About Reasoner
Reasoner is an MCP server published by parmarjh in the Other category.
The repository has 12 stars and 6 forks, with the last commit a year ago. Six months or more without a commit doesn't mean the server is broken, but check the open issues before depending on it in production.
Install
git clone https://github.com/parmarjh/mcp-reasonerThis server has no ConduID identity, so agent calls to it are not receipted. Pin the version you install and review the source before granting it credentials.
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README
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.
README fetched from the repository 2 days ago. The original is authoritative.