MCP-ORTools

by MCP-Reasoner

97 downloads

Not rated

GitHub

Other

About

Model Context Protocol (MCP) server implementation using Google OR-Tools for constraint solving

Details

Author: MCP-Reasoner
Downloads: 97
Categories: Other

Setting up with Highlight

This MCP is not yet compatible with Highlight’s one-click setup. However, you can still use it with Highlight by following these steps:

Download and install Highlight from highlightai.com/download
Navigate to the plugins tab and select "Add Custom Plugin"
Configure the plugin with the settings below

Plugin Name MCP-ORTools

Command (node, npx, python, etc.)

Please refer to the README for specific instructions on how to obtain API keys or other required environment variables.
Enable "Start Automatically" if you want the plugin to start when Highlight launches

Setting up with Cursor

Open Cursor's settings
Navigate to the MCP section
Click "Add new Global MCP server"
Copy and paste the configuration below based on your operating system

JSON

{
    "mcpServers": {
        "mcp-ortools": {
            "ortools": {
                "command": "python",
                "args": [
                    "-m",
                    "mcp_ortools.server"
                ]
            }
        }
    }
}

JSON

{
    "mcpServers": {
        "mcp-ortools": {
            "ortools": {
                "command": "python",
                "args": [
                    "-m",
                    "mcp_ortools.server"
                ]
            }
        }
    }
}

JSON

{
    "mcpServers": {
        "mcp-ortools": {
            "ortools": {
                "command": "python",
                "args": [
                    "-m",
                    "mcp_ortools.server"
                ]
            }
        }
    }
}

Setting up with Claude Desktop

Open Claude Desktop's settings
Go to the Integrations tab
Click "Add MCP Server"
Use the configuration below based on your operating system

Note: Make sure Claude Desktop is running before attempting to connect.

JSON

{
    "mcpServers": {
        "mcp-ortools": {
            "ortools": {
                "command": "python",
                "args": [
                    "-m",
                    "mcp_ortools.server"
                ]
            }
        }
    }
}

JSON

{
    "mcpServers": {
        "mcp-ortools": {
            "ortools": {
                "command": "python",
                "args": [
                    "-m",
                    "mcp_ortools.server"
                ]
            }
        }
    }
}

JSON

{
    "mcpServers": {
        "mcp-ortools": {
            "ortools": {
                "command": "python",
                "args": [
                    "-m",
                    "mcp_ortools.server"
                ]
            }
        }
    }
}

Setting up with Windsurf

Open Windsurf's preferences
Go to the Integrations section
Click "Add MCP Integration"
Use the configuration below based on your operating system

JSON

{
    "mcpServers": {
        "mcp-ortools": {
            "ortools": {
                "command": "python",
                "args": [
                    "-m",
                    "mcp_ortools.server"
                ]
            }
        }
    }
}

JSON

{
    "mcpServers": {
        "mcp-ortools": {
            "ortools": {
                "command": "python",
                "args": [
                    "-m",
                    "mcp_ortools.server"
                ]
            }
        }
    }
}

JSON

{
    "mcpServers": {
        "mcp-ortools": {
            "ortools": {
                "command": "python",
                "args": [
                    "-m",
                    "mcp_ortools.server"
                ]
            }
        }
    }
}

Setting up with Cline

Open Cline's settings
Navigate to the Integrations section
Click "Add MCP Server"
Copy and paste the configuration below based on your operating system

Note: Make sure to restart Cline after adding the configuration.

JSON

{
    "mcpServers": {
        "mcp-ortools": {
            "ortools": {
                "command": "python",
                "args": [
                    "-m",
                    "mcp_ortools.server"
                ]
            }
        }
    }
}

JSON

{
    "mcpServers": {
        "mcp-ortools": {
            "ortools": {
                "command": "python",
                "args": [
                    "-m",
                    "mcp_ortools.server"
                ]
            }
        }
    }
}

JSON

{
    "mcpServers": {
        "mcp-ortools": {
            "ortools": {
                "command": "python",
                "args": [
                    "-m",
                    "mcp_ortools.server"
                ]
            }
        }
    }
}

Setting up with Goose

Open Goose's preferences
Go to the Integrations tab
Select "MCP Servers"
Click "Add New Server"
Use the configuration below based on your operating system

JSON

{
    "mcpServers": {
        "mcp-ortools": {
            "ortools": {
                "command": "python",
                "args": [
                    "-m",
                    "mcp_ortools.server"
                ]
            }
        }
    }
}

JSON

{
    "mcpServers": {
        "mcp-ortools": {
            "ortools": {
                "command": "python",
                "args": [
                    "-m",
                    "mcp_ortools.server"
                ]
            }
        }
    }
}

JSON

{
    "mcpServers": {
        "mcp-ortools": {
            "ortools": {
                "command": "python",
                "args": [
                    "-m",
                    "mcp_ortools.server"
                ]
            }
        }
    }
}

From the repository

Install the package via pip install git+https://github.com/Jacck/mcp-ortools.git, then configure Claude Desktop by adding an ortools MCP server entry pointing to python -m mcp_ortools.server in the MCP configuration file. Submit constraint models in JSON format with variables, constraints, and optional objective sections.

