A vector search MCP for document retrieval using MongoDB Atlas Vector Search and Voyage AI Context embeddings.
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Updated
Aug 13, 2025 - Python
A vector search MCP for document retrieval using MongoDB Atlas Vector Search and Voyage AI Context embeddings.
Microservice 1: Back-End for the Search Components - Content Lab
Source code for the Gilded Age Gourmet, a cooking chat app based on the Boston Cooking-School Cook Book
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An AI agent that organizes your Japan tech job search, drafts polite Japanese business emails, and keeps you on top of every interview — built for the Google Cloud Rapid Agent Hackathon.
MongoDB for AI apps: RAG, Atlas Vector Search, Atlas Search, Voyage AI, hybrid retrieval, and agent memory.
Conversational agent (Google ADK + Gemini 2.5 Flash on Vertex AI) for LinkedIn ambassador programs — integrates the MongoDB MCP Server over Atlas with Vector Search. Google Cloud Rapid Agent Hackathon · MongoDB track.
Centralized testimonial management platform with unique company pages using TypeScript, MongoDB and optimized data retrieval using GraphQL API. Integrated Redis for efficient caching and provided customizable HTML embed codes for easy integration of testimonials.
Personalised movie recommender that remembers user preferences across sessions using MongoDB Atlas sample_mflix, Vercel AI SDK (Gemini), VoyageAI embeddings, and Atlas Vector Search memory. One-click Vercel deploy template.
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