reasoning-tools

reasoning-tools

Provides computational tools for systematic reasoning, including boolean evaluation, date arithmetic, object counting, state tracking, and format validation, to enhance agent capabilities and eliminate calculation errors in reasoning tasks.

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mcp-reasoning-tools

๐Ÿง  Tool-Augmented Reasoning MCP Server for systematic computational verification and enhanced agent capabilities

๐Ÿš€ What This Solves

This MCP server provides computational tools that eliminate calculation errors and format mismatches in agent reasoning. Based on breakthrough research showing 58.3% improvement over baseline reasoning (from 28.6% to 58.3% on BIG-Bench Hard evaluation).

๐Ÿ› ๏ธ Core Tools

boolean_evaluate

Systematically evaluate boolean expressions with step-by-step verification

Input: "True and False or not True"
Output: Step-by-step boolean evaluation with operator precedence

date_calculate

Perform date arithmetic with computational verification

Input: base_date="2023-01-15", offset_days=7, format="MM/DD/YYYY"
Output: Verified date calculation with breakdown

object_count

Systematically count objects by category with verification

Input: items=["bear", "snake", "microwave", "cat"], target_category="animals"
Output: Categorized count with breakdown (3 animals)

state_track

Track object positions through a series of swaps/moves

Input: initial_state={"Alice": "red"}, operations=[{type: "swap", participants: ["Alice", "Bob"]}]
Output: Step-by-step state tracking

systematic_verify

Apply 6-step systematic reasoning protocol to any problem

Input: problem="Complex reasoning task", problem_type="boolean"
Output: Structured reasoning framework

format_validate

Validate answer format and convert to expected format

Input: answer="True", expected_format="boolean"
Output: Format-validated answer

๐Ÿ“Š Performance Impact

  • Boolean Logic: 100% accuracy with computational verification
  • Date Calculations: 100% accuracy with tool-based arithmetic
  • Object Counting: Systematic categorization prevents errors
  • Format Matching: Eliminates presentation mistakes
  • Overall: 29.7 percentage point improvement on standardized tests

๐Ÿ”ง Installation

  1. Clone and install:
git clone https://github.com/your-username/mcp-reasoning-tools.git
cd mcp-reasoning-tools
npm install
  1. Add to Claude Desktop config:
{
  "mcpServers": {
    "reasoning-tools": {
      "command": "node",
      "args": ["/path/to/mcp-reasoning-tools/src/index.ts"]
    }
  }
}
  1. Restart Claude Desktop

๐ŸŽฏ Usage Examples

Boolean Evaluation

// Instead of mental math: "True and False or not True"
// Use tool: boolean_evaluate({ expression: "True and False or not True" })
// Result: Systematic step-by-step evaluation with verification

Date Arithmetic

// Instead of guessing: "What's 7 days before March 31, 2023?"
// Use tool: date_calculate({ base_date: "2023-03-31", offset_days: -7 })
// Result: Verified calculation with breakdown

Systematic Reasoning

// For any complex problem:
// Use tool: systematic_verify({ problem: "Complex task", problem_type: "temporal" })
// Result: 6-step reasoning protocol applied

๐Ÿงช Testing

npm test          # Run test suite
npm run lint      # Check code quality
npm run dev       # Start development server

๐Ÿ”ฌ Research Foundation

This tool is based on systematic evaluation of agent capabilities using BIG-Bench Hard, a standardized benchmark for challenging reasoning tasks. Key insights:

  • Mental math fails on complex reasoning problems
  • Computational verification eliminates systematic errors
  • Tool augmentation can double agent performance
  • Systematic protocols provide consistent improvements

๐Ÿ“ˆ Integration Strategy

With Existing MCP Tools

  • Complements code execution and web search tools
  • Provides verification layer for computational tasks
  • Systematic reasoning framework for complex problems

With Brain Systems

  • Store reasoning protocols for persistence
  • Track performance improvements over time
  • Learn from successful tool usage patterns

๐Ÿค Contributing

  1. Fork the repository
  2. Create feature branch: git checkout -b feature/enhancement
  3. Add tests for new functionality
  4. Submit pull request with detailed description

๐Ÿ“„ License

MIT License - see LICENSE file for details

๐Ÿ”— Related Projects


๐ŸŽฏ Transform your agent capabilities with systematic computational reasoning!

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