MCP-ORTools

What is MCP-ORTools?

MCP-ORTools is a server implementation of the Model Context Protocol (MCP) using Google OR-Tools for constraint solving. It enables large language models to interact with constraint models for efficient problem-solving.

How to use MCP-ORTools?

To use MCP-ORTools, install the package via pip, configure your application with a setup file, and define models in JSON format specifying variables, constraints, and optional objectives.

Key features of MCP-ORTools?

• Integration with Google OR-Tools for constraint programming
• JSON-based model specification approach
• Comprehensive support for various optimization problems
• Compatibility with both integer and boolean variables
• Extensive constraint relationship definitions

Use cases of MCP-ORTools?

1. Optimizing supply chain logistics through integer programming.
2. Solving scheduling problems within operations management.
3. Assisting in combinatorial optimization tasks such as the knapsack problem.

FAQ from MCP-ORTools?

• What types of problems can MCP-ORTools solve?

MCP-ORTools can address a wide range of optimization and constraint satisfaction problems using linear and binary constraints.

• Is there support for different variable types?

Yes, the implementation supports both integer and boolean variables.

• How can I define constraints in my models?

Constraints should be defined using OR-Tools method syntax, including relational operators and methods for equality, inequality, and linear combinations.