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by archana-mukunthamani • Uncategorized
An AI-powered digital twin assistant using Retrieval-Augmented Generation to answer questions about professional profiles.
Provide context-aware answers about professional profiles using semantic search and LLMs.
Simulate technical interviews and assess candidate performance with detailed analytics.
Analyze job postings and tailor job application materials based on profile matching.
This MCP server implements a digital twin assistant that leverages semantic vector search and large language models to provide context-aware, accurate responses about a user's professional experience, skills, and projects. It supports interactive interview simulations, job matching, and analytics dashboards to track performance over time. The system integrates Upstash Vector for semantic search, Upstash Redis for analytics storage, and Groq's Llama 3.3 70B model for grounded response generation, offering a comprehensive tool for career development and interview preparation.