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mcp-optimizer

solve_linear_program_tool

Optimize resource allocation, diet plans, manufacturing mixes, and more by solving linear programming problems. Input objective, variables, and constraints to maximize or minimize outcomes efficiently.

Instructions

Solve a linear programming problem using PuLP.

This tool solves general linear programming problems where you want to optimize a linear objective function subject to linear constraints. Use cases: - Resource allocation: Distribute limited resources optimally - Diet planning: Create nutritionally balanced meal plans within budget - Manufacturing mix: Determine optimal product mix to maximize profit - Investment planning: Allocate capital across different investment options - Supply chain optimization: Minimize transportation and storage costs - Energy optimization: Optimize power generation and distribution Args: objective: Objective function with 'sense' ("minimize" or "maximize") and 'coefficients' (dict mapping variable names to coefficients) variables: Variable definitions mapping variable names to their properties (type: "continuous"/"integer"/"binary", lower: bound, upper: bound) constraints: List of constraints, each with 'expression' (coefficients), 'operator' ("<=", ">=", "=="), and 'rhs' (right-hand side value) solver: Solver to use ("CBC", "GLPK", "GUROBI", "CPLEX") time_limit_seconds: Maximum time to spend solving (optional) Returns: Optimization result with status, objective value, variable values, and solver info Example: # Maximize 3x + 2y subject to 2x + y <= 20, x + 3y <= 30, x,y >= 0 solve_linear_program( objective={"sense": "maximize", "coefficients": {"x": 3, "y": 2}}, variables={ "x": {"type": "continuous", "lower": 0}, "y": {"type": "continuous", "lower": 0} }, constraints=[ {"expression": {"x": 2, "y": 1}, "operator": "<=", "rhs": 20}, {"expression": {"x": 1, "y": 3}, "operator": "<=", "rhs": 30} ] )

Input Schema

NameRequiredDescriptionDefault
constraintsYes
objectiveYes
solverNoCBC
time_limit_secondsNo
variablesYes

Input Schema (JSON Schema)

{ "properties": { "constraints": { "items": { "additionalProperties": true, "type": "object" }, "title": "Constraints", "type": "array" }, "objective": { "additionalProperties": true, "title": "Objective", "type": "object" }, "solver": { "default": "CBC", "title": "Solver", "type": "string" }, "time_limit_seconds": { "anyOf": [ { "type": "number" }, { "type": "null" } ], "default": null, "title": "Time Limit Seconds" }, "variables": { "additionalProperties": { "additionalProperties": true, "type": "object" }, "title": "Variables", "type": "object" } }, "required": [ "objective", "variables", "constraints" ], "type": "object" }

MCP directory API

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curl -X GET 'https://glama.ai/api/mcp/v1/servers/dmitryanchikov/mcp-optimizer'

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