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 serradura · MCP Server · ★ 154
Last updated: · Indexed by AgentSkillsHub · Auto-synced every 8h
🔒 Is okf safe to install? View the security audit →
<img src="https://github.com/serradura/okf/act
| Stars | 154 |
| Forks | 11 |
| Language | Ruby |
| Category | MCP Server |
| License | Apache-2.0 |
| Quality Score | 64.3048956159985/100 |
| Open Issues | 5 |
| Last Updated | 2026-09-06 |
| Created | 2026-07-11 |
| Platforms | claude-code, cli, docker, mcp, ruby |
| Est. Tokens | ~18k |
These tools work well together with okf for enhanced workflows:
Looking for a okf alternative? If you're comparing okf 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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okf is OKF (Open Knowledge Format): Durable, structured memory for AI agents. Author, validate, consume, and maintain portable knowledge bundles through an ecosystem of Skills, MCP, an interactive graph, TUI. It is categorized as a MCP Server with 154 GitHub stars.
okf is primarily written in Ruby. It covers topics such as agent-skills, ai-agents, claude-code.
You can find installation instructions and usage details in the okf GitHub repository at github.com/serradura/okf. The project has 154 stars and 11 forks, indicating an active community.
okf is released under the Apache-2.0 license, making it free to use and modify according to the license terms.
The top alternatives to okf on Agent Skills Hub include okf-skills, Awesome-OKF, okf-agent-memory. 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: