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
Basic information
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.
Add this server to your MCP-compatible client using the configuration below.
{
"mcpServers": {
"smallest-ai-mcp": {
"command": "python",
"args": [
"server.py"
]
}
}
}Tool list not available yet
This listing does not currently have a tool list to display. This does not mean the server has no tools; check its documentation for supported capabilities.
We auto-extract tools from the README. The maintainer can list them under a ## Tools heading to populate this section.
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.
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