Enables LLM clients to run Python code in a persistent, user-selected interpreter via MCP, with tools for data loading, summaries, regressions, diagnostics, and plotting, while keeping sessions alive between calls and isolating crashes.
Enables LLM clients to load, clean, visualize, and analyze tabular datasets, and to generate multi-format analytic reports through natural language instructions.
Enables data analysis and visualization operations such as loading CSV/Excel/JSON files, computing summary statistics, generating charts, and exploring datasets via SSE/HTTP.
Enables AI clients such as Codex, Claude, and Cursor to control Rhino and Grasshopper through natural language, including creating and modifying geometry, managing layers, inspecting scenes, and running Grasshopper operations.
Provides a comprehensive MCP server for data preprocessing, analysis, mathematical modeling, and visualization, enabling agents to load, clean, analyze, model, and plot data with tracking and dynamic method extension capabilities.
