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 jimmykane · MCP Server · ★ 234
Last updated: · Indexed by AgentSkillsHub · Auto-synced every 8h
🔒 Is quantified-self safe to install? View the security audit →
Quantified Self Quantified Self is an open-source platform for collecting, analyzing, and visualizing fitness and health data. It combines activity imports and connected fitness services with dashboards, training insights, route tools, sleep trends, and detailed workout analysis. Try the hosted app at quantified-self.io. Highlights Import activity files in FIT, GPX, TCX, JSON, and SML formats. Connect Garmin, Suunto, COROS, and Wahoo for supported activity, route, sleep, and history workflows. Explore configurable dashboards, training readiness, load trends, power curves, intensity zones, laps, and durability metrics. View activities and saved routes with Mapbox-powered maps and route tools. Compare recordings from multiple devices, share selected activities, and export your data. Ask grounded fitness-data questions through the built-in Assistant. Technology and repository layout The main repository areas are:
| Stars | 234 |
| Forks | 32 |
| Language | TypeScript |
| Category | MCP Server |
| Quality Score | 66.7953153539068/100 |
| Open Issues | 54 |
| Last Updated | 2026-10-12 |
| Created | 2017-06-23 |
| Platforms | mcp, node |
| Est. Tokens | ~17k |
These tools work well together with quantified-self for enhanced workflows:
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quantified-self is Analyze your data from Garmin, Suunto, Coros to one centralized app. It is categorized as a MCP Server with 234 GitHub stars.
quantified-self is primarily written in TypeScript. It covers topics such as coros, fit-file, fitness-dashboard.
You can find installation instructions and usage details in the quantified-self GitHub repository at github.com/jimmykane/quantified-self. The project has 234 stars and 32 forks, indicating an active community.
The top alternatives to quantified-self on Agent Skills Hub include intervals-icu-mcp, garmin-connect-mcp, whoop-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.
Sources & who's responsible: