#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.

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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

该仓库未发布描述。

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.