Enables formal logical reasoning, mathematical problem-solving, and proof construction across 11 logic systems including propositional, predicate, modal, fuzzy, and probabilistic logic. Integrates external solvers (Z3, ProbLog, Clingo) for advanced reasoning, with support for proof storage, argument scoring, and cross-system translation.
Enables formal verification of LLM outputs against compliance ontologies using Z3 SMT solver. Validates that AI-generated content adheres to regulatory requirements like HIPAA or mortgage compliance rules.
MCP server that gives LLMs access to formal verification via Z3 and SWI-Prolog, plus tree-sitter-based source code analysis. Translates natural language problems into formal logic using a template-based pipeline, verifies results with mathematical certainty, and analyzes call graphs for reachability, dead code, and impact analysis.
Provides symbolic reasoning capabilities by converting natural language logical problems into Answer Set Programming (ASP) format and solving them using the Clingo solver. Enables users to perform formal logical reasoning, verify logical arguments, and get step-by-step explanations for complex logical problems.
A best-effort universal logic and numerical solver interface using MCP that implements the 'LLM sandwich' model to process queries, call dedicated solvers (ortools, cvxpy, z3), and verbalize results.