Jacck/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:
bash
pip install git+https://github.com/Jacck/mcp-ortools.git
2. Configure Claude Desktop
Create the configuration file at %APPDATA%\Claude\claudedesktopconfig.json (Windows) or ~/Library/Application Support/Claude/claudedesktopconfig.json (macOS):
json
"mcpServers": {
"ortools": {
"command": "python",
"args": ["-m", "mcportools.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 ( =)
.eq() for equality (==)
.ne() for not equal (!=)
## Usage Examples
### Simple Optimization Model
json
"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.
json
"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:
json
"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