MCP Solver

what is MCP Solver? MCP Solver is a server that implements the Model Context Protocol (MCP) to enable Large Language Models (LLMs) to solve constraint satisfaction problems using MiniZinc constraint programming. how to use MCP Solver? To use MCP Solver, install the package via pip from GitHub. Once installed, you can interact with the server to submit constraint models, validate them, and retrieve solutions using provided tools. key features of MCP Solver? Comprehensive support for MiniZinc constraint models. Asynchronous solving capabilities with timeout management. Validation of parameters and type checking for robustness. Management of the solution state and automatic inclusion of libraries based on constraints. Monitoring of the solver's progress and state. use cases of MCP Solver? Solving complex theatrical casting problems based on various constraints. Assisting in resource allocation decisions in various fields. Supporting optimization tasks in AI-driven applications. FAQ from MCP Solver? What programming languages does MCP Solver support? MCP Solver is built to be used with Python (version 3.9+). You will also need MiniZinc with the Chuffed solver installed. Is MCP Solver suitable for production use? MCP Solver is in its prototype stage and should be used with caution, primarily for experimentation. Where can I find more examples? Further sample chat dialogs and examples are included in the repository's 'examples' folder.

As an MCP (Model Context Protocol) server, MCP Solver enables AI agents to communicate effectively through standardized interfaces. The Model Context Protocol simplifies integration between different AI models and agent systems.

To use MCP Solver, install the package via pip from GitHub. Once installed, you can interact with the server to submit constraint models, validate them, and retrieve solutions using provided tools. key features of MCP Solver? Comprehensive support for MiniZinc constraint models. Asynchronous solving capabilities with timeout management. Validation of parameters and type checking for robustness. Management of the solution state and automatic inclusion of libraries based on constraints. Monitoring of the solver's progress and state. use cases of MCP Solver? Solving complex theatrical casting problems based on various constraints. Assisting in resource allocation decisions in various fields. Supporting optimization tasks in AI-driven applications. FAQ from MCP Solver? What programming languages does MCP Solver support? MCP Solver is built to be used with Python (version 3.9+). You will also need MiniZinc with the Chuffed solver installed. Is MCP Solver suitable for production use? MCP Solver is in its prototype stage and should be used with caution, primarily for experimentation. Where can I find more examples? Further sample chat dialogs and examples are included in the repository's 'examples' folder.

Learn how to integrate this MCP server with your AI agents and leverage the Model Context Protocol for enhanced capabilities.