Provides linear programming (LP), mixed-integer programming (MIP), and quadratic programming (QP) optimization capabilities using the HiGHS solver, enabling AI assistants to solve complex optimization problems like production planning, logistics, and portfolio optimization.
Enables solving linear programming (LP) and mixed-integer linear programming (MILP) optimization problems through natural language, with built-in simplex and branch-and-cut solvers plus infeasibility diagnostics. Includes optional OR-Tools fallback for larger problems and supports parsing optimization problems from natural language descriptions.
Enables Claude Desktop and MCP-compatible agents to formulate, solve, and certify mathematical optimization problems using production-grade open-source solvers, providing mathematically grounded decisions.
Enables Large Language Models to submit and solve constraint satisfaction and optimization problems using Google OR-Tools through JSON model specification.
