#vector-search

Search code and feature records by meaning through the command line or Model Context Protocol (MCP). Inference runs on your GPU.

Declarative SQL query engine for Qdrant and edge vector databases. Multi-vector dense & BM25 sparse search, hybrid retrieval, CTEs, and MMR in Rust, Python, Node.js, and WebAssembly

Semantic memory for AI agents — local-first MCP server with hybrid search, governance, and consolidation

High-performance graph database + vector search powered by InterSystems IRIS

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

Self-hosted retrieval infrastructure for AI assistants. MCP-first search and grounded answers over a private corpus, with citations that resolve to a real location in a real document — a page, a heading, a line, a cell.

OramaCore is the complete runtime you need for your projects, answer engines, copilots, and search. It includes a fully-fledged full-text search engine, vector database, LLM interface, and many more utilities.

End-to-end encrypted memory for AI agents — portable, yours forever.

saige - Super Artificial Intelligence Graph Environment. A unified Go SDK, CLI, and MCP server for streaming AI agents, knowledge graphs, and RAG pipelines, with Ollama, OpenAI, Anthropic, and Google providers behind one interface.

AI-Lake Format: self-contained Parquet + HNSW index — unifying tabular data, embeddings, and vector search in a single Iceberg-compatible file

The Ultimate Vectors Library for Java

Production-ready .NET 10 RAG library with hybrid vector + keyword search, multi-backend storage (SQLite, PostgreSQL, Neo4j, Qdrant), and MCP server integration.

Ruby wrapper for the Qdrant vector search database API

RushDB is a graph + vector database and memory layer for AI agents. Push any JSON, get typed, searchable, relationship-aware records back — no schema, no migrations. Built on Neo4j.

Open-source Java/SpringAI/Spring Boot AI enablement/orchestration layer for applications with RAG, governed actions, providers, vector stores, PII, tenant safety, chat memory, and behavior analysis.

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Kura — the knowledgebase for humans and agents. Agent-native docs infrastructure, built on June.

An Approximate Nearest Neighbors library in Rust, based on random projections and LMDB and optimized for memory usage :boom:

Evidence-first, multilingual, S3-native RAG — answers only from cited evidence (exact quote, page, bbox) and abstains when the evidence is weak, missing or conflicting. The guarantee is "no ungrounded claim". Byte-identical core across Python, Go and JavaScript. Docs: https://muthuishere.github.io/citenexus/

Standalone AI agent memory engine — hybrid search (BM25 + vectors), Q-learning scoring, Ebbinghaus decay, tiered storage, knowledge graph. Part of TRW Framework.

Local-first encrypted memory for AI agents