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 CodeAbra · MCP Server · ★ 119
Last updated: · Indexed by AgentSkillsHub · Auto-synced every 8h
🔒 Is iai-mcp safe to install? View the security audit →
The best-benchmarked open-source memory system for AI coding assistants. Every claim ships with the harness that proves it. Run the benchmarks yourself. = 99%" iai-mcp Independent Autistic Intelligence — a local memory layer for Claude (and other MCP-compatible assistants). Table of contents What it is Quick start Usage How it works Benchmarks Configuration Doctor [Notes
| Stars | 119 |
| Forks | 13 |
| Language | Python |
| Category | MCP Server |
| License | MIT |
| Quality Score | 75.6487269162216/100 |
| Last Updated | 2026-05-15 |
| Created | 2026-05-06 |
| Platforms | claude-code, mcp, python |
| Est. Tokens | ~154k |
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iai-mcp is The best-benchmarked open-source memory system for AI coding assistants. It is categorized as a MCP Server with 119 GitHub stars.
iai-mcp is primarily written in Python. It covers topics such as ai-agents, ai-memory, claude.
You can find installation instructions and usage details in the iai-mcp GitHub repository at github.com/CodeAbra/iai-mcp. The project has 119 stars and 13 forks, indicating an active community.
iai-mcp is released under the MIT license, making it free to use and modify according to the license terms.
The top alternatives to iai-mcp on Agent Skills Hub include omega-memory, mychatarchive, claude-mem-lite. 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: