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 HCF-STUDIOS · MCP Server · ★ 85
Last updated: · Indexed by AgentSkillsHub · Auto-synced every 8h
🔒 Is openhermit safe to install? View the security audit →
OpenHermit Agents, but operable. Open-source platform for deploying fleets of AI agents as production services — durable state, sandboxed execution, managed at scale, and the channels you already use. Built by Amiko — an agent-agnostic infrastructure platform for the AI era. Website · Why OpenHermit · Docs · npm Why OpenHermit Most CLI-based agents (Claude Code, OpenClaw, Hermes, …) keep their state in files: memories as markdown, sessions as JSONL, skills as folders, secrets as dotfiles. That's perfect for one human at one machine — but it falls apart the moment you stop being one human. Running an internal agent platform for your team, a SaaS where every customer
| Stars | 85 |
| Forks | 20 |
| Language | TypeScript |
| Category | MCP Server |
| License | MIT |
| Quality Score | 75.197787216902/100 |
| Last Updated | 2026-09-30 |
| Created | 2026-03-07 |
| Platforms | mcp, node |
| Est. Tokens | ~17k |
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openhermit is OpenHermit is the open-source platform for deploying fleets of AI agents as production services — durable state, sandboxed execution, managed at scale, and the channels you already use.. It is categorized as a MCP Server with 85 GitHub stars.
openhermit is primarily written in TypeScript. It covers topics such as agent-framework, agent-infrastructure, agent-orchestration.
You can find installation instructions and usage details in the openhermit GitHub repository at github.com/HCF-STUDIOS/openhermit. The project has 85 stars and 20 forks, indicating an active community.
openhermit is released under the MIT license, making it free to use and modify according to the license terms.
The top alternatives to openhermit on Agent Skills Hub include instar, markus, Deft. 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: