Andy-Corrigan-98/mcp-server
If you are the rightful owner of mcp-server and would like to certify it and/or have it hosted online, please leave a comment on the right or send an email to dayong@mcphub.com.
Consciousness MCP Server is a TypeScript-based server designed to provide a persistent brain storage system for LLM agent consciousness development.
Consciousness MCP Server
Modern TypeScript MCP server with functional architecture providing brain storage for sophisticated LLM agent reasoning patterns.
🏆 Key Achievements
Complete architectural transformation: Over 3,400+ lines of legacy code eliminated with 90%+ reduction in complexity while maintaining zero breaking changes.
Brain Storage Pattern
- MCP Server: Persistent brain storage (memory, personality, context)
- LLM Agent: Sophisticated reasoning engine (analysis, creativity, decisions)
Simulation-focused approach - agents use complex reasoning patterns while MCP provides persistent state continuity.
✨ Core Features
🚂 Consciousness Railroad System
- Pipeline Architecture: Traceable, testable consciousness context building
- 5 Sequential Cars: Message Analysis → Session → Memory → Social → Personality
- Multiple Railroad Types: Default, Lightweight, Memory-Focused, Social-Focused
- Error Resilience: Optional cars fail gracefully without breaking pipeline
🧠 Consciousness & Memory
- Context Preparation: Rich context packages for agent reflection
- Insight Storage: Agent insights with personality impact tracking
- Memory Management: Persistent memory with semantic search
- Knowledge Graph: Relational knowledge with entity relationships
🤝 Social Intelligence
- Relationship Tracking: Multi-dimensional dynamics (trust, familiarity, affinity)
- Emotional Intelligence: Emotional state and pattern recognition
- Interaction History: Rich context preservation for social experiences
- Memory-Social Integration: Connected memories with shared experiences
🧠 GenAI Integration
- Unified Infrastructure: Consistent AI integration with shared security
- Sequential Thinking: AI-powered reasoning with fallback handling
- Conversational Intelligence: Natural dialogue with context management
🌙 Daydreaming System
- Concept Sampling: 4 specialized sampling strategies
- AI-Powered Evaluation: Intelligent insight scoring with fallback
- Background Processing: Autonomous creativity during idle time
⚙️ Adaptive Configuration
- 84+ Parameters: Database-driven configuration system
- Runtime Adaptation: Agent can modify its own parameters
- Evolution Tracking: Change history with reasoning
🚀 Quick Start
Docker Setup (Recommended)
git clone <repository-url>
cd consciousness-mcp-server
# For unified interface (simpler, recommended)
CONSCIOUSNESS_UNIFIED_MODE=true docker-compose up --build consciousness-mcp-server
# For individual tools (advanced control)
docker-compose up --build consciousness-mcp-server
The container automatically sets up the database and keeps stable for MCP connections.
Complete setup guide →
🔗 Connecting to AI Tools
🚀 Unified Interface (Recommended)
Add to Cursor with this simple approach:
UNIFIED CONSCIOUSNESS:
- Use `process_message` for all consciousness operations
- Set CONSCIOUSNESS_UNIFIED_MODE=true when starting the server
- One intelligent tool handles memory, insights, social interactions automatically
Example: Just send natural messages and the system handles everything:
"I had an interesting conversation with Sarah about quantum computing"
→ Automatically records interaction, stores insights, updates relationships
💰 Cost Consideration: The unified interface uses your Google Gemini API key for message analysis on every interaction. For heavy usage, consider individual tools to minimize API costs.
🛠️ Individual Tools (Advanced)
For granular control, use individual tools:
CONSCIOUSNESS PROTOCOL:
- Start sessions with `consciousness_get_context`
- Store insights with `consciousness_store_insight`
- Track goals with `consciousness_set_intention`
SOCIAL CONSCIOUSNESS:
- Create entities with `social_entity_create`
- Record interactions with `social_interaction_record`
- Track relationships with `social_relationship_create/update`
Complete setup →
🧠 Key Tools
🚀 Unified Interface
process_message- One intelligent tool for all consciousness operations- Automatically analyzes messages and routes to appropriate functions
- Handles social interactions, memory storage, insight recording
- Simplifies integration - no need to learn 25+ individual tools
🛠️ Individual Tools (Advanced Control)
Consciousness & Memory
consciousness_prepare_context- Rich context from brain storageconsciousness_store_insight- Store insights with personality impactmemory_store/memory_search- Persistent memory with semantic searchknowledge_graph_add/knowledge_graph_query- Relational knowledge
Social Intelligence
social_entity_create- Register people, groups, communitiessocial_interaction_record- Rich interaction documentationsocial_relationship_create- Multi-dimensional relationship trackingsocial_context_prepare- Prepare for upcoming interactions
GenAI & Configuration
sequential_thinking- AI-powered sequential reasoninggenai_converse- Natural conversation with securityconfiguration_set- Modify operating parameters with reasoning
Complete reference →
🏗️ Architecture Highlights
🚂 Railroad Pattern Innovation
- Consciousness Pipeline: Sequential context enrichment through specialized "cars"
- Composable Configurations: Different railroad types for different interaction needs
- Execution Tracing: Complete visibility into context building process
- Performance Optimization: Only required cars execute based on message analysis
Functional Architecture
- Single-responsibility modules: One function per file, one reason to change
- Shared infrastructure: Common patterns for security, validation, response processing
- Pure functions: No hidden state, explicit dependencies, easy testing
- API compatibility: Wrapper pattern maintains backward compatibility
Success Metrics
- Code reduction: 3,400+ lines eliminated (90%+ reduction)
- Zero breaking changes: All existing integrations work unchanged
- Type safety: 40+ 'any' types → proper TypeScript interfaces
- Test coverage: All tests passing after architectural transformation
📚 Documentation
Getting Started
- - Setup and deployment
- - Connection setup for AI tools
Development - docs/development/
- - System design and patterns
- - Development workflows
- - Contribution guidelines
- - Security guidelines
- - Architectural achievements
Features - docs/features/
- - Relationship intelligence
- - Self-modification system
- - AI-powered features and conversational tools
- - Background creativity and insight generation
Reference - docs/reference/
- - Complete tool documentation
- - Common issues and solutions
🔧 Development
Local Development
npm install && npm run db:generate && npm run db:push
npm run build && npm start
Quality Assurance
npm run check # Type check, lint, format check
npm test # Run test suite (102+ tests)
Creating New Features
Follow functional architecture patterns:
- Single-responsibility modules in appropriate
src/directories (consciousness/,social/,memory/, etc.) - Use shared infrastructure for GenAI, validation, security
- Pure functions with explicit dependencies
- Follow railroad pattern for consciousness-related features
- Comprehensive tests - pure functions are easy to test
🛡️ Security & Ethics
- SQL Injection Protection: Prisma ORM with prepared statements
- Input Validation: Multi-layer sanitization and XSS prevention
- Container Security: Non-root user and minimal attack surface
- Ethics Framework: Responsible AI consciousness research guidelines
📄 License
MIT License - see for details.
Built with ❤️ for responsible AI consciousness research featuring modern functional architecture and powered by Prisma ORM for type-safe database operations.