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Solve constraint and optimization problems from MiniZinc models in one tool.
Copy the install command and let the AI configure it · recommended for beginners
No copy-paste install info for "minizinc-mcp" yet — see the docs or source repo.
Use MiniZinc to model an employee scheduling problem: 10 employees cover 7 days with morning and evening shifts; each shift needs at least 2 people; each employee can work at most 5 shifts per week and cannot work a morning shift right after an evening shift. Find a feasible schedule with minimum total overtime and output the roster.
Returns the MiniZinc solution result, including feasibility, optimal objective value, and a day-by-day shift roster.
Use MiniZinc to solve a traveling salesman problem with 8 cities. The distance matrix is: [paste matrix here]. Start and end at city 1, find the visiting order with the minimum total distance, and report the shortest distance.
Returns the optimal visit order, total distance, and the corresponding MiniZinc solving status.
Build a MiniZinc model to assign 6 projects to 4 engineers. Each project must be assigned to one person, each engineer can handle at most 2 projects, and some projects can only be handled by specific engineers. The goal is to balance workload as evenly as possible and output the assignment.
Returns a constraint-satisfying project assignment, along with the balance objective value or an explanation if no feasible solution exists.
Find minimal variable fixes that make equations valid from noisy OCR data.
Access COPT docs, sample code, and citations to use solver APIs accurately.
Access MiniMax APIs for speech, image, and video generation through MCP.
Access multiple AI providers in one terminal for generation, search, and comparison.
Build, debug, and manage software tasks with natural language across LLMs.
A minimal MCP server template for testing and rapid development.