MCP-Solver enables Large Language Models to leverage symbolic solvers for complex constraint problems, addressing a key limitation in AI systems.

• Implements the Model Context Protocol (MCP) to connect LLMs with constraint programming systems
• Provides interfaces for Minizinc, PySAT, and Python Z3 for varied problem-solving approaches
• Uses an iterative editing approach to refine solutions when initial attempts fail
• Combines natural language flexibility with formal reasoning precision

This engineering breakthrough matters because it brings mathematical verification and provable guarantees to LLM outputs, essential for critical applications where correctness is paramount.

MCP-Solver: Integrating Language Models with Constraint Programming Systems