MCP (Model Context Protocol) server for TuiML.
Exposes workflow and discovery tools that give LLMs access to all TuiML components (algorithms, preprocessors, datasets, features). New algorithms added to the component registry are automatically discoverable via
tuiml_list / tuiml_describe and usable via tuiml_train / tuiml_benchmark.Run the server (installed with pip install tuiml):
bash
tuiml-mcp
Or run it as a Python module:
bash
python -m tuiml.agent.mcp.server
Server options:
bash
tuiml-mcp --help # Show help
tuiml-mcp --info # Show server info
Configure in Claude Desktop (claude_desktop_config.json):
json
{
"mcpServers": {
"tuiml": {
"command": "tuiml-mcp"
}
}
}
Functions
create_server() -> 'Server'
Create and configure the TuiML MCP server.
Only workflow and discovery tools are exposed as MCP tools (30 total). The internal registry still tracks all 200+ components so that tuiml_list, tuiml_describe, and tuiml_train can dynamically access any algorithm - including new ones added later.
Returns
Server
Configured MCP server exposing TuiML workflow tools, with every handler registered on the constructor as the 2.x SDK expects.
Raises
ImportError
If the 2.x
mcp package is not installed.
run_server()
Run the MCP server using stdio transport.
Returns
None
Blocks until the client disconnects; exits the process if the
mcp package is not installed.
main()
Main entry point for the MCP server (the tuiml-mcp command).
Handles the
--info and --help flags, otherwise runs the stdio server.Returns
None
get_server_info() -> Dict[str, Any]
Get information about the MCP server.
Returns
dict
Server metadata with keys
"name", "version", "description", "mcp_available", and "tools" (a dict with "exposed_tools", "discoverable_components", and "components_by_category" counts).