MCP Reasoner
Implements beam search and thought evaluation for structured problem-solving, enabling exploration of multiple solution paths in complex reasoning tasks.
About
This MCP reasoner, developed by Jacck, provides a systematic approach to problem-solving using beam search and thought evaluation. Built with TypeScript and leveraging the Model Context Protocol SDK, it offers capabilities for exploring multiple solution paths, scoring thoughts, and managing tree-based reasoning states. The reasoner implements a configurable beam width, depth-limited search, and statistical analysis of the reasoning process. It's designed for tackling complex problems that require step-by-step analysis, such as mathematical puzzles, logical deductions, and multi-stage planning tasks. This implementation is particularly valuable for enhancing AI assistants' problem-solving abilities in scenarios requiring structured thinking and exploration of multiple solution strategies.
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