An intelligent AI-powered development framework that combines Single Source of Truth (SSOT) project state management, context-aware Rule Engine, and Model Context Protocol (MCP) integration to create a self-organizing, learning development environment.

The SSOT-RULE-ENGINE-TEMPLATE transforms your development workflow by providing:

• 🧠 Persistent AI Memory: Knowledge Graph-based project understanding that grows over time
• 📋 Centralized State Management: Single Source of Truth for all project information
• 🎛️ Context-Aware AI Behavior: Dynamic rule system that adapts to your project needs
• 🔧 Advanced AI Capabilities: Specialized MCP servers for enhanced reasoning and analysis
• 📊 Intelligent Project Tracking: Automated progress monitoring and documentation
• 📈 Advanced Analytics: Real-time project health monitoring and performance insights

• Centralized project state in .cursor/CORE/SSOT/
• Automated project history and progress tracking
• Intelligent workflow orchestration via trigger system
• Project portability with snapshot/restore capabilities

• Context-aware AI behavior through .mdc files
• Global and file-specific rule application
• Automated rule generation and staging
• Consistent development standards enforcement

• Knowledge Graph Server: Persistent entity-relationship project modeling
• Sequential Thinking Server: Multi-step reasoning and problem solving
• Filesystem Server: Enhanced file system operations and analysis

• Automated project initialization and analysis
• Smart codebase understanding and documentation
• GitHub preparation and repository optimization
• Comprehensive testing and quality assurance

• Real-time project health scoring (0-100 scale)
• Interactive web dashboard with live visualizations
• Multi-dimensional analysis (SSOT, MCP, Rules, Project structure)
• Intelligent recommendations engine with priority suggestions
• Development velocity tracking and trend analysis
• System performance monitoring and optimization insights

• Node.js (v16 or higher)
• npm or yarn
• Cursor IDE with AI capabilities

1. Describe Your Project in Cursor chat, then initialize:

!!-INIT-.ENGINE-!!

2. Install MCP Servers:

!!-INSTALL-MCP-!!

3. Build Knowledge Graph:

!!-BUILD-KG-!!

1. Analyze Existing Codebase:

!!-ADD-.ENGINE-!!

2. Install MCP Servers:

!!-INSTALL-MCP-!!

3. Build Knowledge Graph:

!!-BUILD-KG-!!

.cursor/
├── CORE/
│   ├── SSOT/                   # Single Source of Truth files
│   │   ├── .ENGINE             # Central workflow orchestrator
│   │   ├── .INIT               # Project initialization
│   │   ├── .CONTEXT            # High-level overview
│   │   ├── .FACTS              # Technical decisions
│   │   ├── .MEMORY             # Component summaries
│   │   ├── .HISTORY            # Activity log
│   │   ├── .CONTINUE           # Next steps
│   │   └── .PROGRESS           # Task tracking
│   ├── MCP/                    # MCP server implementations
│   │   ├── knowledge-graph/    # Graph database server
│   │   ├── sequentialthinking/ # Reasoning server
│   │   └── filesystem/         # File operations server
│   ├── RULE-ENGINE/            # Generated rules staging
│   ├── MEMORY/                 # Persistent memory storage
│   ├── PROMPTS/                # System prompts
│   ├── ANALYTICS/              # Analytics engine and dashboard
│   │   ├── analytics_engine.py # Project health analysis
│   │   ├── dashboard.py        # Web dashboard with visual rule engine
│   │   ├── startup.py          # Dashboard auto-launch script
│   │   ├── USER-RULES-TEMPLATE.md # Template for easy USER-RULES setup
│   │   └── dashboard/          # Generated dashboard files
│   └── DOCS/                   # Documentation
├── rules/                      # Active rule files
├── mcp.json                    # MCP configuration
└── launch-dashboard.py         # Quick dashboard launcher

The template includes three pre-configured MCP servers:

1. Knowledge Graph Server - Persistent project memory
2. Sequential Thinking Server - Advanced reasoning capabilities
3. Filesystem Server - Enhanced file operations

Configuration is handled automatically through the trigger system.

