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?
- Optimizing supply chain logistics through integer programming.
- Solving scheduling problems within operations management.
- 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.