by NeoLi00 · Claude Skill · ★ 131
Last updated: · Indexed by AgentSkillsHub · Auto-synced every 8h
English · 中文 · Architecture memX turns completed work into structured, searchable, self-maintained memory, then injects only the evidence an agent needs for the current query. It connects natively to Codex, Claude Code, and OpenClaw, and reaches any MCP-compatible client through the same local memory layer. Benchmarks Suite Scope R@3 success rate LongMemEval-S Long-context memory retrieval 94.2% Real engineering cases 30 cases, each with 20+ turns 100% Architecture Agent support Codex native hooks, MCP hidden by default <img src=
| Stars | 131 |
| Forks | 3 |
| Language | TypeScript |
| Category | Claude Skill |
| License | MIT |
| Quality Score | 65.1396296722317/100 |
| Open Issues | 2 |
| Last Updated | 2026-05-26 |
| Created | 2026-05-08 |
| Platforms | claude-code, codex, node |
| Est. Tokens | ~228k |
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memX is memX: self-learning, self-maintaining memory plugin for AI agents; native support for claude code, codex, and openclaw. It is categorized as a Claude Skill with 131 GitHub stars.
memX is primarily written in TypeScript. It covers topics such as agent, agent-memory, claude-code.
You can find installation instructions and usage details in the memX GitHub repository at github.com/NeoLi00/memX. The project has 131 stars and 3 forks, indicating an active community.
memX is released under the MIT license, making it free to use and modify according to the license terms.
The top alternatives to memX on Agent Skills Hub include memorix, hipocampus, remnic. Each offers a different approach to the same problem space — compare them side-by-side by stars, quality score, and community activity.