MCTS MCP Server

Bayesian MCTS Model Context Protocol Server allowing Claude to control Ollama local models for Advanced MCTS and analysis.

Local serverstdioPython

What is the MCTS MCP Server?

Bayesian MCTS Model Context Protocol Server allowing Claude to control Ollama local models for Advanced MCTS and analysis.

What you get

A Model Context Protocol (MCP) server that exposes an Advanced Bayesian Monte Carlo Tree Search (MCTS) engine for AI-assisted analysis and reasoning.

This MCP server enables Claude to use Monte Carlo Tree Search (MCTS) algorithms for deep, explorative analysis of topics, questions, or text inputs. The MCTS algorithm uses a Bayesian approach to systematically explore different angles and interpretations, producing insightful analyses that evolve through multiple iterations.

  • Bayesian MCTS — Uses a probabilistic approach to balance exploration vs. exploitation during analysis
  • Multi-iteration Analysis — Supports multiple iterations of thinking with multiple simulations per iteration
  • State Persistence — Remembers key results, unfit approaches, and priors between turns in the same chat
  • Approach Taxonomy — Classifies generated thoughts into different philosophical approaches and families
  • Thompson Sampling — Can use Thompson sampling or UCT for node selection
  • Surprise Detection — Identifies surprising or novel directions of analysis

Configuration and credentials

  • Python 3.10+ (required) - Internet connection (for downloading dependencies)

More MCP options

Compare MCP servers by category, or browse hosted MCP servers if you prefer an endpoint over a local process.

Maintainer setup documentation.

Recorded tools

Check the linked publisher documentation and your connected client's tool list. Names and availability can vary with the server version and account permissions.

ToolWhat it does
initialize_mctsStart a new MCTS analysis with a specific question. Can optionally specify provider_name and model_name to override defaults for this run.
run_mctsRun the MCTS algorithm for a set number of iterations/simulations.
generate_synthesisGenerate a final summary of the MCTS results.
get_configView current MCTS configuration parameters, including active LLM provider and model.
update_configUpdate MCTS configuration parameters (excluding provider/model, use set_active_llm for that).
get_mcts_statusCheck the current status of the MCTS system.

How to install the MCTS MCP Server

{
  "mcpServers": {
    "mcts-mcp-server": {
      "command": "uv",
      "args": [
        "--directory",
        "/path/to/mcts-mcp-server/src",
        "run",
        "mcts-mcp-server"
      ],
      "env": {
        "UV_PROJECT_ENVIRONMENT": "/path/to/mcts-mcp-server"
      }
    }
  }
}

Configuration as documented by the project. Restart the client after saving.

Configuration

  • Python 3.10+ (required) - Internet connection (for downloading dependencies)
VariableDescriptionRequired
UV_PROJECT_ENVIRONMENTConfiguration value read at startup.Optional
OPENAI_API_KEYCredential the server authenticates with.Yes
ANTHROPIC_API_KEYCredential the server authenticates with.Yes
GEMINI_API_KEYCredential the server authenticates with.Yes

Example prompts to try

  • “Use MCTS to initialize mcts.”
  • “Use MCTS to run mcts.”
  • “Use MCTS to generate synthesis.”

Frequently asked questions

Python 3.10+ and the UV package manager. Dependencies are installed automatically by the setup script.