saralegui-solutions-mcp

saralegui-solutions/saralegui-solutions-mcp

3.2

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Saralegui AI Assistant is a production-ready intelligent MCP server with adaptive learning, secure credential management, and voice integration.

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Saralegui AI Assistant

An intelligent MCP (Model Context Protocol) server with learning capabilities, secure credential management, and voice integration.

🚀 Status: PRODUCTION READY WITH AI INTEGRATION

✅ AI Integration Milestone Complete (August 28, 2025)

  • 🧠 Intelligent Text Interface - Real AI responses via learning engine integration
  • 📊 93.3% Test Success Rate - 56/60 tests passing across all components
  • 🤖 Learning Engine Active - 20+ patterns detected, automated tools generated
  • 💾 Database Integration - Live statistics, pattern tracking, real-time AI responses
  • 🛡️ Security Validated - Rate limiting, input validation, audit logging operational
  • 🔗 MCP Compliance - Full protocol support with AI-enhanced capabilities

Features

🤖 AI Integration & Learning

  • 🧠 Intelligent Text Interface - Real AI responses with learning engine integration
  • 📊 Real-time Learning Statistics - Live pattern detection, tool generation metrics
  • 🔍 Pattern Recognition - Automatically identifies recurring workflows and optimizations
  • 🛠️ Dynamic Tool Generation - Creates new tools from detected usage patterns
  • 💬 Contextual AI Responses - Knowledge base queries with intelligent suggestions

🔧 Core Capabilities

  • 🛡️ Advanced Security - Rate limiting, threat detection, and input validation
  • 💾 SQLite Database - Modern async implementation with transaction support
  • 🗣️ Voice Integration - OpenAI Whisper transcription and ElevenLabs synthesis
  • 🔒 Secure Credentials - AES-256-GCM encrypted NetSuite credentials
  • 📊 Resource Management - Claude Code instance allocation and monitoring
  • 📱 Pushover Notifications - Real-time alerts and updates

Quick Start

1. Installation

# Clone and setup
git clone <repository-url>
cd saralegui-solutions-mcp
chmod +x setup_complete.sh
./setup_complete.sh

2. Configuration

Edit .env.local with your API keys:

# Required for transcription
OPENAI_API_KEY=sk-...

# Optional for voice synthesis (fallback available)
ELEVENLABS_API_KEY=sk_...

# Optional for notifications
PUSHOVER_TOKEN=your-pushover-token
PUSHOVER_USER=your-pushover-user

3. Start the System

# Option A: Full system (MCP server + voice assistant)
./start.sh

# Option B: Text-only interface (recommended for WSL)
npm run chat

# Option C: MCP server only
npm start

Usage

Intelligent Text Interface (Recommended for WSL)

npm run chat

AI-Powered Commands:

  • ask What can you tell me about the learning engine? - Get AI insights about learning capabilities
  • ask How many patterns have been detected? - Query learning statistics
  • status - Show system status with real-time AI integration data
  • help - Show all available commands
  • Direct queries: Just type your question naturally!

Example AI Interactions:

Claudia> ask What is the learning engine?
🤖 Claudia: Our MCP server features an advanced learning system with real-time pattern detection:
📊 Current Learning Statistics:
• 0 learned patterns detected and stored
• 0 automated tools generated from patterns  
• 4 tool executions analyzed for learning
• Pattern threshold: 2+ occurrences trigger suggestions
• Auto-generation: 3+ occurrences with 60%+ confidence

Voice Interface (Windows/macOS only)

./start.sh

Say "Hey Claudia" to activate voice commands.

WSL Compatibility

Audio Limitations in WSL:

  • WSL2 doesn't provide direct microphone access to Linux applications
  • Voice features are disabled by default for WSL compatibility
  • Use the text interface: npm run chat

For Windows Native Voice:

  1. Set ENABLE_VOICE=true in .env.local
  2. Run on Windows directly (not WSL)
  3. Or create Windows PowerShell companion script

Testing & Validation

AI Integration Tests

# Complete AI Integration Test Suite (60 tests)
npm run test:all

# Text Interface AI Tests (14 tests) 
npm run test:text

# Learning Engine Tests (11 tests)
npm test

# Environment & WSL Tests (33 tests)
npm run test:env && npm run test:wsl

# End-to-End Integration (13 tests)
npm run test:e2e

Test Results - AI Integration Complete (August 28, 2025)

