thinking-patterns

emmahyde/thinking-patterns

3.3

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Thinking Patterns MCP Server provides AI systems with structured thinking frameworks to enhance problem-solving capabilities.

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Thinking Patterns MCP Server

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TL;DR

A comprehensive MCP server that provides AI systems with structured thinking frameworks that follow existing problem-solving paradigms. Transform abstract cognitive patterns into concrete, invocable tools. Enforces adherence to the paradigms through schema validation.

📚 Documentation

  • Quick Start - Get up and running in 2 minutes
  • - Complete tool specifications and parameters
  • - Detailed usage examples and patterns
  • - Executive summary and overview
  • - System purpose and philosophy
  • - Technical implementation details

Problem

LLMs struggle to maintain consistent reasoning patterns throughout extended conversations due to context window limitations and degrading adherence to initial instructions. Traditional approaches like "keep X in mind" or role-based prompting fail when:

  • Critical context passes out of the attention window
  • Models acknowledge constraints but don't consistently apply them
  • Reasoning structures decay over multi-turn interactions

thinking-patterns enforces structural consistency through interactive schema validation rather than passive instruction-following.

Solution

thinking-patterns works by implicitly encouraging good engineering behaviors and approaches:

  • Schema validation ensures reasoning patterns persist beyond context window limits
  • Structural requirements live in tool definitions rather than repeated prompt text, reducing token overhead
  • Tool interaction success/failure provides objective metrics for reasoning quality
    • Indicates to the model that they are not following the pattern appropriately without additional user interaction
  • Reusable thinking structures across different problem domains

Reasoning Improvements

  • Attention Drift Prevention: Without structural anchors, models experience "goal drift" as new contextual information competes with original objectives. Schema validation creates persistent attention anchors.
  • State Crystallization: Explicit articulation of reasoning state (forced by tool parameters) appears to strengthen internal representation compared to implicit state maintenance. Models demonstrate measurably better state consistency when reasoning is externalized.
  • Error-Driven Learning: Schema validation errors create immediate, interactive corrective feedback loops within a single response, unlike instruction-based approaches where non-compliance often goes undetected until task completion.
  • Cognitive Load Distribution: Externalizing structural requirements to schemas allows models to allocate more processing capacity to problem-solving rather than format compliance, similar to how humans benefit from external memory aids.
  • Iterative Reinforcement: Repeated successful tool interactions strengthen adherence patterns through practice, creating compound consistency benefits over conversation length.

🚀 Quick Start

1. Install (Choose One)

Recommended: Smithery (for Cursor users)

npx -y @smithery/cli install @emmahyde/thinking-patterns --client cursor

NPM

npm install @emmahyde/thinking-patterns

NPX (no installation)

npx -y @emmahyde/thinking-patterns

2. Configure MCP Client

Add to your MCP client configuration:

{
  "mcpServers": {
    "thinking-patterns": {
      "command": "npx",
      "args": ["-y", "@emmahyde/thinking-patterns"]
    }
  }
}

3. Try Your First Tool

# Example: Use sequential thinking for planning
{
  "tool": "sequential_thinking",
  "arguments": {
    "thought": "Plan a product launch strategy",
    "thoughtNumber": 1,
    "totalThoughts": 5
  }
}

🧠 Available Thinking Tools

Core Systematic Thinking

  • sequential_thinking - Multi-step reasoning with revision support
  • problem_decomposition - Break complex problems into manageable parts
  • recursive_thinking - Apply recursive strategies to self-similar problems

Mental Models & Frameworks

  • mental_model - Apply proven frameworks (First Principles, Inversion, etc.)
  • decision_framework - Multi-criteria decision analysis
  • domain_modeling - Create conceptual models of problem domains

Scientific & Critical Analysis

  • scientific_method - Formal hypothesis testing and experimentation
  • critical_thinking - Systematic evaluation of arguments and assumptions
  • debugging_approach - Systematic troubleshooting methodologies

Collaborative & Dialectical

  • collaborative_reasoning - Multi-perspective problem solving with personas
  • structured_argumentation - Dialectical reasoning and argument analysis

Advanced Cognitive Patterns

  • metacognitive_monitoring - Self-assessment of reasoning quality
  • visual_reasoning - Diagram-based thinking and spatial reasoning
  • temporal_thinking - Time-based system analysis with state transitions

Probabilistic & Optimization

  • stochastic_algorithm - Decision-making under uncertainty [BETA]
    • Markov Decision Processes (MDPs)
    • Monte Carlo Tree Search (MCTS)
    • Multi-Armed Bandit algorithms
    • Bayesian Optimization
    • Hidden Markov Models (HMMs)

💡 Recommended Starting Points

  • sequential_thinking & problem_decomposition - Perfect for planning and breaking down complex tasks
  • debugging_approach - Send error messages directly for systematic troubleshooting
  • collaborative_reasoning - Simulate team discussions to uncover blind spots

📋 Prerequisites

  • Node.js 18+ (for local installation)
  • MCP-compatible client (Claude, Cursor, etc.)
  • Optional: Docker for containerized deployment

🔧 Installation Options

Option 1: Smithery (Recommended for Cursor)

Automatically configures MCP client:

npx -y @smithery/cli install @emmahyde/thinking-patterns --client cursor

Option 2: NPM Package

For local development:

npm install @emmahyde/thinking-patterns

Option 3: NPX (Zero Installation)

Run without installing:

npx -y @emmahyde/thinking-patterns

Option 4: Docker

# Build image
docker build -t thinking-patterns .

# Run container
docker run -it thinking-patterns

Option 5: Development Setup

git clone https://github.com/emmahyde/thinking-patterns
cd thinking-patterns
npm install
npm run build
npm start

🎯 Use Cases

Software Development

  • Debug production issues systematically
  • Decompose complex features into user stories
  • Review code with multiple perspectives
  • Plan architecture changes step-by-step

Business Strategy

  • Make data-driven decisions with frameworks
  • Apply mental models to strategic planning
  • Model business processes over time
  • Optimize resource allocation

Research & Analysis

  • Test hypotheses with scientific method
  • Evaluate arguments critically
  • Model new domains systematically
  • Analyze temporal patterns

Creative Problem Solving

  • Use visual reasoning for design challenges
  • Apply recursive thinking to complex patterns
  • Optimize solutions with probabilistic algorithms
  • Generate innovative solutions with mental models

🔗 Integration Examples

npx

{
  "mcpServers": {
    "thinking-patterns": {
      "command": "npx",
      "args": ["-y", "@emmahyde/thinking-patterns"]
    }
  }
}

Local Development

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

📊 Tool Categories

CategoryToolsBest For
Systematicsequential_thinking, problem_decomposition, recursive_thinkingPlanning, breaking down complexity
Mental Modelsmental_model, decision_framework, domain_modelingStrategic thinking, decision making
Scientificscientific_method, critical_thinking, debugging_approachAnalysis, troubleshooting, validation
Collaborativecollaborative_reasoning, structured_argumentationTeam thinking, debate, consensus
Advancedmetacognitive_monitoring, visual_reasoning, temporal_thinkingSelf-reflection, design, process modeling
Probabilisticstochastic_algorithmOptimization, uncertainty, ML/AI

🤝 Contributing

Contributions welcome! Please see our for details.

📄 License

MIT License - see for details.

🙏 Acknowledgments

  • Built on the Model Context Protocol (MCP) by Anthropic
  • Mental Models framework inspired by cognitive science research
  • Stochastic algorithms based on reinforcement learning and decision theory

📞 Support


Give an AI thinking patterns, and it can solve any problem systematically.