#vector-search

Full AI context and content layer for coding agents over one MCP server — tree-sitter code-map, document RAG, shared memory, multi-agent comms, web crawl, git history + blame. 300+ languages, 10+ agent harnesses, pure Rust.

Local AI-powered document search and editing with first-in-class hybrid retrieval, LLM answers, WebUI, REST API and MCP support for AI clients.

Keine Repository-Beschreibung veröffentlicht.

RedDB is a multi-structure database engine for applications that need structured rows, raw payloads, linked entities, semantic retrieval, graph analytics, operational metadata and exports without splitting data across multiple systems.

RuvNet Brain — a downloadable, source-grounded brain for Claude Code over Reuven Cohen's (rUv's) RuvNet stack: RuVector/RVF, Ruflo, AgentDB, RuLake, SPARC + 21 building blocks. Grounds Claude in real source via one MCP tool (search_ruvnet), so it builds with the stack instead of drifting off it.

Hermes Agent memory plugin/provider for scope-aware recall, SQLite truth, LanceDB semantic search, and hybrid retrieval.

Local-first, inspectable memory for coding agents: durable context across sessions and repositories, code-aware recall, bi-temporal history, MCP, and a self-hosted WebUI.

Go SDK for Dakera AI agent memory — self-hosted, 88.2% LoCoMo. Vectors, hybrid search, knowledge graphs, sessions.

Two-tier hybrid search for Rust: sub-millisecond initial results via potion-128M, quality-refined rankings in 150ms via MiniLM-L6-v2. Combines lexical (Tantivy BM25) and semantic (vector cosine) search with Reciprocal Rank Fusion. Progressive iterator API, f16 SIMD vector index, feature-gated compilation.

Rust implementation of a bunch of approximate nearest neighbours searches; now with Python bindings

Keine Repository-Beschreibung veröffentlicht.

Hybrid search for Obsidian vaults via plugin, CLI, and MCP server

Toolkit for testing and packaging portable AI agents across various LLMs, frameworks, and deployment targets

🌌 A complete search engine and RAG pipeline in your browser, server or edge network with support for full-text, vector, and hybrid search in less than 2kb.

CPersona — persistent memory for AI agents over MCP. One SQLite file you own, hybrid vector + full-text + keyword search, no LLM in the loop, and honest reporting when recall degrades. MIT licensed.

Embeddable, in-memory, document-oriented database with a high-level Query builder interface.

🥤 RAGLite is a Python toolkit for Retrieval-Augmented Generation (RAG) with DuckDB or PostgreSQL

Verified experience for AI agents: independently checked, scoped, cited, and reversible.

Embedded single file SQL database written in Golang

SeekStorm: vector & lexical search - in-process library & multi-tenancy server, in Rust.

The unified database engine: native SQL, vector search (HNSW), and columnar storage in one Rust engine — from an embedded file to a distributed cluster.

Self-hosted MCP server to index and search any documentation site—public or private

Give any MCP-capable agent persistent memory: remember/recall over a tiered store with hybrid vector + keyword retrieval. Single Go binary, SQLite or Postgres, embedded admin UI.

MongoDB Search

Persistent memory MCP server for AI agents — Rust, 19 tools, knowledge graph, Hebbian learning, episodic memory, contradiction detection, prospective triggers, Bayesian calibration, zero-config Docker setup.

Reflective memory for agents

kevy — a pure-Rust, zero-dependency, Redis-compatible serving engine: declared indexes, CJK full-text + vector search, views, CDC feeds, replication & failover, MCP

Persistent graph-native memory for coding agents — works with any MCP agent. SQLite + FTS5, model-agnostic.