Freddy MCP Server: Give Your OpenClaw Agent Read Access to Personal Health Data

Freddy is a personal health data server that exposes your health and performance data as an MCP server. It just went live as an iOS and Android app, meaning your OpenClaw agents can now pull real sleep, recovery, and training load data instead of relying on generic advice.
What It Connects
- Apple Health or Health Connect (from phone)
- Oura, Polar, WHOOP, Garmin, Withings, Suunto
- Intervals.icu, Hevy
You connect your sources once, and the agent gets access to all of it inside whatever workflow you're running.
Auth for Headless Agents
The recommended auth flow for headless agents is the device flow. This gives the agent its own scoped access without you having to paste a URL around.
Weekend Project Idea
Build a morning agent that looks at last night's sleep and recent training load, then writes you a two-line note on whether to push or back off today. It's a small task but reads real numbers instead of guessing.
You can find Freddy at https://freddy.coach/.
Privacy
Data is encrypted, not sold, and the developer is not looking to profit off your stats. If you don't trust third-party solutions, just don't use it.
📖 Read the full source: r/openclaw
👀 See Also

Testing MiniMax M2.7 via API on Three Real ML and Coding Workflows
A developer benchmarks MiniMax M2.7 against Claude Opus 4.7 on three real tasks: refactoring a PyTorch project, drafting Obsidian notes, and more. Key findings and setup included.

WeAreHere Browser Extension and MCP Tools Scan Website Privacy Practices
Two open-source tools—barebrowse and wearehere—scan websites for trackers, fingerprinting, and data broker connections. The wearehere browser extension shows real-time privacy scores (0-100) as you browse, while MCP servers enable AI assistants to assess any site on command.

Antibody System: Out-of-Band Watchdog for OpenClaw Agents
The Antibody System is an open-source watchdog that runs on a separate machine and monitors OpenClaw agents over SSH, implementing tiered responses from detection to service recovery. It's designed to survive failures that take down the primary agent.

Parallel Claude Chat Architecture for Next.js Development
A developer created a system to run multiple Claude AI chats simultaneously on the same Next.js codebase using a shared database table and polling agent, achieving 87% build success rate with zero merge conflicts in one session.