Cuba-Thinking is an advanced cognitive reasoning engine designed to transform flat, unstructured AI agent thinking into a structured, verifiable, and persistent process. Operating as a Model Context Protocol (MCP) server, it provides a 6-stage cognitive engine based on Bloom's Taxonomy, a 9-layer anti-hallucination system, and comprehensive bias detection. The tool integrates a Graph-of-Thought (GoT) topology for tracking reasoning paths and preventing circular logic, alongside persistent thought sessions that allow for state accumulation, epistemological rollback, and mode collapse detection. With a sandboxed Process Reward Model (PRM) for secure code evaluation, Cuba-Thinking ensures high-quality, reliable, and bias-aware AI reasoning without cloud dependencies.
主要功能
01Graph-of-Thought (GoT) topology tracking with Tarjan SCC cycle detection
026-stage cognitive engine based on Bloom's Taxonomy state machine
03Sandboxed Process Reward Model (PRM) for secure Python code evaluation
049-layer anti-hallucination system with evidence accumulation and contradiction detection
05Persistent thought sessions with epistemological rollback and mode collapse guard
063 GitHub stars
使用案例
01Improving the depth and quality of AI agent reasoning and problem-solving processes
02Automated evaluation and refinement of AI-generated code snippets for correctness and safety
03Enhancing AI reliability by detecting and mitigating hallucinations, biases, and logical fallacies
