Is this server ready for ephemeral environments like `uvx`?
No, this project is not yet set up for ephemeral environments; you must clone the repo and run it locally.
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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": {
"mcp-server-scikit-learn": {
"command": "npx",
"args": [
"@modelcontextprotocol/inspector",
"uv",
"--directory=src/mcp_server_scikit_learn",
"run",
"mcp-server-scikit-learn"
]
}
}
}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。
点击上方按钮,在临时沙箱中运行此服务器并实时获取工具列表。
The mcp-server-scikit-learn is a Model Context Protocol server that provides a standardized interface for interacting with Scikit-learn models and datasets. It is designed for developers who want to train, evaluate, and manage Scikit-learn models via the MCP protocol.
Clone the repository locally, then launch the MCP inspector using npx @modelcontextprotocol/inspector uv --directory=src/mcp_server_scikit_learn run mcp-server-scikit-learn. Alternatively, add it as a MCP server in your configuration with the uv command pointing to the local directory.
No, this project is not yet set up for ephemeral environments; you must clone the repo and run it locally.
The server requires Python and uses `uv` as the package runner; a virtual environment is recommended.
Launch the MCP inspector via npm (`npx @modelcontextprotocol/inspector ...`) to get a browser-accessible debugging URL.
Currently, a local clone is required; there is no `uvx` or pip-based one-line install described in the README.

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