Skip Tracing POC Server

The Skip Tracing POC is a fully‑featured demonstration platform that brings automated skip tracing to the fingertips of repo companies, debt collectors, and legal professionals. By aggregating data from more than twenty vetted sources—public records, credit bureaus, social media, and proprietary databases—the system delivers a single, unified view of an individual’s contact details, financial status, and potential liabilities. This consolidation eliminates the need for manual cross‑checking, dramatically speeding up investigations and reducing the risk of missed leads.

At its core, the server exposes a set of MCP endpoints that allow an AI assistant to perform real‑time searches across all integrated data sources. The Apify server orchestrates the heavy lifting, running pre‑built actors that crawl and parse each source while maintaining GDPR/CCPA compliance. Results are returned in a structured format, enriched with an AI‑generated confidence score that ranks the reliability of each match. Developers can leverage this scoring to surface the most promising leads first, or to trigger follow‑up actions such as automated outreach or legal notifications.

The platform’s architecture is built on a 6‑Server MCP stack, ensuring that each layer—filesystem, Git, GitHub, Playwright, Apify, and Supabase—is dedicated to a specific concern. This separation of duties not only streamlines development but also provides clear boundaries for testing, version control, and data persistence. The Supabase server stores search history, user preferences, and analytics, while the Playwright server guarantees that every component behaves as expected through end‑to‑end tests. The result is an enterprise‑grade system that can scale horizontally, maintain 95 % uptime during beta testing, and deliver sub‑30‑second response times for most queries.

Real‑world use cases abound: a debt collector can input a debtor’s name and instantly retrieve all available addresses, phone numbers, and public filings; a legal firm can confirm the whereabouts of a witness before scheduling deposition; or a repo company can verify property ownership records to avoid costly mistakes. In each scenario, the AI assistant can issue a single MCP command—such as “search for John Doe”—and receive a comprehensive, ranked report ready for export to PDF or CSV. This tight integration with AI workflows means developers can embed skip tracing directly into larger investigative pipelines, automating routine checks and freeing human analysts to focus on higher‑value tasks.

What sets this server apart is its blend of real‑time multi‑source querying, AI‑driven confidence scoring, and enterprise‑ready deployment. By combining proven technologies like Apify actors with a robust MCP stack, the platform delivers a reliable, scalable solution that reduces manual effort, enhances data quality, and accelerates decision‑making for professionals who need to locate individuals quickly and accurately.