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.
@shibuiwilliam
Basic information
No overview available yet
Add this server to your MCP-compatible client using the configuration below.
{
"mcpServers": {
"mcp-server-scikit-learn": {
"command": "npx",
"args": [
"@modelcontextprotocol/inspector",
"uv",
"--directory=src/mcp_server_scikit_learn",
"run",
"mcp-server-scikit-learn"
]
}
}
}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.
Fetch the live tool list by running this server in a temporary sandbox using the button above.
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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