MCP (Model Context Protocol) server for Gurddy optimization library - CSP, LP, and SciPy integration for advanced optimization
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# Gurddy MCP Server [](https://pypi.org/project/gurddy_mcp/) [](https://pypi.org/project/gurddy_mcp/) [](https://opensource.org/licenses/MIT) [](https://gurddy-mcp.fly.dev) A comprehensive Model Context Protocol (MCP) server for solving Constraint Satisfaction Problems (CSP), Linear Programming (LP), Minimax optimization, and SciPy-powered advanced optimization problems. Built on the `gurddy` optimization library with SciPy integration, it supports solving various classic problems through two MCP transports: stdio (for IDE integration) and streamable HTTP (for web clients). **🚀 Quick Start (Stdio):** `pip install gurddy_mcp` then configure in your IDE **🌐 Quick Start (HTTP):** `docker run -p 8080:8080 gurddy-mcp` or see deployment guide **📦 PyPI Package:** [https://pypi.org/project/gurddy_mcp](https://pypi.org/project/gurddy_mcp) ## Main Features ### 🎯 CSP Problem Solving - **N-Queens Problem**: Place N queens on an N×N chessboard with no attacks - **Graph Coloring**: Assign colors to vertices so adjacent vertices differ - **Map Coloring**: Color geographic regions with adjacent regions differing - **Sudoku Solver**: Solve standard 9×9 Sudoku puzzles - **Logic Puzzles**: Einstein's Zebra puzzle and custom logic problems - **Scheduling**: Course scheduling, meeting scheduling, resource allocation - **General CSP Solver**: Support for custom constraint satisfaction problems ### 📊 LP/Optimization Problems - **Linear Programming**: Continuous variable optimization with linear constraints - **Mixed Integer Programming**: Optimization with integer and continuous variables - **Production Planning**: Resource-constrained production optimization with sensitivity …
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