python",
"args": [
"whisper_server.py"
]
}
}
}工具
未检测到工具
工具是从 README 中自动提取的。维护者可以在 ## Tools 标题下列出工具,即可填充这部分内容。
概览
What is Whisper Speech Recognition MCP Server?
A high-performance speech recognition MCP server based on Faster Whisper, providing efficient audio transcription capabilities. It is designed for developers who want to integrate speech-to-text into AI tools like Claude Desktop.
How to use Whisper Speech Recognition MCP Server?
Install dependencies (Python 3.10+, Faster Whisper, PyTorch, MCP), then run start_server.bat on Windows or python whisper_server.py on other platforms. Configure the server in Claude Desktop by adding its path to claude_desktop_config.json. Three tools are available: get_model_info, transcribe, and batch_transcribe.
Key features of Whisper Speech Recognition MCP Server
- Integrated with Faster Whisper for efficient speech recognition
- Batch processing acceleration for improved transcription speed
- Automatic CUDA acceleration when available
- Support for multiple model sizes (tiny to large-v3)
- Output formats: VTT subtitles, SRT, and JSON
- Model instance caching to avoid repeated loading
Use cases of Whisper Speech Recognition MCP Server
- Transcribe a single audio file via the
transcribetool - Batch transcribe all audio files in a folder using
batch_transcribe - Integrate speech-to-text capabilities into Claude Desktop
- Process long audio files with VAD (Voice Activity Detection) for improved accuracy
FAQ from Whisper Speech Recognition MCP Server
What are the runtime dependencies?
Python 3.10+, faster-whisper>=0.9.0, PyTorch and torchaudio (CUDA or CPU version), and mcp[cli]>=1.2.0.
How do I start the Whisper Speech Recognition MCP Server?
On Windows, run start_server.bat. On other platforms, run python whisper_server.py from the project directory.
How do I integrate the server with Claude Desktop?
Edit claude_desktop_config.json (located in %APPDATA%\Claude on Windows or ~/Library/Application Support/Claude on macOS) and add the server configuration with the command python and the path to whisper_server.py.
What model sizes are supported?
The server supports model sizes from tiny up to large-v3, allowing a trade-off between speed and accuracy.
What output formats are available?
Transcriptions can be produced in VTT (subtitles), SRT (subtitles), or JSON formats.
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