Claude Desktop / Cursor

Paste into your MCP client config file to install this server.

{
    "mcpServers": {
        "mcp-ortools": {
            "ortools": {
                "command": "python",
                "args": [
                    "-m",
                    "mcp_ortools.server"
                ]
            }
        }
    }
}

McpServers

{
    "ortools": {
        "command": "python",
        "args": [
            "-m",
            "mcp_ortools.server"
        ]
    }
}

MCP-ORTools

A Model Context Protocol (MCP) server implementation using Google OR-Tools for constraint solving. Designed for use with Large Language Models through standardized constraint model specification.

Overview

MCP-ORTools integrates Google's OR-Tools constraint programming solver with Large Language Models through the Model Context Protocol, enabling AI models to:
- Submit and validate constraint models
- Set model parameters
- Solve constraint satisfaction and optimization problems
- Retrieve and analyze solutions

Installation

1. Install the package:

pip install git+https://github.com/Jacck/mcp-ortools.git

2. Configure Claude Desktop
Create the configuration file at %APPDATA%\Claude\claude_desktop_config.json (Windows) or ~/Library/Application Support/Claude/claude_desktop_config.json (macOS):

{

  "mcpServers": {

    "ortools": {

      "command": "python",

      "args": ["-m", "mcp_ortools.server"]

    }

  }

}

Model Specification

Models are specified in JSON format with three main sections:
- variables: Define variables and their domains
- constraints: List of constraints using OR-Tools methods
- objective: Optional optimization objective

Constraint Syntax

Constraints must use OR-Tools method syntax:
- .__le__() for less than or equal (<=)
- .__ge__() for greater than or equal (>=)
- .__eq__() for equality (==)
- .__ne__() for not equal (!=)

Usage Examples

Simple Optimization Model

{
    "variables": [
        {"name": "x", "domain": [0, 10]},
        {"name": "y", "domain": [0, 10]}
    ],
    "constraints": [
        "(x + y).__le__(15)",
        "x.__ge__(2  y)"
    ],
    "objective": {
        "expression": "40  x + 100  y",
        "maximize": true
    }
}

Knapsack Problem
Example: Select items with values [3,1,2,1] and weights [2,2,1,1] with total weight limit of 2.

{
    "variables": [
        {"name": "p0", "domain": [0, 1]},
        {"name": "p1", "domain": [0, 1]},
        {"name": "p2", "domain": [0, 1]},
        {"name": "p3", "domain": [0, 1]}
    ],
    "constraints": [
        "(2p0 + 2p1 + p2 + p3).__le__(2)"
    ],
    "objective": {
        "expression": "3p0 + p1 + 2p2 + p3",
        "maximize": true
    }
}

Additional constraints example:

{ "constraints": [ "p0.__eq__(1)", // Item p0 must be selected "p1.__ne__(p2)", // Can't select both p1 and p2 "(p2 + p3).__ge__(1)" // Must select at least one of p2 or p3 ] }

Features

- Full OR-Tools CP-SAT solver support
- JSON-based model specification
- Support for:
- Integer and boolean variables (domain: [min, max])
- Linear constraints using OR-Tools method syntax
- Linear optimization objectives
- Timeouts and solver parameters
- Binary constraints and relationships
- Portfolio selection problems
- Knapsack problems

Supported Operations in Constraints
- Basic arithmetic: +, -, - Comparisons: .__le__(), .__ge__(), .__eq__(), .__ne__() - Linear combinations of variables - Binary logic through combinations of constraints

Development

To setup for development:

git clone https://github.com/Jacck/mcp-ortools.git

cd mcp-ortools

pip install -e .

Model Response Format

The solver returns solutions in JSON format:

{

    "status": "OPTIMAL",

    "solve_time": 0.045,

    "variables": {

        "p0": 0,

        "p1": 0,

        "p2": 1,

        "p3": 1

    },

    "objective_value": 3.0

}

Status values:
- OPTIMAL: Found optimal solution
- FEASIBLE: Found feasible solution
- INFEASIBLE: No solution exists
- UNKNOWN: Could not determine solution

License

MIT License - see LICENSE file for details

No reviews yet — be the first

Use Google, GitHub, or an email account so ratings stay tied to real people.

Email sign in

No reviews posted yet.

About

Details

Jump to

Setting up with Highlight

From the repository

Claude Desktop / Cursor

McpServers

MCP-ORTools

Overview

Installation

Model Specification

Constraint Syntax

Usage Examples

Simple Optimization Model

Knapsack Problem

Features

Supported Operations in Constraints

Development

Model Response Format

License

Install

More like this

Sequential Thinking

Filesystem

EverArt

Google Drive

Reactive Resume

FastMCP v2 🚀