Whisper Speech Recognition MCP Server

Name: Whisper Speech Recognition MCP Server
Author: BigUncle

@BigUncle

Whisper Speech Recognition MCP Server について

A high-performance speech recognition MCP server based on Faster Whisper, providing efficient audio transcription capabilities.

基本情報

カテゴリ

その他

ランタイム

python

トランスポート

stdio

公開者

BigUncle

設定

以下の設定を使って、このサーバーを MCP 対応クライアントに追加してください。

{
  "mcpServers": {
    "Fast-Whisper-MCP-Server": {
      "command": "python",
      "args": [
        "whisper_server.py"
      ]
    }
  }
}

ツール

ツールは検出されませんでした

ツールは README から自動的に抽出されます。メンテナーは ## Tools という見出しの下に記載することで、このタブに反映できます。

概要

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 transcribe tool
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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