Reasoner
Systematic reasoning with Beam Search and Monte Carlo Tree Search.
Installation
Installing for Claude Desktop
Manual Configuration Required
This MCP server requires manual configuration. Run the command below to open your configuration file:
npx mcpbar@latest edit -c claude
This will open your configuration file where you can add the Reasoner MCP server manually.
MCP Reasoner
A systematic reasoning MCP server implementation for Claude Desktop featuring both Beam Search and Monte Carlo Tree Search (MCTS) capabilities.
Features
- Dual search strategies:
- Beam search with configurable width
- MCTS for complex decision spaces
- Thought scoring and evaluation
- Tree-based reasoning paths
- Statistical analysis of reasoning process
- MCP protocol compliance
Installation
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"],
}
}
}
Search Strategies
Beam Search
- Maintains fixed-width set of most promising paths
- Optimal for step-by-step reasoning
- Best for: Mathematical problems, logical puzzles
Monte Carlo Tree Search
- Simulation-based exploration of decision space
- Balances exploration and exploitation
- Best for: Complex problems with uncertain outcomes
Note: Monte Carlo Tree Search allowed Claude to perform really well on the Arc AGI benchmark (scored 6/10 on the public test), whereas beam search yielded a (3/10) on the same puzzles. For super complex tasks, you'd want to direct Claude to utilize the MCTS strategy over the beam search.
Algorithm Details
- Search Strategy Selection
- Beam Search: Evaluates and ranks multiple solution paths
- MCTS: Uses UCT for node selection and random rollouts
- Thought Scoring Based On:
- Detail level
- Mathematical expressions
- Logical connectors
- Parent-child relationship strength
- Process Management
- Tree-based state tracking
- Statistical analysis of reasoning
- Progress monitoring
Use Cases
- Mathematical problems
- Logical puzzles
- Step-by-step analysis
- Complex problem decomposition
- Decision tree exploration
- Strategy optimization
Future Implementations
- Implement New Algorithms
- Iterative Deepening Depth-First Search (IDDFS)
- Alpha-Beta Pruning
License
This project is licensed under the MIT License - see the LICENSE file for details.
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