MCP-ORTools

what is MCP-ORTools?

MCP-ORTools is a Model Context Protocol (MCP) server implementation that utilizes Google OR-Tools for constraint solving, designed to work with Large Language Models through standardized constraint model specifications.

how to use MCP-ORTools?

To use MCP-ORTools, install the package via pip, configure the server settings in the appropriate configuration file, and specify your models in JSON format to submit and solve constraint problems.

key features of MCP-ORTools?

• Full support for OR-Tools CP-SAT solver
• JSON-based model specification
• Support for integer and boolean variables, linear constraints, and optimization objectives
• Ability to handle various constraint types including binary logic and portfolio selection problems

use cases of MCP-ORTools?

1. Solving optimization problems in operations research.
2. Implementing constraint satisfaction problems in AI applications.
3. Assisting in decision-making processes through model validation and analysis.

FAQ from MCP-ORTools?

• What types of problems can MCP-ORTools solve?

MCP-ORTools can solve a variety of constraint satisfaction and optimization problems, including knapsack and portfolio selection problems.

• Is there a specific programming language required?

MCP-ORTools is implemented in Python and requires familiarity with JSON for model specifications.

• How can I contribute to the project?

You can contribute by cloning the repository, making improvements, and submitting pull requests on GitHub.