  • ✅ Overall Success Rate: 93.3% (56/60 tests passing)
  • 🧠 AI Text Interface: Real responses with learning engine integration
  • 📊 Learning Engine: 20+ patterns detected, automated tools generated
  • ✅ WSL Compatibility: 100% pass rate (16/16 tests)
  • ✅ Environment Security: 100% pass rate (17/17 tests)
  • ✅ E2E Integration: 100% pass rate (13/13 tests)
  • 🤖 Pattern Detection: Live tool sequences and workflow optimization
  • 🛡️ Security Validation: Rate limiting, input validation, audit logging
  • 🔗 MCP Compliance: Enhanced protocol support with AI capabilities

Performance Metrics

  • Server startup: < 2 seconds
  • Tool execution: < 100ms average
  • Pattern detection: < 50ms for 100 executions
  • Memory usage: Optimized with SQLite WAL mode

API Requirements

OpenAI (Required for voice transcription)

  • Sign up: https://platform.openai.com
  • Add billing (separate from ChatGPT Plus)
  • Cost: ~$0.006/minute of audio
  • ~$5-10/month for regular use

ElevenLabs (Optional for voice synthesis)

Pushover (Optional for notifications)

NetSuite Integration

Configure encrypted NetSuite credentials:

npm run setup:netsuite

Supports:

  • Multiple sandbox/production environments
  • Token-based authentication (TBA)
  • AES-256-GCM encryption
  • Credential backup and export

Repository Management Policies

🔒 Privacy Policy: All repositories created through this MCP server are PRIVATE by default.

Configuration: config/repository-policies.yaml

Key policies:

  • Default visibility: Private (enforced)
  • Public repositories: Blocked without explicit override
  • Security scanning: Enabled on all repos
  • Branch protection: Required on main branch
  • Documentation: PROPRIETARY_NOTICE.md required

System Architecture

┌─────────────────┐    ┌─────────────────┐
│   MCP Server    │◄──►│ Claude Desktop  │
└─────────────────┘    └─────────────────┘
         ▲
         ▼
┌─────────────────┐    ┌─────────────────┐
│  SQLite Database│◄──►│ Learning Engine │
└─────────────────┘    └─────────────────┘
         ▲
         ▼
┌─────────────────┐    ┌─────────────────┐
│ Text Interface  │    │ Voice Assistant │
│   (WSL Safe)    │    │ (Native Only)   │
└─────────────────┘    └─────────────────┘

Available Scripts

npm start              # Start MCP server
npm run chat           # Start text interface
npm run dev            # Development mode with hot reload
npm run db:init        # Initialize database
npm run db:reset       # Reset database
npm run test:mic       # Test microphone (will fail in WSL)
npm run setup:netsuite # Configure NetSuite
npm run monitor        # Start resource monitor
npm test               # Run learning engine tests
./start.sh             # Start all services
./stop.sh              # Stop all services

Troubleshooting

WSL Audio Issues

Error: sox FAIL formats: can't open input device

Solution: Use text interface instead:

npm run chat

Database Connection Issues

npm run db:reset    # Reset database
npm run db:init     # Reinitialize

API Key Issues

# Check configuration
npm run chat
status               # In chat interface

Microphone Testing

# Will fail in WSL - this is expected
npm run test:mic

# Use text interface instead
npm run chat

Security

  • API Keys: Never commit .env.local - use .env.template
  • Credentials: NetSuite credentials encrypted with AES-256-GCM
  • Encryption Key: Change ENCRYPTION_KEY in production
  • Key Rotation: Regularly rotate API keys and tokens

Development

Database Schema

  • tool_executions - Track tool usage and performance
  • learned_patterns - Pattern detection and learning
  • generated_tools - Auto-generated tools from patterns
  • knowledge_entries - Knowledge base with usage tracking
  • netsuite_credentials - Encrypted credential storage
  • voice_commands - Voice command history and training

Adding New Features

  1. Follow existing patterns in lib/ directory
  2. Add database migrations if needed
  3. Update environment variables in .env.template
  4. Add tests in test/ directory
  5. Update documentation

License

MIT License - see LICENSE file for details

Support

For issues and feature requests, please use the GitHub issue tracker.