mcp-solver
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- AlicenseNot gradedqualityNot gradedmaintenanceAn MCP server that enables Large Language Models to interactively create, edit, and solve constraint models using backends like MiniZinc, Z3, PySAT, and Clingo. It bridges natural language with symbolic reasoning for solving complex logical, SAT, SMT, and optimization problems.MIT
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TDQS
Scored across 6 tools
Most tools are clearly distinct: python_status, python_interrupt, python_exec, and submit_code each have a unique role. The only mild overlap is between select_backend and python_reset (both create/configure kernels), but descriptions explicitly steer users to prefer select_backend, resolving the ambiguity.
Four tools share a consistent python_<action> prefix (python_status, python_interrupt, python_exec, python_reset), but select_backend and submit_code break this pattern with a verb_noun convention. Two coexisting conventions make it mixed but still readable.
Six tools is well-scoped for a constraint-solving workflow: backend setup, execution, kernel management, and final submission. Each tool earns its place with no redundancy.
The lifecycle (select_backend -> python_exec iterate -> submit_code, with status/interrupt/reset for kernel control) is well covered. Minor gaps: no tool to list or retrieve previously submitted solutions (only a resource mention), but core workflows are complete.