Constrained Optimization MCP Server

Solve constraint programming problems using OR-Tools. This tool is ideal for combinatorial optimization problems, scheduling, assignment problems, and constraint satisfaction with discrete variables. Args: variables: List of variable definitions with 'name', 'type', and optional 'domain'/'shape' constraints: List of constraint expressions as strings objective: Optional objective definition with 'type' and 'expression' parameters: Dictionary of solver parameters description: Optional problem description Returns: Solution results including variable values and feasibility status Example: variables = [ {"name": "x", "type": "integer", "domain": [0, 10]}, {"name": "y", "type": "boolean"} ] constraints = [ "x + y >= 5", "x - y <= 3" ] objective = {"type": "minimize", "expression": "x + y"}

{ "properties": { "constraints": { "items": { "type": "string" }, "title": "Constraints", "type": "array" }, "description": { "default": "", "title": "Description", "type": "string" }, "objective": { "default": null, "title": "Objective", "type": "object" }, "parameters": { "default": null, "title": "Parameters", "type": "object" }, "variables": { "items": { "type": "object" }, "title": "Variables", "type": "array" } }, "required": [ "variables", "constraints" ], "type": "object" }