A search engine built for AI — embeddings-based retrieval that finds pages by meaning, not keyword overlap.
Data & AnalyticsFreemium
Embeddings
Vector representations of text and media that power semantic search and retrieval.
5 apps, 2 skills and 1 MCP server tagged Embeddings.
Apps
An open-source AI-native database combining vector search, structured filtering, and built-in model integrations.
Data & AnalyticsFreemium
The embedding database that starts as a Python import and grows into a distributed cloud service.
Data & AnalyticsFreemium
An open-source vector search engine written in Rust — fast, memory-efficient, and self-hostable.
Data & AnalyticsFreemium
A fully managed vector database for semantic search and retrieval at billion-scale, with no infrastructure to run.
Data & AnalyticsFreemium
Skills
Take an OpenSearch search application from requirements to a running cluster — BM25, dense and sparse vectors, hybrid retrieval, agentic search and RAG, with relevance evaluation built in.
3 views
Weaviate's official skill for searching and managing vector collections — hybrid, semantic and keyword search, schema inspection, filtered fetches and bulk imports.
4 views
MCP servers
MCP: Chroma
by Chroma
Chroma's official MCP server — build and query vector collections directly from an AI client.
4 views
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