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 chu2bard · MCP Server · ★ 95
Last updated: · Indexed by AgentSkillsHub · Auto-synced every 8h
🔒 Is pinion-os safe to install? View the security audit →
pinion-os Client SDK, Claude Code plugin, and skill server framework for Pinion. Handles x402 micropayments on Base so your code (or your agent) can call on-chain skills without thinking about payments. Architecture Three layers: your code talks to the SDK, the SDK handles x402 payment signing, the skill server verifies payment through a facilitator and returns data. x402 Payment Flow Client
| Stars | 95 |
| Forks | 6 |
| Language | TypeScript |
| Category | MCP Server |
| License | MIT |
| Quality Score | 70.2374420721436/100 |
| Open Issues | 1 |
| Last Updated | 2026-02-23 |
| Created | 2026-02-11 |
| Platforms | claude-code, cli, mcp, node |
| Est. Tokens | ~16k |
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pinion-os is Client SDK, Claude plugin and skill framework for the Pinion protocol. x402 micropayments on Base.. It is categorized as a MCP Server with 95 GitHub stars.
pinion-os is primarily written in TypeScript. It covers topics such as agents, base, claude.
You can find installation instructions and usage details in the pinion-os GitHub repository at github.com/chu2bard/pinion-os. The project has 95 stars and 6 forks, indicating an active community.
pinion-os is released under the MIT license, making it free to use and modify according to the license terms.
The top alternatives to pinion-os on Agent Skills Hub include payram-mcp, agenti, awesome-molt-ecosystem. 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: