cortex-mem: The production-ready cognitive foundation for autonomous systems such as Embodied-AI and OpenClaw

by sopaco · MCP Server · ★ 302

Last updated: · Indexed by AgentSkillsHub · Auto-synced every 8h

How to install cortex-mem

cargo install --path cortex-mem-cli
cargo install --path cortex-mem-service

Taken from the project's README on GitHub. Check the security audit before running it.

Security audit verdict: SAFE · quality 69/100

None of the 42 rules matched — no credential harvesting, no data exfiltration, no curl-pipe-shell installer. Scanned against 42 published rules built on the SlowMist agent-security taxonomy, refreshed every 8 hours. Full audit →

The quality score combines nine heuristic checks of the repo and its README: completeness, clarity, specificity, examples, structure, agent readiness, step-by-step content, instruction quality and security notes. It rates how well the project explains itself to an agent, not the code.

clawhubembodied-agentembodied-cognitionopenclawskills

Quick Facts

Stars302
Forks23
LanguageRust
CategoryMCP Server
LicenseMIT
Quality Score69/100
Open Issues1
Last Updated2026-07-22
Created2025-11-30
Platformscli, mcp, rust
Est. Tokens~29k

About cortex-mem

Cortex Memory English | 中文 🧠 The AI-native memory framework for building intelligent, context-aware applications 🧠 Built with Rust, Cortex Memory is a high-performance, persistent, and intelligent long-term memory system that gives your AI agents the ability to remember, learn, and personalize interactions across sessions. <img alt="MIT" src="https://

Compatible Skills

These tools work well together with cortex-mem for enhanced workflows:

  • rai — semantic(0.41)+complementary+rare_topics+similar_pop (49%)

cortex-mem alternative? Top 6 similar tools

Looking for a cortex-mem alternative? If you're comparing cortex-mem with other mcp server tools, these 6 projects are the closest alternatives on Agent Skills Hub — ranked by topic overlap, star count, and community traction.

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How this security grade is produced

Grades come from a rule-based scan built on the SlowMist agent-security taxonomy: 42 published rules, covering credential harvesting, data exfiltration, curl | sh installers and more. 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:

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