Embedding Atlas provides interactive visualizations for high-dimensional embeddings produced by ML models. It supports automatic clustering, kernel density estimation, real-time nearest-neighbor search, and linked dashboards for cross-filtering metadata. The tool includes built-in viewers for text, image, audio, and other data types commonly associated with embedding pipelines. AI agents can interact with the tool via Model Context Protocol to query schemas, run queries, and capture visualizations.