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 MaxGfeller · MCP Server · ★ 594
Last updated: · Indexed by AgentSkillsHub · Auto-synced every 8h
🔒 Is open-harness safe to install? View the security audit →
OpenHarness Build capable, general-purpose AI agents in code. Based on Vercel's AI SDK, inspired by Claude Code, Codex, and similar agent harnesses. Documentation Packages Quick Start Multi-Turn with Sessions typescript import { Session } from "@openharness/core"; const session = new Session({ agent, contextWindow: 128000 }); for await (const event of session.send("List all TypeScript files")) { if (event.type === "text.delta") process.stdout.write(event.text); } // Session remembers the conversati
| Stars | 594 |
| Forks | 98 |
| Language | TypeScript |
| Category | MCP Server |
| License | MIT |
| Quality Score | 69.6243396444595/100 |
| Open Issues | 2 |
| Last Updated | 2026-07-17 |
| Created | 2026-02-23 |
| Platforms | mcp, node |
| Est. Tokens | ~14k |
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open-harness is A code-first, composable SDK to build powerful AI agents. It is categorized as a MCP Server with 594 GitHub stars.
open-harness is primarily written in TypeScript. It covers topics such as agents, agentskills, ai.
You can find installation instructions and usage details in the open-harness GitHub repository at github.com/MaxGfeller/open-harness. The project has 594 stars and 98 forks, indicating an active community.
open-harness is released under the MIT license, making it free to use and modify according to the license terms.
The top alternatives to open-harness on Agent Skills Hub include py-gpt, mcp, pg-aiguide. 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: