What are the prerequisites?
Python 3.10+, Uvicorn, Google Fire, an AssemblyAI API key, and optionally Docker.
@Charisma2595
基本信息
暂无概览
使用下面的配置,将此服务器添加到你的 MCP 客户端。
{
"mcpServers": {
"transcription_mcp_server": {
"command": "uv",
"args": [
"run",
"mcp",
"dev",
"mcpserver_transcription.py"
]
}
}
}工具列表暂未提供
当前收录暂时没有可展示的工具列表,不代表服务没有工具。请查阅项目文档了解支持的能力。
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。
Transcription MCP Sever is an MCP (Model-Context-Protocol) server for transcribing MP3 audio files using the AssemblyAI API. It provides command-line and Docker-based tools to transcribe audio, targeting podcasters, content creators, educators, and business teams.
Install dependencies from requirements.txt, set your AssemblyAI API key as the API_KEY environment variable, then run with mcp dev or mcp install to connect with an AI assistant like Claude, or use the provided client script with a file path.
Python 3.10+, Uvicorn, Google Fire, an AssemblyAI API key, and optionally Docker.
Set it as an environment variable: `export API_KEY="your_assemblyai_api_key"` on Linux/macOS, or `set API_KEY="your_assemblyai_api_key"` on Windows CMD.
All transcripts are saved in a local folder named `transcripts/`.
Only MP3 files are supported for transcription.
Yes, it can run directly on a local machine using Python and Uvicorn. Docker is optional.
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