Mcp Reasoner

MCP Reasoner provides Claude with advanced reasoning capabilities through two complementary search algorithms: Beam Search for straightforward problems and Monte Carlo Tree Search (MCTS) with experimental alpha variations that incorporate policy simulation layers and adaptive exploration techniques. The server enables Claude to explore multiple reasoning paths simultaneously, evaluate their quality, and analyze the complete reasoning process while allowing dynamic control over search parameters like beam width and simulation count. It solves the problem of enhancing Claude's complex problem-solving abilities by giving the model access to sophisticated algorithmic reasoning strategies that combine both search and policy-based approaches.