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Alternatives to HiGHS MCP Server

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    Related Servers

    • A
      license
      Not graded
      quality
      D
      maintenance
      Enables solving linear programming (LP) and mixed-integer linear programming (MILP) optimization problems through natural language, with built-in simplex and branch-and-cut solvers plus infeasibility diagnostics. Includes optional OR-Tools fallback for larger problems and supports parsing optimization problems from natural language descriptions.
      MIT
    • F
      license
      B
      quality
      D
      maintenance
      Enables AI assistants to solve linear, integer, mixed-integer, and knapsack optimization problems using Google OR-Tools via a simple JSON interface.
      3
      -
    • F
      license
      Not graded
      quality
      D
      maintenance
      Enables AI applications to solve optimization problems including linear programming, mixed-integer programming, and quadratic programming using the Gurobi solver installed on the local device.
      1
      -
    • A
      license
      A
      quality
      F
      maintenance
      Provides constraint satisfaction and optimization capabilities to LLMs and AI agents for scheduling, resource allocation, routing, budget optimization, and configuration problems using Google OR-Tools CP-SAT solver.
      5
      5
      Apache 2.0
    • A
      license
      Not graded
      quality
      D
      maintenance
      Enables Claude Desktop and MCP-compatible agents to formulate, solve, and certify mathematical optimization problems using production-grade open-source solvers, providing mathematically grounded decisions.
      MIT
    • A
      license
      A
      quality
      C
      maintenance
      Enables AI assistants to solve linear, nonlinear, and integer optimization models with a locally installed LINGO 11 solver and read the results back as structured data — status, objective, variable values, reduced costs, row slacks, and dual prices. It also runs arbitrary LINGO command-window analyses, reports the detected installation and license status, and lists the bundled sample models, correctly flagging infeasible or unbounded models instead of inventing an optimum.
      4
      1
      MIT