// MCP TOOL REFERENCE

WARPGBM TOOLS

6 tools from the WarpGBM MCP Server, categorised by risk level.

READ TOOLS

get_agent_guide Get the comprehensive agent guide with examples, best practices, and troubleshooting tips for using this service list_models List all available ML model backends (warpgbm, lightgbm) train Train a gradient boosting model and return portable artifacts (joblib and/or ONNX)

WRITE TOOLS

submit_feedback Submit feedback about the service. Agents can report bugs, request features, or provide general feedback. 2/5 upload_data Upload CSV or Parquet files for training. Parses files and returns structured X and y arrays ready for training. 2/5

EXECUTE TOOLS

predict_from_artifact Run inference using a trained model artifact or artifact_id. Use artifact_id for fast predictions right after training (valid for 5 minutes). 3/5

// FAQ

How many tools does the WarpGBM MCP server have? +

The WarpGBM MCP server exposes 6 tools across 3 categories: Read, Write, Execute.

How do I enforce policies on WarpGBM tools? +

Use Intercept, the open-source MCP proxy. Write YAML rules for each tool — rate limits, argument validation, or deny rules — then run Intercept in front of the WarpGBM server.

What risk categories do WarpGBM tools fall into? +

WarpGBM tools are categorised as Read (3), Write (2), Execute (1). Each category has a recommended default policy.

Enforce policies on WarpGBM

Open source. One binary. Zero dependencies.

npx -y @policylayer/intercept

github.com/policylayer/intercept →