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Query and analyze Garmin Connect health and activity data via MCP.
Copy the install command and let the AI configure it · recommended for beginners
No copy-paste install info for "Garmin MCP" yet — see the docs or source repo.
Use Garmin MCP to query my last 7 days of steps, sleep, and stress data, summarize it in Chinese, and point out notable fluctuations.
A 7-day health summary with trends and anomaly highlights.
Use Garmin MCP to query my recent activities, analyze them by activity type and time, and provide brief conclusions.
An activity analysis with category breakdowns and concise takeaways.
Based on the data available through Garmin MCP, propose a visualization plan for steps, sleep, and stress changes.
A charting and layout plan suitable for those health metrics.
Useful for anyone who wants to review steps, sleep, and stress regularly. It helps summarize Garmin Connect health data and spot trends.
Useful for people who need to review workout logs, such as athletes or coaches. It can analyze activities by type and provide concise insights.
Useful for data analysts or product managers turning health metrics into charts. It provides a basis for querying, analysis, and visualization.
It is an MCP server that exposes Garmin Connect health and activity data. It supports querying, analysis, and visualization through tools.
The description mentions steps, sleep, stress, activities, and similar Garmin Connect data. For the full scope, see the source repository.
The provided information only says it is an MCP server for Garmin Connect data and does not include setup, auth, or runtime details. See the source repository.
Query Garmin health and fitness data in natural language.
Access and analyze Garmin Connect sleep, health, activity, and training data.
Access Garmin health, activity, LiveTrack, and training readiness data in AI workflows.
Retrieve Garmin Connect health, activity, and device data using natural language.
Access Garmin Connect data for activity, health, training, and device analysis.
Access Garmin wellness metrics, summaries, and historical health trends through MCP tools.