No red flags found in any of the 11 categories — no credential harvesting, no data exfiltration, no curl-pipe-shell installer. Scanned against the SlowMist agent-security taxonomy, refreshed every 8 hours. Full audit →
by rtk-ai · MCP Server · ★ 580
Last updated: · Indexed by AgentSkillsHub · Auto-synced every 8h
🔒 Is icm safe to install? View the security audit →
English 한국어 ICM Permanent memory for AI agents. Single binary, zero dependencies, MCP native. ICM gives your AI agent a real memory — not a note-taking tool, not a context manager, a memory. ICM (Infinite Context Memory) ┌──────────────────────┬─────────────────────────┐ │ MEMORIES (Topics) │ MEMOIRS (Knowledge) │ │ │ │ │ Episodic, temporal │ Permanent, structured │ │ │ │
| Stars | 580 |
| Forks | 61 |
| Language | Rust |
| Category | MCP Server |
| License | Apache-2.0 |
| Quality Score | 66.4329102601869/100 |
| Open Issues | 4 |
| Last Updated | 2026-10-08 |
| Created | 2026-02-02 |
| Platforms | claude-code, mcp, rust |
| Est. Tokens | ~27k |
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icm is Permanent memory for AI agents. Single binary, zero dependencies, MCP native.. It is categorized as a MCP Server with 580 GitHub stars.
icm is primarily written in Rust. It covers topics such as ai-agents, claude-code, experimental.
You can find installation instructions and usage details in the icm GitHub repository at github.com/rtk-ai/icm. The project has 580 stars and 61 forks, indicating an active community.
icm is released under the Apache-2.0 license, making it free to use and modify according to the license terms.
The top alternatives to icm on Agent Skills Hub include ai-devkit, forgetful, cocoindex-code. 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: