#thinking

An MCP server implementation that provides a tool for dynamic and reflective problem-solving through a structured thinking process.

An advanced sequential thinking process using a Multi-Agent System (MAS) built with the Agno framework and served via MCP.

A powerful server providing advanced thinking tools via the Model Context Protocol (MCP) to enhance the reasoning, planning, and iterative refinement capabilities of AI agents like Cline.

Raycast Extension that acts as an MCP client for the Thinking Partner MCP server

Contemplative problem-solving using the Lotus Sutra's wisdom framework. Multi-perspective reasoning with skillful means, non-dual recognition, and meditation pauses.

MCP server for Turtle Soup (lateral thinking puzzles). Start sessions, ask questions, get 4-class judgments (Yes/No/Both/Irrelevant), and reveal the full story when allowed.

An oracle for machines that need to think sideways. Feed it a creative problem; it returns something you can't quite explain but can't stop using. Three free consultations.

Taking the sequential thinking mcp server and prodding it onwards.

Advanced cognitive thinking MCP server with DAG-based thought graph, multiple reasoning strategies, metacognition, and self-evaluation. A significant evolution beyond sequential-thinking MCP, providing structured deep reasoning with graph-based thought management. Features DAG-Based Thought Graph — Thoughts form a directed acyclic graph with branching, merging, and cross-edges (not just a linear chain) 5 Reasoning Strategies — Sequential, Dialectic (thesis→antithesis→synthesis), Parallel, Analogical, Abductive (inference to best explanation) Confidence Scoring — Multi-factor confidence evaluation with support/contradiction analysis, depth penalties, and knowledge integration boosts Self-Critique — Automatic critique generation with severity levels and confidence adjustments Metacognitive Engine — Detects stuck states, stagnation, declining confidence; suggests strategy switches and corrective actions Knowledge Integration — Attach external knowledge to thoughts, detect gaps, validate consistency across sources Thought Pruning — Dead-end detection, redundancy removal, deep unproductive branch elimination, path optimization