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 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.
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
A Model Context Protocol server that bridges MCP clients with local LLM services, enabling seamless integration with MCP-compatible applications through standard tools like chat completion, model listing, and health checks.
An educational implementation of a Model Context Protocol server that demonstrates how to build a functional MCP server integrating with various LLM clients.
