Enables solving Constraint Satisfaction Problems (CSP) like N-Queens, graph coloring, and Sudoku, as well as Linear Programming optimization problems through both MCP tools and HTTP API endpoints.
An MCP server that enables Large Language Models to interactively create, edit, and solve constraint models using backends like MiniZinc, Z3, PySAT, and Clingo. It bridges natural language with symbolic reasoning for solving complex logical, SAT, SMT, and optimization problems.
Enables Large Language Models to submit and solve constraint satisfaction and optimization problems using Google OR-Tools through JSON model specification.
MCP-ORTools integrates Google's OR-Tools constraint programming solver with Large Language Models through the MCP, enabling AI models to:
Submit and validate constraint models
Set model parameters
Solve constraint satisfaction and optimization problems
Retrieve and analyze solution