by shashankswe2020-ux · MCP Server · ★ 174
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git clone https://github.com/shashankswe2020-ux/whoop-mcp.gitTaken from the project's README on GitHub. Check the security audit before running it.
None of the 42 rules matched — no credential harvesting, no data exfiltration, no curl-pipe-shell installer. Scanned against 42 published rules built on the SlowMist agent-security taxonomy, refreshed every 8 hours. Full audit →
The quality score combines nine heuristic checks of the repo and its README: completeness, clarity, specificity, examples, structure, agent readiness, step-by-step content, instruction quality and security notes. It rates how well the project explains itself to an agent, not the code.
| Stars | 174 |
| Forks | 71 |
| Language | TypeScript |
| Category | MCP Server |
| License | MIT |
| Quality Score | 79/100 |
| Open Issues | 26 |
| Last Updated | 2026-10-25 |
| Created | 2026-04-10 |
| Platforms | claude-code, codex, mcp, node |
| Est. Tokens | ~17k |
whoop-ai-mcp An MCP (Model Context Protocol) server that connects AI assistants like Claude to your WHOOP health and fitness data. Ask questions about your recovery, sleep, workouts, and more — all through natural conversation. 📦 Published on the MCP Registry as — discoverable by any MCP-compatible client.
These tools work well together with whoop-mcp for enhanced workflows:
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Manage your Hevy workouts, routines, folders, and exercise templates. Create and update sessions faster, organ
Notion MCP server with token auth: connect Claude Code, Claude Desktop, Cursor, VS Code and Codex to Notion pa
Model Context Protocol server giving Claude (or any MCP client) full read + write access to your Whoop fitness
Model Context Protocol server giving Claude (or any MCP client) full read + write access to your Whoop fitness
Model Context Protocol server giving Claude (or any MCP client) full read + write access to your Whoop fitness
Clean, LLM-optimized Reddit MCP server. Browse posts, search content, analyze users. No fluff, just Reddit dat
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Grades come from a rule-based scan built on the SlowMist agent-security taxonomy: 42 published rules, covering credential harvesting, data exfiltration, curl | sh installers and more. 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: