mongodb-ai

What problem does it solve?

MongoDB Atlas Vector Search and AI integration patterns provide up-to-date guidance for building semantic search, RAG pipelines, and AI agent memory within MongoDB, addressing knowledge gaps in vector-based workflows.

Core Features & Use Cases

• Design and optimize vector indexes with correct numDimensions, similarity, and pre-filtering for scalable recall.
• Implement $vectorSearch, RAG ingestion/retrieval, and hybrid search with $rankFusion/$scoreFusion.
• Manage AI agent memory (short- and long-term) with semantic retrieval and context-aware prompts.

Quick Start

Run a starter example that creates a vector index, runs a $vectorSearch query, or demonstrates a basic RAG pattern.