ThoughtMCP

AI that thinks more like humans do.

ThoughtMCP gives AI systems human-like thinking capabilities. Instead of just processing text, it can think systematically, remember experiences, and check its own reasoning quality.

🚀 Production Ready: 789 tests, 79.63% coverage, stable API, ready for real-world use.

What Makes It Different?

Most AI systems process text once and respond. ThoughtMCP implements multiple thinking systems inspired by cognitive science:

🧠 Human-Like Thinking

• Fast intuitive responses for familiar problems
• Careful deliberation for complex decisions
• Creative exploration for innovation challenges
• Analytical reasoning for technical problems

💾 Learning Memory

• Remembers experiences and learns from them
• Builds knowledge that improves over time
• Recalls relevant information when making decisions
• Consolidates patterns from specific cases to general principles

🔍 Self-Monitoring

• Checks its own reasoning for quality and biases
• Provides confidence levels for transparency
• Suggests improvements to its own thinking
• Adapts approach based on problem complexity

⚡ Production Ready

• 789 comprehensive tests with 79.63% coverage
• Multiple thinking modes for different scenarios
• Configurable behavior for your specific needs
• Robust error handling with graceful degradation

Quick Start

1. Install and Setup

# Clone the repository
git clone https://github.com/keyurgolani/ThoughtMcp.git
cd ThoughtMcp

# Install dependencies
npm install

# Build and start
npm run build
npm run dev

2. Try Your First Example

Ask ThoughtMCP to help with a decision:

{
  "tool": "think",
  "arguments": {
    "input": "I'm trying to decide between two job offers. One pays more but has longer hours, the other has better work-life balance but lower pay. How should I approach this decision?",
    "mode": "deliberative"
  }
}

What happens:

• Analyzes your question systematically
• Considers multiple factors and perspectives
• Provides structured reasoning with confidence levels
• Suggests ways to improve the decision-making process

3. Build Knowledge Over Time

Store important insights:

{
  "tool": "remember",
  "arguments": {
    "content": "When choosing between job offers, work-life balance often matters more than salary for long-term satisfaction",
    "type": "semantic",
    "importance": 0.8
  }
}

Recall relevant knowledge:

{
  "tool": "recall",
  "arguments": {
    "cue": "job decision work-life balance"
  }
}

The Four Thinking Tools

🧠 Think - Systematic Reasoning

Process complex questions using human-like reasoning:

• Intuitive mode: Fast, gut-reaction responses
• Deliberative mode: Slow, careful analysis
• Creative mode: Innovative problem-solving
• Analytical mode: Logical, data-driven reasoning

💾 Remember - Build Knowledge

Store experiences and insights for future use:

• Episodic memory: Specific experiences and events
• Semantic memory: General knowledge and principles
• Importance weighting: Prioritize what matters most
• Emotional tagging: Remember how things felt

🔍 Recall - Find Relevant Information

Retrieve past experiences and knowledge when needed:

• Similarity matching: Find related experiences
• Context-aware: Consider current situation
• Confidence scoring: Know how relevant results are
• Cross-memory search: Search both experience and knowledge

🔬 Analyze Reasoning - Quality Control

Check thinking quality and identify potential problems:

• Bias detection: Spot common reasoning errors
• Logic validation: Ensure arguments are sound
• Confidence assessment: Evaluate certainty levels
• Improvement suggestions: Get better at reasoning

Real-World Examples

See ThoughtMCP in action with practical scenarios:

• Customer Support Agent - Solving technical problems systematically
• Personal Finance Advisor - Making complex financial decisions
• Recipe Recommendation - Personalized suggestions with constraints
• Study Buddy - Helping students learn effectively
• Travel Planning - Complex multi-constraint planning

Each example shows:

• The real-world problem
• Step-by-step tool usage
• How cognitive thinking improves outcomes
• Lessons you can apply to your own use cases

Documentation

🚀 New to ThoughtMCP?

• Getting Started - 5-minute tutorial and basic concepts
• Installation Guide - Detailed setup instructions
• Basic Concepts - How human-like thinking works
• Examples - From simple to complex real-world scenarios

👩‍💻 For Developers

• API Reference - Complete tool documentation and schemas
• Integration Guide - Add to your applications
• Configuration - Customize behavior and performance
• Troubleshooting - Common issues and solutions

🧠 Understanding the Architecture

• Architecture Overview - How the cognitive system works
• Cognitive Components - Individual system details
• Research Background - Academic foundations and algorithms
• Performance Benchmarks - Speed and accuracy metrics

🛠️ Contributing

• Development Setup - Set up for development
• Contributing Guide - How to contribute effectively
• Architecture for Developers - Codebase structure
• Testing Guide - Writing and running tests

Why Choose ThoughtMCP?

For AI Applications

• Better Decision Making: Considers multiple perspectives and checks reasoning quality
• Continuous Learning: Gets smarter over time by remembering experiences
• Transparency: Shows reasoning process and confidence levels
• Adaptability: Different thinking modes for different types of problems

For Developers

• Production Ready: 789 tests, comprehensive error handling, performance monitoring
• Easy Integration: Standard MCP protocol, clear API, extensive documentation
• Configurable: Tune behavior for your specific use case and performance needs
• Open Source: MIT license, active community, extensible architecture

For Researchers

• Scientifically Grounded: Based on established cognitive science research
• Comprehensive Implementation: Full dual-process theory, memory systems, metacognition
• Benchmarked Performance: Validated against cognitive psychology principles
• Extensible Design: Add new cognitive components and reasoning strategies

Community and Support

• 📖 Documentation: Comprehensive guides from beginner to advanced
• 💬 GitHub Discussions: Ask questions and share ideas
• 🐛 Issues: Report bugs and request features
• 🤝 Contributing: Join our community of contributors
• 📧 Contact: Reach out to @keyurgolani

Project Status

• ✅ Stable API: All four cognitive tools fully implemented
• ✅ Production Ready: 789 tests with 79.63% coverage
• ✅ Well Documented: Comprehensive documentation for all user levels
• ✅ Active Development: Regular updates and community contributions
• ✅ Open Source: MIT license, community-driven development

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Ready to give your AI human-like thinking capabilities?

👉 Get Started in 5 Minutes | 📚 View Documentation | 🤝 Join Community