MCTS MCP Server

# Using MCTS for Complex Problem Solving ## When to Use MCTS Use the MCTS server when you need: - Deep analysis of complex questions - Exploration of multiple solution approaches - Systematic reasoning through difficult problems - Optimal solutions requiring iterative refinement ## Basic Workflow ### 1. Initialize MCTS ``` Tool: initialize_mcts Required: question, chat_id Optional: provider (default: "gemini"), model Example: - question: "How can we reduce carbon emissions in urban transportation?" - chat_id: "urban_transport_analysis_001" - provider: "gemini" (recommended for performance) ``` ### 2. Run Search Iterations ``` Tool: run_mcts_search Parameters: - iterations: 3-5 for most problems (more for complex issues) - simulations_per_iteration: 5-10 Start with: iterations=3, simulations_per_iteration=5 Increase for more thorough analysis ``` ### 3. Get Final Analysis ``` Tool: get_synthesis No parameters needed - uses current MCTS state Returns comprehensive analysis with best solutions ``` ## Pro Tips 1. **Start Simple**: Begin with 3 iterations and 5 simulations 2. **Monitor Status**: Use get_status to check progress 3. **Provider Choice**: Gemini is default and recommended for balanced performance 4. **Unique Chat IDs**: Use descriptive IDs for state persistence 5. **Iterative Refinement**: Run additional searches if needed ## Example Complete Session 1. `initialize_mcts("How to improve team productivity?", "productivity_analysis_001")` 2. `run_mcts_search(iterations=3, simulations_per_iteration=5)` 3. `get_synthesis()` - Get the final recommendations ## Error Handling - Check get_status if tools return errors - Ensure provider API keys are set if using non-Gemini providers - Reinitialize if needed with a new chat_id