Sponsored by Deepsite.site

Skip Tracing POC - Professional Demo Platform

Created By
GautaVaid7 months ago
Professional skip tracing demo built with 6-server MCP stack - Locate individuals and gather contact information with AI-powered confidence scoring
Content

Skip Tracing POC - Professional Demo Platform

License: MIT Node.js React MCP Integration

Professional skip tracing demo built with 6-server MCP stack for maximum development efficiency and enterprise-grade quality.

🎯 Project Overview

Skip Tracing POC is a proof-of-concept demonstration platform that showcases automated skip tracing capabilities for repo companies, debt collectors, and legal professionals. The system aggregates data from 20+ verified sources to locate individuals and gather contact information with professional confidence scoring.

Key Features

  • Real-time Multi-Source Search - Query 20+ databases simultaneously
  • 🎯 Confidence Scoring - AI-powered result validation and ranking
  • 📊 Professional Reporting - PDF/CSV exports with branding
  • 📱 Mobile Responsive - Works across all devices and browsers
  • 🔒 Privacy Compliant - GDPR/CCPA compliant data handling
  • 🚀 Enterprise Ready - Scalable architecture with comprehensive testing

Success Metrics Target

  • 50+ beta users test the demo
  • 60%+ positive feedback on concept validation
  • Sub-30 second search response times
  • 95%+ uptime during beta testing period

🏗️ MCP Stack Architecture

This project leverages the ultimate 6-Server MCP Stack for professional development:

MCP ServerPurposeStatus
🗂️ FilesystemDirect file operations and management✅ Configured
🔧 GitProfessional version control workflow✅ Configured
🐙 GitHubProject management and collaboration✅ Configured
🎭 PlaywrightComprehensive testing and QA✅ Configured
🔍 ApifySkip tracing functionality and validation✅ Configured
🗄️ SupabaseDatabase operations and analytics✅ Configured

🚀 Quick Start

Prerequisites

  • Node.js 18+ and npm
  • Git for version control
  • Supabase account for database
  • Apify account for skip tracing APIs
  • Claude Desktop with MCP configuration

Installation

  1. Clone the repository

    git clone https://github.com/GautaVaid/Skip_Tracing.git
    cd Skip_Tracing
    
  2. Install dependencies

    # Install backend dependencies
    cd server && npm install
    
    # Install frontend dependencies  
    cd ../client && npm install
    
  3. Environment setup

    # Copy environment template
    cp .env.example .env
    
    # Configure your API keys:
    # - APIFY_TOKEN=your_apify_token
    # - SUPABASE_URL=your_supabase_url
    # - SUPABASE_ANON_KEY=your_supabase_key
    
  4. Database setup

    cd database
    npm run migrate
    npm run seed
    
  5. Start development servers

    # Terminal 1: Backend
    cd server && npm run dev
    
    # Terminal 2: Frontend
    cd client && npm run dev
    
  6. Open the application

📁 Project Structure

Skip_Tracing/
├── client/                 # React frontend application
│   ├── src/
│   │   ├── components/     # Reusable UI components
│   │   ├── pages/         # Page-level components
│   │   └── utils/         # Frontend utilities
│   └── package.json
├── server/                # Node.js backend API
│   ├── routes/           # API endpoint definitions
│   ├── engines/          # Skip tracing engine core
│   ├── actors/           # Apify actor integrations
│   └── package.json
├── database/             # Database schema and migrations
│   ├── schema/          # Supabase table definitions
│   └── migrations/      # Database migration files
├── tests/               # Comprehensive test suite
│   ├── e2e/            # End-to-end tests (Playwright)
│   ├── api/            # API integration tests
│   └── unit/           # Unit tests
├── docs/               # Project documentation
├── deployment/         # Deployment configuration
└── config/            # MCP and application configuration

🧪 Testing

Run Test Suite

# Run all tests
npm run test

# Run specific test types
npm run test:unit        # Unit tests
npm run test:api         # API integration tests  
npm run test:e2e         # End-to-end tests (Playwright)
npm run test:performance # Performance benchmarks

Test Coverage

  • Target: 80%+ code coverage
  • Current: Will be displayed after first test run
  • Reports: Generated in coverage/ directory

🔧 Development Workflow

Branch Strategy (GitFlow)

  • main - Production-ready code
  • develop - Integration branch for features
  • feature/ - Individual feature development
  • hotfix/ - Critical production fixes
  • release/ - Release preparation

Commit Standards

We use Conventional Commits:

feat: add skip trace result confidence scoring
fix: resolve mobile responsive layout issues  
docs: update API documentation for search endpoints
test: add end-to-end tests for export functionality

Code Quality

  • ESLint - Code linting and style enforcement
  • Prettier - Code formatting
  • Husky - Git hooks for quality gates
  • File Limit - Maximum 500 lines per file

📊 API Documentation

Core Endpoints

Search Operations

  • POST /api/search - Perform skip trace search
  • GET /api/search/:id - Retrieve search results
  • DELETE /api/search/:id - Cancel active search

Export Operations

  • POST /api/export/pdf - Generate PDF report
  • POST /api/export/csv - Generate CSV export
  • POST /api/export/email - Email report to user

Analytics

  • GET /api/analytics/dashboard - Get analytics dashboard data
  • POST /api/analytics/event - Track user interaction event

Rate Limits

  • Search API: 10 requests per minute per IP
  • Export API: 5 requests per minute per IP
  • Analytics API: 100 requests per minute per IP

🔒 Security & Privacy

Data Protection

  • All PII is encrypted at rest and in transit
  • Search results are automatically purged after 24 hours
  • No user authentication required for demo (anonymous usage)
  • GDPR/CCPA compliant data handling procedures

API Security

  • Rate limiting on all endpoints
  • Input validation and sanitization
  • XSS and SQL injection protection
  • CORS configuration for frontend domains

🚀 Deployment

Development

  • Frontend: Deployed to development server
  • Backend: Containerized with Docker
  • Database: Supabase cloud instance

Production (Future)

  • Frontend: CDN deployment with caching
  • Backend: Auto-scaling container orchestration
  • Database: Production Supabase with backups
  • Monitoring: Comprehensive logging and alerting

📈 Performance Benchmarks

Target Performance

  • Search Response: < 30 seconds average
  • Page Load Time: < 3 seconds initial load
  • API Response: < 500ms for non-search endpoints
  • Uptime: 99.9% availability target

Optimization Features

  • Result caching for repeated searches
  • Database query optimization
  • Frontend code splitting and lazy loading
  • CDN for static assets

🤝 Contributing

We welcome contributions! Please see CONTRIBUTING.md for details on:

  • Code of conduct
  • Development setup
  • Pull request process
  • Coding standards
  • Testing requirements

Getting Help

  • Issues: Create GitHub issue for bugs or feature requests
  • Discussions: Use GitHub Discussions for questions
  • Documentation: Check /docs directory for detailed guides

📋 Development Roadmap

Phase 1: Foundation ✅

  • MCP stack configuration and validation
  • Repository setup and Git workflow
  • Project structure and documentation

Phase 2: Core Development 🚧

  • Database schema and backend API
  • Skip tracing engine and Apify integration
  • Frontend components and user interface

Phase 3: Testing & Quality 📋

  • Comprehensive test suite implementation
  • Performance optimization and benchmarking
  • Security auditing and compliance validation

Phase 4: Production Ready 🎯

  • Export functionality and professional features
  • Deployment automation and monitoring
  • Beta user onboarding and feedback collection

📄 License

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

🙏 Acknowledgments

  • Apify Platform - Skip tracing data source integration
  • Supabase - Database and backend services
  • MCP Protocol - AI-powered development acceleration
  • Beta Users - Valuable feedback and testing support

Built with ❤️ using the 6-Server MCP Stack for maximum development efficiency

Transform weeks of development into days with AI-powered professional workflows

Recommend Servers
TraeBuild with Free GPT-4.1 & Claude 3.7. Fully MCP-Ready.
Visual Studio Code - Open Source ("Code - OSS")Visual Studio Code
AiimagemultistyleA Model Context Protocol (MCP) server for image generation and manipulation using fal.ai's Stable Diffusion model.
Amap Maps高德地图官方 MCP Server
TimeA Model Context Protocol server that provides time and timezone conversion capabilities. This server enables LLMs to get current time information and perform timezone conversions using IANA timezone names, with automatic system timezone detection.
MCP AdvisorMCP Advisor & Installation - Use the right MCP server for your needs
BlenderBlenderMCP connects Blender to Claude AI through the Model Context Protocol (MCP), allowing Claude to directly interact with and control Blender. This integration enables prompt assisted 3D modeling, scene creation, and manipulation.
Playwright McpPlaywright MCP server
WindsurfThe new purpose-built IDE to harness magic
Context7Context7 MCP Server -- Up-to-date code documentation for LLMs and AI code editors
ChatWiseThe second fastest AI chatbot™
CursorThe AI Code Editor
Jina AI MCP ToolsA Model Context Protocol (MCP) server that integrates with Jina AI Search Foundation APIs.
EdgeOne Pages MCPAn MCP service designed for deploying HTML content to EdgeOne Pages and obtaining an accessible public URL.
Howtocook Mcp基于Anduin2017 / HowToCook (程序员在家做饭指南)的mcp server,帮你推荐菜谱、规划膳食,解决“今天吃什么“的世纪难题; Based on Anduin2017/HowToCook (Programmer's Guide to Cooking at Home), MCP Server helps you recommend recipes, plan meals, and solve the century old problem of "what to eat today"
Baidu Map百度地图核心API现已全面兼容MCP协议,是国内首家兼容MCP协议的地图服务商。
Zhipu Web SearchZhipu Web Search MCP Server is a search engine specifically designed for large models. It integrates four search engines, allowing users to flexibly compare and switch between them. Building upon the web crawling and ranking capabilities of traditional search engines, it enhances intent recognition capabilities, returning results more suitable for large model processing (such as webpage titles, URLs, summaries, site names, site icons, etc.). This helps AI applications achieve "dynamic knowledge acquisition" and "precise scenario adaptation" capabilities.
Serper MCP ServerA Serper MCP Server
MiniMax MCPOfficial MiniMax Model Context Protocol (MCP) server that enables interaction with powerful Text to Speech, image generation and video generation APIs.
Tavily Mcp
DeepChatYour AI Partner on Desktop