I craft unique cereal names, stories, and ridiculously cute Cereal Baby images.

MCP-ORTOOLS
Model Context Protocol (MCP) -Server-Implementierung mit Google oder-Tools zur Einschränkungslösung
1
Github Watches
1
Github Forks
9
Github Stars
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
- Install the package:
pip install git+https://github.com/Jacck/mcp-ortools.git
- 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": [
"(2*p0 + 2*p1 + p2 + p3).__le__(2)"
],
"objective": {
"expression": "3*p0 + p1 + 2*p2 + 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
相关推荐
Evaluator for marketplace product descriptions, checks for relevancy and keyword stuffing.
This GPT assists in finding a top-rated business CPA - local or virtual. We account for their qualifications, experience, testimonials and reviews. Business operators provide a short description of your business, services wanted, and city or state.
I find academic articles and books for research and literature reviews.
Confidential guide on numerology and astrology, based of GG33 Public information
Professional Flask/SQLAlchemy code guide. Follow: https://x.com/navid_re
Entdecken Sie die umfassendste und aktuellste Sammlung von MCP-Servern auf dem Markt. Dieses Repository dient als zentraler Hub und bietet einen umfangreichen Katalog von Open-Source- und Proprietary MCP-Servern mit Funktionen, Dokumentationslinks und Mitwirkenden.
Ein einheitliches API-Gateway zur Integration mehrerer Ethercan-ähnlicher Blockchain-Explorer-APIs mit Modellkontextprotokoll (MCP) für AI-Assistenten.
Mirror ofhttps: //github.com/bitrefill/bitrefill-mcp-server
Reviews

user_2Qcp1tLS
As a loyal user of mcp-ortools, I highly recommend this brilliant tool by Jacck. It seamlessly integrates with various applications and provides exceptional optimization solutions. The comprehensive documentation and active support community enhance its usability. Explore its features at https://github.com/Jacck/mcp-ortools and elevate your projects with mcp-ortools!