vector search

Omni is a local-first semantic search app for macOS that indexes text, code, PDFs, images, audio, and video on-device. It supports multilingual search, private offline use, and exposes a local endpoint for agents to query indexed files.

Enterprise Postgres platform for AI apps, with managed, BYO cloud, and on-prem deployment options. It adds built-in MCP access for agents, pgvector and hybrid search for RAG, branching for isolated experiments, and a path from prototype to production.

A Python GraphRAG library for PostgreSQL that combines entity/relation extraction, pgvector embeddings, graph traversal, and full-text search to answer questions with time-aware updates.

A single-binary local MCP server that turns a codebase into AI context using AST parsing, call graphs, and local embeddings. It targets privacy-sensitive and air-gapped workflows and can serve indexed code context to editors and MCP clients.

A local-first backend for AI agents that bundles documents, vector search, cache, queues, and cron jobs into one SQLite file, with optional Postgres support.

Local-first federated search for AI agents that queries transcripts, files, a knowledge graph, a vector store, and the web, then merges results with trust-weighted ranking.

A lightweight CLI for running RAG over local documents, with hybrid vector + BM25 retrieval, OCR for scans and images, and support for local or API-based LLMs.

Polygres is a Postgres platform built for agent and retrieval workloads, combining hosted PostgreSQL with native graph traversal, HNSW vector search, and hybrid retrieval APIs. The page shows a working product site, SDK usage, API/runtime connection details, and example hybrid queries.

A cognitive memory engine for AI agents with temporal decay, contradiction detection, autonomous consolidation, knowledge graph support, and ANN recall via HNSW. The repo shows Rust and Python usage, MCP client setup, and a quick-start path for agents and developers.

Sana is an object-storage-native search database for vectors, full-text search, and attribute filters. The repo describes durability, indexing, backends, operations, and quick-start commands for running the service or demo.

A curated GitHub list and benchmark leaderboard for ultra-lightweight, zero-dependency AI engines in C/C++/Rust/Assembly, covering local LLMs, vector search, memory, GEMM, and agent tooling.