Claude Desktop向けの推論実装で、ビームサーチとモンテカルロツリーサーチ(MCTS)の両方を使えます。正直なところ、これはClaudeを複雑な問題解決にさらに優れさせる方法として始まりました…結果的に、確実にそれが可能になりました。

現行バージョン:

v2.0.0

最新情報:

2つの実験的推論アルゴリズムを追加しました:

• mcts-002-alpha

• A検索手法と初期のアルファ*実装のポリシーシミュレーションレイヤーを使用

• Adaptive Exploration SimulatorおよびOutcome Based Reasoning Simulatorの初期アルファ実装も含まれています

注 これらのアルファシミュレーターの実装はまだ完全ではなく、変更される可能性があります

• mcts-002alt-alpha

• 双方向検索法と初期のアルファ実装のポリシーシミュレーションレイヤーを使用。

• Adaptive Exploration SimulatorおよびOutcome Based Reasoning Simulatorの初期アルファ実装も含まれています

注 これらのアルファシミュレーターの実装はまだ完全ではなく、変更される可能性があります

mcts-001-alphaとmcts-001alt-alphaはどうなったのですか?

簡単に言えば、役に立たず、基本のmcts方式とほぼ同じでした。

MCP Reasoner

A reasoning implementation for Claude Desktop that lets you use both Beam Search and Monte Carlo Tree Search (MCTS). tbh this started as a way to see if we could make Claude even better at complex problem-solving… turns out we definitely can.

Current Version:

v2.0.0

What’s New:

Added 2 Experimental Reasoning Algorithms:

- `mcts-002-alpha`

    - Uses the A* Search Method along with an early *alpha* implementation of a Policy Simulation Layer

    - Also includes an early *alpha* implementation of Adaptive Exploration Simulator & Outcome Based Reasoning Simulator

*NOTE* the implementation of these alpha simulators is not complete and is subject to change

- `mcts-002alt-alpha`

    - Uses the Bidirectional Search Method along with an early *alpha* implementation of a Policy Simulation Layer

    - Also includes an early *alpha* implementation of Adaptive Exploration Simulator & Outcome Based Reasoning Simulator

*NOTE* the implementation of these alpha simulators is not complete and is subject to change

What happened to mcts-001-alpha and mcts-001alt-alpha?

Quite simply: It was useless and near similar to the base mcts method. After initial testing the results yielded in basic thought processes was near similar showing that simply adding policy simulation may not have an effect.

So why add Polciy Simulation Layer now?

Well i think its important to incorporate Policy AND Search in tandem as that is how most of the algorithms implement them.

Previous Versions:

v1.1.0

Added model control over search parameters:

beamWidth - lets Claude adjust how many paths to track (1-10)

numSimulations - fine-tune MCTS simulation count (1-150)

Features

• Two search strategies that you can switch between:
  • Beam search (good for straightforward stuff)
  • MCTS (when stuff gets complex) with alpha variations (see above)
• Tracks how good different reasoning paths are
• Maps out all the different ways Claude thinks through problems
• Analyzes how the reasoning process went
• Follows the MCP protocol (obviously)

Installation

git clone https://github.com/frgmt0/mcp-reasoner.git 

OR clone the original:

git clone https://github.com/Jacck/mcp-reasoner.git

cd mcp-reasoner
npm install
npm run build

Configuration

Add to Claude Desktop config:

{
  "mcpServers": {
    "mcp-reasoner": {
      "command": "node",
      "args": ["path/to/mcp-reasoner/dist/index.js"],
    }
  }
}

Testing

[More Testing Coming Soon]

Benchmarks

[Benchmarking will be added soon]

Key Benchmarks to test against:

• MATH500

• GPQA-Diamond

• GMSK8

• Maybe Polyglot &/or SWE-Bench

License

This project is licensed under the MIT License - see the LICENSE file for details.