$ loading_
Compute your fitness metrics against your own 28-day baseline to surface meaningful trends.
Copy the install command and let the AI configure it · recommended for beginners
Please install the "TrainBud" MCP server from askskill: Run: claude mcp add 'io-github-zsadigzade-trainbud' -- npx -y trainbud
Users can quickly compare current fitness data with their 28-day baseline at week end, producing a quick read on improvement or decline to guide the next week.
When users want to monitor whether their training is drifting, they can watch deviations from the 28-day baseline and spot moments that need adjustment.
TrainBud is an MCP tool focused on personal fitness data analysis. Its core capability is computing findings against your own 28-day baseline.
The provided information only states it analyzes your personal fitness data with 28-day baselines. For setup, credentials, or runtime requirements, please refer to the source repository.
It is not just for storing values; it performs baseline-based calculations and highlights computed findings. For fuller differences, see the source repository.
Query TrainingPeaks workouts, fitness metrics, and power PRs in natural language.
Connect TrainingPeaks to AI assistants for workout planning, tracking, and calendar control.
Use natural language to query workouts, build intervals, and track fitness trends.
Connect Whoop data to Claude for recovery, sleep, and training insights.
Calculate body metrics and track measurement trends over time.
Access and analyze Fitbit health data through natural-language AI interactions.