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 kentcdodds · MCP Server · ★ 770
Last updated: · Indexed by AgentSkillsHub · Auto-synced every 8h
🔒 Is kody safe to install? View the security audit →
Your assistant's home — the memory, keys, code, and automations your AI agent keeps, portable across every MCP host. Built on Cloudflare Workers. Kody is your assistant's home—the memory, keys, code, and automations your AI agent keeps, portable across every MCP host. Built on Cloudflare Workers and the Model Context Protocol (MCP), it ships a Remix UI, Worker-based request routing, package runtime plumbing, and OAuth-protected MCP endpoints. The project favors a compact MCP surface with powerful and Code Mode flows over a large static
| Stars | 770 |
| Forks | 72 |
| Language | TypeScript |
| Category | MCP Server |
| Quality Score | 62.4904431562059/100 |
| Open Issues | 67 |
| Last Updated | 2026-10-12 |
| Created | 2026-03-18 |
| Platforms | mcp, node |
| Est. Tokens | ~15k |
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kody is 🐨 Your agents' cloud — the memory, keys, code, and automations your AI agent keeps, portable across every MCP host.. It is categorized as a MCP Server with 770 GitHub stars.
kody is primarily written in TypeScript. It covers topics such as agents, ai-assistant, cloudflare-workers.
You can find installation instructions and usage details in the kody GitHub repository at github.com/kentcdodds/kody. The project has 770 stars and 72 forks, indicating an active community.
The top alternatives to kody on Agent Skills Hub include Sentient, py-gpt, agentor. 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: