GitHub Configuration
Mathematical Optimization MCP Server with PuLP and OR-Tools support
Overview
what is MCP Optimizer?
MCP Optimizer is a mathematical optimization server that supports various optimization problem types using PuLP and OR-Tools.
how to use MCP Optimizer?
To use MCP Optimizer, integrate it with LLM clients like Claude Desktop or Cursor, or run it via Docker or pip installation. Configuration involves adding the server details to the client settings.
key features of MCP Optimizer?
- Supports multiple optimization problem types including linear programming, assignment problems, and financial optimization.
- Provides integration with various LLM clients and Docker support.
- Offers comprehensive testing and production-ready architecture.
use cases of MCP Optimizer?
- Solving linear programming problems for resource allocation.
- Assigning tasks to workers optimally.
- Portfolio optimization for investment management.
FAQ from MCP Optimizer?
- What types of optimization problems can MCP Optimizer solve?
MCP Optimizer can solve linear programming, assignment, transportation, knapsack, routing, scheduling, and financial optimization problems.
- Is MCP Optimizer easy to integrate with existing systems?
Yes! It provides various integration methods including Docker, pip, and direct LLM client support.
- How can I test MCP Optimizer?
You can run comprehensive tests included in the repository to ensure functionality.
Server Config
{
"mcpServers": {
"mcp-optimizer": {
"command": "uvx",
"args": [
"mcp-optimizer"
]
}
}
}Project Info
Created At
a year agoUpdated At
a year agoAuthor Name
dmitryanchikovStar
0Language
PythonLicense
-Category
research-and-data
Recommend Servers
View AllFilesystem
@modelcontextprotocol
2 months ago
虎嗅嗅 Ai行业参谋
2 hours ago
Tavily Mcp
@tavily-ai
JavaScript
a year ago
Crevio
2 days ago
Serper MCP Server
@garymengcom
A Serper MCP Server
Python
a year ago