Agentmemory

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Summary

Agentmemory offers persistent memory for AI models such as Codex, Hermes, OpenClaw, and Claude, allowing them to maintain long-term context across interactions.

<p> #1 Persistent memory for Codex, Hermes, OpenClaw, Claude ++ </p> <p> <a href="https://www.producthunt.com/products/agent-memory-dev?utm_campaign=producthunt-atom-posts-feed&amp;utm_medium=rss-feed&amp;utm_source=producthunt-atom-posts-feed">Discussion</a> | <a href="https://www.producthunt.com/r/p/1144164?app_id=339">Link</a> </p>
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rohitg00/agentmemory

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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.

An open source natural temporal memory for claude code, hermes and openclaw agent

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agentmemory is an open-source library that provides natural temporal memory for AI agents like Claude Code, Hermes, and OpenClaw. It uses a three-tier architecture with hybrid retrieval (BM25, vector, knowledge graph) and Ebbinghaus decay, achieving ~92% fewer tokens and 200x more tool calls before context limits.

Agent Memory: An Anatomy

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An exploration of the components and design decisions behind agent memory libraries, clarifying the gap between cognitive science terminology and engineering implementation.