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    Forces host coding agents through a structured multi-step reasoning protocol, scaffolding, validating, and formatting their thinking in QUICK, STANDARD, or DEEP modes, plus independent refutation and self-consistency verification passes. It runs entirely locally over stdio or Streamable HTTP using bash with no LLM, API key, GPU, or inference cost.
    6
    MIT
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    This is a MCP server that implements an unreasonable thinking system. It helps generate unconventional solutions: Generating unreasonable thoughts that challenge conventional wisdom. Creating branches of thinking in different directions
    3
    30
    MIT
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    A sophisticated MCP server that provides a multi-dimensional, adaptive reasoning framework for AI assistants, replacing linear reasoning with a graph-based architecture for more nuanced cognitive processes.
    1
    53 npm
    33
    MIT
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    Enables dynamic and reflective problem-solving through a structured thinking process with tools for sequential analysis, tree of thoughts, self-critique, and integration with external knowledge and codebase analysis.
    23 npm
    MIT
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    Remote MCP server for dynamic and reflective problem-solving through structured thinking. Enables step-by-step reasoning with branching, revision tracking, and session management.
    28 npm
    MIT
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    Facilitates structured creative thinking through sequential thought processing, helping users shift from reactive problem-solving to proactive outcome creation using structural tension analysis and stage-based thinking workflows.
    1
    MIT
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    Provides five rigorous reasoning protocols (debate, red team, audit_argument, threat_model, check_study) that run on the AI you're already using, requiring no extra API keys or costs.
    MIT
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    A structured, persistent reasoning workspace for AI. 20 tools for thought chains, branching, revision, search, tagging, and SQLite session persistence that survives context window resets and server restarts.
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    161 npm
    3
    MIT
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    A tool that implements Claude Shannon's problem-solving methodology to help break down complex problems into structured steps including problem definition, constraints, modeling, validation, and implementation.
    1
    18 npm
    70
    MIT
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    Enhances AI model capabilities with structured, retrieval-augmented thinking processes that enable dynamic thought chains, parallel exploration paths, and recursive refinement cycles for improved reasoning.
    1
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    MIT
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    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.
    1
    MIT