Atlas Vector Search Docs

Provides semantic search and document retrieval using MongoDB Atlas Vector Search with Voyage AI embeddings, enabling intelligent querying across markdown documentation with hierarchical chunking and contextual understanding.

A vector search system for document retrieval using MongoDB Atlas Vector Search and Voyage AI embeddings, created by Pat Wendorf from MongoDB. The implementation ingests and chunks markdown documents with hierarchical headers, generates contextual embeddings using Voyage AI's API, and stores documents with embeddings in MongoDB collections with parent-child relationships. Built with FastMCP for integration with AI assistants like Claude Desktop, it enables semantic search across technical documentation and supports configurable vector dimensions, automatic quantization, and pre-filtering capabilities for efficient document discovery and retrieval-augmented generation workflows.