Flagged: reads agent memory, sudo usage. Scanned against the SlowMist agent-security taxonomy, refreshed every 8 hours. Full audit →
by 24kchengYe · MCP Server · ★ 611
Last updated: · Indexed by AgentSkillsHub · Auto-synced every 8h
🔒 Is MemoMind safe to install? View the security audit →
🧠 MemoMind Give your AI agent a brain that remembers. A fully local, GPU-accelerated memory system for AI coding agents. Start building your digital twin's memory today — portable, evolving, and ready to migrate when a better system comes along. -blue) English | 中文 Two Kinds of AI Memory AI memory has two audiences — the machine and the human. Most tools only address one: "Why does it keep forgetting my coding style?"
| Stars | 611 |
| Forks | 6 |
| Language | Python |
| Category | MCP Server |
| Quality Score | 63.9217335989456/100 |
| Open Issues | 4 |
| Last Updated | 2026-08-07 |
| Created | 2026-03-15 |
| Platforms | claude-code, mcp, python |
| Est. Tokens | ~21k |
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MemoMind is Give your AI agent a brain that remembers. Local memory system for Claude Code — 100% private, GPU-accelerated, zero cloud dependency.. It is categorized as a MCP Server with 611 GitHub stars.
MemoMind is primarily written in Python. It covers topics such as agent-memory, ai, claude-code.
You can find installation instructions and usage details in the MemoMind GitHub repository at github.com/24kchengYe/MemoMind. The project has 611 stars and 6 forks, indicating an active community.
The top alternatives to MemoMind on Agent Skills Hub include Ori-Mnemos, omega-memory, claude-historian-mcp. Each offers a different approach to the same problem space — compare them side-by-side by stars, quality score, and community activity.
Grades come from a rule-based scan built on the SlowMist agent-security taxonomy, covering 11 red-flag categories including credential harvesting, data exfiltration, and curl | sh installers. It is a first-layer scan, not a manual audit — we say so rather than overstate it.
The scale of the problem is documented independently: Liu et al. (2026), in a study of 31,132 agent skills, report that 26.1% contain security vulnerabilities. Our own full-catalog census is published as a citable open dataset.
Sources & who's responsible: