mcp-reasoner

Jacck
225
A systematic reasoning MCP server implementation for Claude Desktop with beam search and thought evaluation.

Overview

mcp-reasoner Introduction

mcp-reasoner is a systematic reasoning MCP server implementation designed for Claude Desktop, utilizing Beam Search and Monte Carlo Tree Search (MCTS) to enhance complex problem-solving capabilities.

How to Use

To use mcp-reasoner, you can switch between two search strategies: Beam Search for straightforward problems and MCTS for more complex scenarios. Adjust parameters like beamWidth and numSimulations to optimize performance.

Key Features

Key features include two search strategies (Beam Search and MCTS), the ability to track reasoning quality, and the introduction of experimental reasoning algorithms with Policy Simulation Layers for improved decision-making.

Where to Use

mcp-reasoner can be used in fields requiring advanced reasoning capabilities, such as artificial intelligence, game development, and complex decision-making systems.

Use Cases

Use cases for mcp-reasoner include enhancing AI problem-solving in games, optimizing decision-making processes in simulations, and developing intelligent systems that require adaptive reasoning.

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