一款用于高级音频转录和处理的模型上下文协议（MCP）服务器，利用OpenAI的Whisper和GPT-4o模型。

[!警告] 本项目已迁移。 活跃开发已迁移至 TJC-LP/sanzaru。该仓库已不再维护，将被归档。请将您的依赖和问题更新到新的仓库。

概述

MCP Server Whisper 通过 OpenAI 最新的转录和语音服务，提供了一种标准化的方式来处理音频文件。通过实现模型上下文协议，它使像 Claude 这样的 AI 助手能够无缝与音频处理能力交互。

主要特点：

• 🔍 高级文件搜索，包含正则表达模式、文件元数据过滤和排序功能
• ⚡ MCP 原生并行处理 - 同时调用多个工具
• 🔄 支持音频类型之间的格式转换
• 📦 **自动压缩处理超大文件
• 🎯 多模型转录，支持所有OpenAI音频模型
• 🗣️ 与GPT-4o音频模型的互动音频聊天
• ✏️ 增强转录，配备专业提示和时间戳支持

MCP Server Whisper

[!WARNING] This project has moved. Active development has migrated to TJC-LP/sanzaru. This repository is no longer maintained and will be archived. Please update your dependencies and issues to the new repo.

Overview

MCP Server Whisper provides a standardized way to process audio files through OpenAI’s latest transcription and speech services. By implementing the Model Context Protocol, it enables AI assistants like Claude to seamlessly interact with audio processing capabilities.

Key features:

• 🔍 Advanced file searching with regex patterns, file metadata filtering, and sorting capabilities
• ⚡ MCP-native parallel processing - call multiple tools simultaneously
• 🔄 Format conversion between supported audio types
• 📦 Automatic compression for oversized files
• 🎯 Multi-model transcription with support for all OpenAI audio models
• 🗣️ Interactive audio chat with GPT-4o audio models
• ✏️ Enhanced transcription with specialized prompts and timestamp support
• 🎙️ Text-to-speech generation with customizable voices, instructions, and speed
• 📊 Comprehensive metadata including duration, file size, and format support
• 🚀 High-performance caching for repeated operations
• 🔒 Type-safe responses with Pydantic models for all tool outputs

Note: This project is unofficial and not affiliated with, endorsed by, or sponsored by OpenAI. It provides a Model Context Protocol interface to OpenAI’s publicly available APIs.

Installation

# Clone the repository
git clone https://github.com/arcaputo3/mcp-server-whisper.git
cd mcp-server-whisper

# Using uv 
uv sync

# Set up pre-commit hooks
uv run pre-commit install

Environment Setup

Create a .env file based on the provided .env.example:

cp .env.example .env

Edit .env with your actual values:

OPENAI_API_KEY=your_openai_api_key
AUDIO_FILES_PATH=/path/to/your/audio/files

Note: Environment variables must be available at runtime. For local development with Claude, use a tool like dotenv-cli to load them (see Usage section below).

Usage

Local Development with Claude