MCP Self-Learning Server

A sophisticated Model Context Protocol (MCP) server that autonomously learns from interactions, optimizes performance, and continuously improves its knowledge base through pattern recognition and machine learning techniques.

🌟 Features

🧠 Autonomous Learning Engine

• Pattern Recognition: Automatically identifies and learns from interaction patterns

• Feature Extraction: Analyzes tool sequences, context, performance metrics, and semantic embeddings

• Confidence Scoring: Evaluates pattern reliability based on frequency, recency, and consistency

• Memory Consolidation: Manages short-term and long-term pattern storage

🔄 Knowledge Synchronization

• Auto-sync: Every 60 seconds between MCP servers

• Knowledge Export/Import: JSON and Markdown formats

• Pattern Merging: With deduplication

• Cross-server Learning: Through shared knowledge directory

📊 Self-Improvement Capabilities

• Performance Optimization: Identifies redundancies and bottlenecks

• Predictive Suggestions: Anticipates next actions based on learned patterns

• Error Pattern Analysis: Learns from failures to improve success rates

• Adaptive Recommendations: Generates context-aware optimizations

💾 Data Persistence

• Automatic Data Saving: Every 5 minutes with backup rotation

• Learning Data Recovery: Loads previous sessions on startup

• Export Knowledge: Multiple formats (JSON, Markdown)

• Backup System: Automatic backup creation before saves

📝 Advanced Logging

• Multi-level Logging: Debug, Info, Warn, Error with colors and emojis

• File & Console Output: Simultaneous logging to both

• Log Rotation: Prevents disk space issues

• Performance Monitoring: Tool execution times and memory usage

🚀 Quick Start

Prerequisites

• Node.js 18+

• npm or yarn

Installation

1. Clone/Download the Project

   cd ~/saralegui-solutions-llc/shared/MCPSelfLearningServer

2. Install Dependencies

   npm install

3. Configure Claude Desktop

   Add to ~/.config/Claude/claude_desktop_config.json:

   { "mcpServers": { "self-learning": { "command": "node", "args": ["/home/ben/saralegui-solutions-llc/shared/MCPSelfLearningServer/mcp-self-learning-server.js"], "env": { "NODE_ENV": "production", "LEARNING_MODE": "autonomous" } } } }

4. Start the Server

   npm start

📋 Available Commands

Development & Testing

Monitoring & Health

Manual Operations

🛠️ Available MCP Tools

Core Learning Tools

analyze_pattern

Analyze and learn from interaction patterns

get_insights

Get current learning analytics and insights

trigger_learning

Manually trigger a learning cycle

Knowledge Management

export_knowledge

Export learned knowledge to file

import_knowledge

Import knowledge from external source

Performance & Optimization

optimize_tool

Get optimization suggestions for specific tools

predict_next_action

Get predictive suggestions based on current context

get_performance_metrics

Get detailed performance analytics

📊 Monitoring & Analytics

Health Check Results

The health check tool verifies:

• ✅ Server startup functionality

• ✅ Data persistence system

• ✅ Logging system

• ✅ Performance metrics (startup time)

Real-time Monitoring

The monitor displays:

• Learning engine status (patterns, knowledge, cycles)

• Log file metrics and activity

• System resource usage

• Change indicators showing growth over time

Performance Expectations

🗂️ Directory Structure

🔧 Configuration

Environment Variables

Learning Engine Settings

• Max Memory Size: 1000 patterns in memory

• Auto-save Interval: 5 minutes

• Pattern Confidence Threshold: 0.5

• Learning Trigger: Every 100 interactions or 50 tool uses

🚨 Troubleshooting

Common Issues

1. Server Won't Start

   • Check Node.js version (18+ required)

   • Verify all dependencies installed: npm install

   • Check file permissions

2. Data Not Persisting

   • Verify data/ directory permissions

   • Check disk space

   • Review logs for errors: tail -f logs/mcp-server.log

3. High Memory Usage

   • Run health check: npm run health

   • Check pattern count: npm run monitor

   • Consider reducing max memory size

4. Slow Performance

   • Enable performance logging: npm run debug

   • Check system resources

   • Review learning cycle frequency

Log Analysis

📈 Expected Learning Outcomes

Immediate (0-100 interactions)

• Basic pattern recognition active

• Initial knowledge base building

• Tool usage tracking enabled

Short-term (100-1000 interactions)

• Pattern confidence scores stabilizing

• First optimization recommendations

• Predictive accuracy ~50%

Long-term (1000+ interactions)

• Predictive accuracy >70%

• Response time improvements ~30%

• Comprehensive knowledge graph

• Cross-server knowledge sharing

• Self-documenting insights

🤝 Integration with Claude

Once configured, the server provides these tools in Claude:

• Pattern analysis for learning from conversations

• Performance insights for optimization

• Predictive suggestions for improved responses

• Knowledge export for documentation

• Real-time learning from every interaction

📝 License

ISC License

🆘 Support

For issues or questions:

1. Run health check: npm run health

2. Check logs: tail -f logs/mcp-server.log

3. Review this documentation

4. Check server status: npm run monitor

Built with ❤️ for autonomous learning and continuous improvement