by mage0535 · Codex Skill · ★ 165
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Memory Sidecar v3.1.1 A production memory system for any AI agent. Keep knowledge across sessions, without touching agent internals. 中文文档 | Architecture What This Is AI agents forget things. Every new session starts blank. Memory Sidecar runs alongside your agent — Hermes, Claude Code, Cursor, Codex, whatever — and gives it a real memory. It saves important conversations, builds long-term knowledge, and feeds relevant context back when needed. It doesn't patch the agent. It's a sidecar: separate process, shared data directory. Three things it actually does: Archives sessions to permanent knowledge — conversations aren't lost when you restart Recalls what matters — layered retrieval: recent context → semantic search → knowledge graph Tracks important topics — people, projects, recurring problems get their own "dossier" ##
| Stars | 165 |
| Forks | 9 |
| Language | Python |
| Category | Codex Skill |
| License | MIT |
| Quality Score | 71.6496885313986/100 |
| Open Issues | 1 |
| Last Updated | 2026-06-29 |
| Created | 2026-04-25 |
| Platforms | claude-code, cli, codex, python |
| Est. Tokens | ~16k |
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hermes-memory-installer is 🧠 Production-grade memory sidecar for AI agents — gbrain + Hindsight + 3-tier recall. Agent-agnostic, battle-tested. | 生产级外挂记忆系统，兼容Hermes/Claude/Cursor等任意AI智能体. It is categorized as a Codex Skill with 165 GitHub stars.
hermes-memory-installer is primarily written in Python. It covers topics such as agent-memory, ai-agent, claude-code.
You can find installation instructions and usage details in the hermes-memory-installer GitHub repository at github.com/mage0535/hermes-memory-installer. The project has 165 stars and 9 forks, indicating an active community.
hermes-memory-installer is released under the MIT license, making it free to use and modify according to the license terms.
The top alternatives to hermes-memory-installer on Agent Skills Hub include omega-memory, Ori-Mnemos, Overture. Each offers a different approach to the same problem space — compare them side-by-side by stars, quality score, and community activity.