What runtime does Smallest AI MCP Server require?
It requires Python 3.11+ and dependencies installed from `requirements.txt`. Docker is also supported.
@Akshay-Sisodia
基本信息
Production-grade ModelContextProtocol (MCP) server for the Smallest AI Waves platform. Exposes all Waves TTS and voice cloning features as MCP tools and resources. Ready for deployment.
使用下面的配置,将此服务器添加到你的 MCP 客户端。
{
"mcpServers": {
"smallest-ai-mcp": {
"command": "python",
"args": [
"server.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。
It is a production-grade Model Context Protocol (MCP) server that bridges the Waves Text-to-Speech and Voice Cloning API with any MCP-compatible LLM or agent. It is designed for speed, security, and ease of deployment.
Clone the repository, install dependencies with pip install -r requirements.txt, copy .env.example to .env and add your WAVES_API_KEY, then start the server with python server.py. Alternatively, build and run the Docker image while passing the API key as an environment variable. All features are exposed as MCP tools.
It requires Python 3.11+ and dependencies installed from `requirements.txt`. Docker is also supported.
Copy `.env.example` to `.env`, edit it to add your real WAVES_API_KEY, and never commit secrets to git. You can also pass it via the Docker `-e` flag.
Yes, a Dockerfile is provided. Build with `docker build -t smallest-ai-mcp .` and run with `docker run -p 8000:8000 -e WAVES_API_KEY=your_key smallest-ai-mcp`.
MIT.
This open-source curriculum introduces the fundamentals of Model Context Protocol (MCP) through real-world, cross-language examples in .NET, Java, TypeScript, JavaScript, Rust and Python. Designed for developers, it focuses on practical techniques for building modular, scalable,
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