Agentmemory
Summary
Agentmemory offers persistent memory for AI models such as Codex, Hermes, OpenClaw, and Claude, allowing them to maintain long-term context across interactions.
Similar Articles
rohitg00/agentmemory
agentmemory is an open-source persistent memory layer for AI coding agents (Claude Code, Cursor, Gemini CLI, Codex CLI, etc.) that uses knowledge graphs, confidence scoring, and hybrid search to give agents long-term memory across sessions via MCP, hooks, or REST API. Built on the iii engine, it requires no external databases and exposes 51 MCP tools.
@dr_cintas: You can now give Hermes, Claude Code, and Codex infinite memory It's called agentmemory. Records what your agent does d…
Agentmemory is a free, open-source tool that gives AI agents like Hermes, Claude Code, and Codex infinite memory by recording session activity, compressing it with AI, and injecting relevant context into future sessions. It has over 4,000 GitHub stars.
I kept losing agent memory between sessions, so I built a memory broker that isolates per-agent and survives restarts
The author built HeurChain, a memory broker that provides agent-specific, persistent memory storage for AI agents, surviving restarts and supporting structured and semantic retrieval.
@akshay_pachaar: the three-tier memory of Hermes agent. AI agents forgets everything when your session ends. Hermes doesn't. it has thre…
Hermes agent's three-tier memory system combines tiny always-present markdown files, full-text SQLite+FTS5 session search, and pluggable external providers to give AI agents persistent, curated memory that composes on every turn.
Agent memory is not just RAG over user facts
The article argues that simple RAG-based agent memory systems fail in production due to issues like stale preferences, missed keywords, and prompt injection, and advocates for a layered memory architecture with active selection, deterministic fallback, governance, and testing.