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 strands-agents · MCP Server · ★ 8.6k
Last updated: · Indexed by AgentSkillsHub · Auto-synced every 8h
🔒 Is harness-sdk safe to install? View the security audit →
Strands Agents A model-driven approach to building AI agents in just a few lines of code. <img alt="Strands Discord" src="https://img.shields.io/badge/Discord-Strands-5865F2?logo=discord&logoColor=
| Stars | 8,632 |
| Forks | 1,315 |
| Language | Python |
| Category | MCP Server |
| License | Apache-2.0 |
| Quality Score | 70.8007153303547/100 |
| Open Issues | 934 |
| Last Updated | 2026-10-02 |
| Created | 2025-05-14 |
| Platforms | mcp, python |
| Est. Tokens | ~16k |
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harness-sdk is Build an agent harness and control it end-to-end. Open-source SDK for production AI agents in Python & TypeScript - any model, any cloud.. It is categorized as a MCP Server with 8.6k GitHub stars.
harness-sdk is primarily written in Python. It covers topics such as agent-framework, agentic, agentic-ai.
You can find installation instructions and usage details in the harness-sdk GitHub repository at github.com/strands-agents/harness-sdk. The project has 8.6k stars and 1315 forks, indicating an active community.
harness-sdk is released under the Apache-2.0 license, making it free to use and modify according to the license terms.
The top alternatives to harness-sdk on Agent Skills Hub include ruby_llm, agent-squad, gptme. 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: