Gevety MCP

**Quick judgment** This is a high-functionality MCP skill for users who already use Gevety. It exposes a broad, well-structured health data surface (biomarkers, healthspan scores, wearables, protocols, actions) with clear workflows for agents. It’s excellent for longitudinal health tracking and prioritized "what to work on" discussions, but must be paired with strong medical-disclaimer behavior from the agent. **Key strengths** - Very comprehensive endpoint set: labs, healthspan scores, biological age, supplements, wearables, workouts, protocols, upcoming tests, and personalized content recommendations. - Biomarker- and score-centric design (canonical names, optimal ranges, axis scores, healthspan and opportunity scores) that makes structured reasoning and prioritization easier for an AI. - Good developer ergonomics: clearly defined endpoints, parameters, response fields, and example workflows aligned with natural user questions. **Main risks / limitations** - **Medical interpretation risk**: Exposes biomarker status labels, biological age, and estimated “years of healthy life gained.” If an agent uses this to provide diagnosis or treatment recommendations, users could misinterpret it as clinical advice. Agents should be constrained to educational, high-level guidance and consistently encourage consultation with healthcare professionals for decisions. - **Privacy and security sensitivity**: Handles highly sensitive health and lab data via Bearer tokens. Misconfigured environment variables, logs, or sharing could leak personally identifiable health information. Operators must secure tokens, avoid logging raw responses where possible, and respect user consent. - **Gevety dependency & data completeness**: Only valuable if users have a Gevety account, uploaded lab reports, and configured the MCP token correctly. Insights can be incomplete or skewed if the user’s testing is sparse or outdated. - **External API reliability**: All functionality depends on the Gevety API’s uptime and stability; outages or breaking changes would directly affect the skill. **Recommended scenarios** - Building a **personal health dashboard or coach** inside OpenClaw that summarizes healthspan, trends, and key opportunities for optimization. - Supporting **quantified-self / longevity / performance enthusiasts** who use Gevety and want high-level interpretation and prioritization of their labs and behavior data (without crossing into medical diagnosis). - Enabling **adherence and routine-support agents** that surface today’s actions, supplements, and key workouts, and monitor completion and trends over time.