vector-database

A modern desktop application for exploring, managing, and analyzing vector databases

Local RAG MCP server for Claude Code — hybrid search (semantic + BM25), cross-encoder reranking, 13 MCP tools, 20 format parsers. Zero external servers, zero API keys.

A pure-Go, single-file AI memory and knowledge graph library and plugin.

Vector Storage is a vector database that enables semantic similarity searches on text documents in the browser's local storage. It uses OpenAI embeddings to convert documents into vectors and allows searching for similar documents based on cosine similarity.

Suite of tools containing an in-memory vector datastore and AI proxy

Graph RAG with pure vector search, achieving SOTA performance in multi-hop reasoning scenarios.

The Kubernetes operator for K8ssandra

High performance embedded vector database

Xmem is a India's First open source multi-modal, multi-agentic long‑term memory layer for AI agents.

In-memory vector index for Go

Python client for Antarys vector database, optimized for large-scale vector operations with built-in caching, parallel processing, and dimension validation.

Strwythura: construct an entity-resolved knowledge graph from structured data sources and unstructured content sources, implementing an ontology pipeline, plus context engineering for optimizing AI application outcomes within a specific domain. This produces a Streamlit app, with MLOps instrumentation.

🧠 The Brain for Your AI — Local-first memory engine for AI agents. Store, recall, and search memories with semantic embeddings. Single Rust binary, zero config, fully offline.

⚡ GUI for editing LLM vector embeddings. No more blind chunking. Upload content in any file extension, join and split chunks, edit metadata and embedding tokens + remove stop-words and punctuation with one click, add images, and download in .veml to share it with your team.

Swift Vector Database. On-device, local vector database for building the next-generation of user experiences

Agent skills for Qdrant vector search: scaling, performance optimization, search quality, monitoring, deployment, model migration, version upgrades, and SDK usage across Python, TypeScript, Rust, Go, .NET, Java

A lightweight, production-ready RAG (Retrieval Augmented Generation) library in Go.

Open multilingual construction cost database for AI Agents - 55K+ work items, 27K+ resources, 30 regions. Semantic search via Qdrant vector DB

Backend library for conversational AI in biomedicine

The Go client for Chroma vector database