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.
Provides constraint satisfaction and optimization capabilities to LLMs and AI agents for scheduling, resource allocation, routing, budget optimization, and configuration problems using Google OR-Tools CP-SAT solver.
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.
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.
