AI memory

Aurra is memory infrastructure for AI agents, with bi-temporal versioning, source-cited memory history, and an automatic supersession feature that uses an LLM classifier to decide when new facts replace old ones.

CMEM is an AI agent memory layer for coding agents, with an open-source local engine and a managed cloud service that syncs observations through a private MCP link. It supports Claude Code, Cursor, Windsurf, Codex, Gemini CLI, and other MCP clients.

Local-first AI memory layer for LLM apps with persistent knowledge graph storage, entity extraction, semantic retrieval, and API endpoints for ingesting and retrieving context.

Bourdon is a recognition-first memory runtime for AI agents, built to share memory across tools like Claude Code, Codex, Cursor, and others. The site shows install commands, product positioning, pricing, and several live field tests.

Local-first memory layer for coding agents with an MCP server, CLI, and desktop console for durable project context, handoffs, and recall across sessions.

A persistent memory layer for AI agents, built as a standard MCP server with local setup, dashboard, and benchmark claims against other memory tools.

HelixDB is an OLTP graph-vector database built in Rust, aimed at AI apps, knowledge graphs, and memory layers. The page shows the product’s core model, CLI workflow, SDK examples, and local setup commands.

xysq.ai is a collaborative memory platform for AI-native teams and enterprises. It connects tools like Slack, Gmail, Drive, Notion, GitHub, Jira, and Linear to build shared context and provide agents with the right information when needed.

A short interactive experiment that asks users to paste a prompt into their AI and measure how much personal context it can recall or infer.