# WarpGBM

Train gradient boosting models quickly and export portable artifacts for smooth deployment. Run fast predictions from newly trained models or existing artifacts. Upload datasets, browse available bac…

## Quick Start

```bash
# Connect this server (installs CLI if needed)
npx -y @smithery/cli@latest mcp add jefferythewind/warpgbm-mcp

# Browse available tools
npx -y @smithery/cli@latest tool list jefferythewind/warpgbm-mcp

# Get full schema for a tool
npx -y @smithery/cli@latest tool get jefferythewind/warpgbm-mcp list_models

# Call a tool
npx -y @smithery/cli@latest tool call jefferythewind/warpgbm-mcp list_models '{}'
```

## Direct MCP Connection

Endpoint: `https://warpgbm-mcp--jefferythewind.run.tools`

## Tools (6)

- `list_models` — List all available ML model backends (warpgbm, lightgbm)
- `train` — Train a gradient boosting model and return portable artifacts (joblib and/or ONNX)
- `predict_from_artifact` — Run inference using a trained model artifact or artifact_id. Use artifact_id for fast predictions right after training …
- `get_agent_guide` — Get the comprehensive agent guide with examples, best practices, and troubleshooting tips for using this service
- `upload_data` — Upload CSV or Parquet files for training. Parses files and returns structured X and y arrays ready for training.
- `submit_feedback` — Submit feedback about the service. Agents can report bugs, request features, or provide general feedback.

```bash
# Get full input/output schema for a tool
npx -y @smithery/cli@latest tool get jefferythewind/warpgbm-mcp <tool-name>
```