Rules are defined in .mdc files with frontmatter:

---
description: Rule description
globs: **/*.js, **/*.ts
alwaysApply: false
---

# Rule Content
Your guidelines and instructions...

# Describe your Flask/Django/Express app, then:
!!-INIT-.ENGINE-!!
!!-INSTALL-MCP-!!
!!-BUILD-KG-!!

# For any existing project:
!!-ADD-.ENGINE-!!
!!-INSTALL-MCP-!!
!!-BUILD-KG-!!

# Create portable state for sharing:
!!-CREATE-PORTABLE-!!

# Team member loads state:
!!-LOAD-PORTABLE-!!

# Quick health assessment:
!!-HEALTH-CHECK-!!

# Comprehensive analysis:
!!-ANALYZE-PROJECT-!!

# Launch interactive dashboard with visual rule engine:
!!-LAUNCH-DASHBOARD-!!

# Open dashboard in browser (if already running):
!!-VIEW-DASHBOARD-!!

# Manual launch options:
python launch-dashboard.py                    # Quick launcher from project root
python .cursor/CORE/ANALYTICS/startup.py     # Direct startup script

Dashboard Features:

• 📊 Analytics Tab: Real-time health scoring and project metrics
• ⚙️ Rule Engine Tab: Visual rule management interface
• 📋 USER-RULES Tab: Template copying for easy setup
• 🗂️ SSOT Tab: System state monitoring and file inspection

• Persistent Context: AI remembers your project across sessions
• Intelligent Assistance: Context-aware suggestions and code generation
• Automated Documentation: Self-updating project documentation
• Quality Assurance: Consistent coding standards and best practices

• Knowledge Sharing: Easy context transfer between team members
• Onboarding: New developers quickly understand project structure
• Standards Enforcement: Consistent development patterns across team
• Progress Tracking: Comprehensive project history and progress monitoring

• Reduced Technical Debt: Continuous quality monitoring and improvement
• Better Architecture: AI-guided architectural decisions and refactoring
• Enhanced Testing: Intelligent test generation and coverage analysis
• Documentation: Always up-to-date project documentation
• Health Monitoring: Real-time project health scoring and trend analysis
• Performance Insights: Actionable recommendations for optimization
• Visual Analytics: Interactive dashboards for comprehensive project oversight

The system builds a comprehensive knowledge graph of your project:

• Entities: Files, functions, classes, modules, configurations
• Relationships: Dependencies, calls, implementations, contains
• Observations: Comments, metrics, patterns, decisions

Real-time project monitoring and insights:

• Health Scoring: Comprehensive 0-100 scale project health assessment
• System Analysis: SSOT (30%), MCP (30%), Rules (25%), General (15%) breakdown
• Interactive Visualizations: Charts, graphs, and real-time data displays
• Intelligent Recommendations: Priority-based suggestions for improvement
• Development Velocity: Activity tracking and productivity metrics
• Web Interface: Responsive dashboard with auto-refresh capabilities

# Launch analytics dashboard
cd .cursor/CORE/ANALYTICS
python dashboard.py  # Opens browser automatically

# Generate static reports
python analytics_engine.py  # Creates JSON and Markdown reports

Create and restore complete project snapshots:

• Full SSOT state preservation
• Knowledge Graph backup/restore
• Rule configuration transfer
• Cross-environment compatibility

Automated repository preparation:

• Intelligent .gitignore generation
• Documentation synchronization
• Code quality checks
• Release preparation

# Check MCP server status
npm run build  # In each MCP server directory

# Restart servers
# Restart Cursor IDE

# Update SSOT after major changes
!!-UPDATE-SSOT-!!

# Rebuild Knowledge Graph if needed
!!-BUILD-KG-!!

• Check .mdc file syntax in rules/ directory
• Verify glob patterns match intended files
• Review rule staging in CORE/RULE-ENGINE/

# Generate dashboard without starting server
cd .cursor/CORE/ANALYTICS
python dashboard.py --generate-only

# Start dashboard on custom port
python dashboard.py --port 8080 --no-browser

# Run analytics analysis only
python analytics_engine.py

1. Fork the repository
2. Create a feature branch (git checkout -b feature/amazing-feature)
3. Use the SSOT system for development tracking
4. Update documentation using !!-UPDATE-DOCS-!!
5. Prepare for submission with !!-PREPARE-GITHUB-!!
6. Submit a Pull Request

This project is licensed under the MIT License - see the LICENSE file for details.

• Model Context Protocol (MCP) - For the foundational server architecture
• Cursor AI - For the intelligent IDE integration
• Anthropic - For advanced AI reasoning capabilities

• Documentation: See DOCS/Comprehensive Documentation.md
• Issues: Report issues through GitHub Issues
• Discussions: Use GitHub Discussions for questions and ideas

• Visual Knowledge Graph explorer
• Advanced analytics and metrics
• Integration with popular development tools
• Multi-language support expansion
• Cloud-based Knowledge Graph synchronization
• Machine learning-based project predictions
• Team collaboration analytics
• CI/CD pipeline integration

Start building smarter with AI-powered development today! 🚀