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 TheUncharted · MCP Server · ★ 89
Last updated: · Indexed by AgentSkillsHub · Auto-synced every 8h
🔒 Is zapcode safe to install? View the security audit →
Zapcode Run AI-generated code. Safely. Instantly. A minimal, secure TypeScript interpreter written in Rust for use by AI agents Experimental — Zapcode is under active development. APIs may change. Why agents should write code AI agents are more capable when they write code instead of chaining tool calls. Code gives agents loops, conditionals, variables, and composition — things that tool chains simulate poorly. Codemode from Cloudflare [Programma
| Stars | 89 |
| Forks | 6 |
| Language | Rust |
| Category | MCP Server |
| License | MIT |
| Quality Score | 67.256496162011/100 |
| Open Issues | 6 |
| Last Updated | 2026-08-29 |
| Created | 2026-03-11 |
| Platforms | mcp, rust |
| Est. Tokens | ~27k |
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zapcode is TypeScript interpreter for AI agents. Written in Rust. 2µs cold start. Sandboxed. Alternative to MCP tool calling.. It is categorized as a MCP Server with 89 GitHub stars.
zapcode is primarily written in Rust. It covers topics such as agent, ai, ai-agents.
You can find installation instructions and usage details in the zapcode GitHub repository at github.com/TheUncharted/zapcode. The project has 89 stars and 6 forks, indicating an active community.
zapcode is released under the MIT license, making it free to use and modify according to the license terms.
The top alternatives to zapcode on Agent Skills Hub include agnix, claudex, vscode-mcp. 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.
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