GC-MCP
Enables AI assistants to access and query Garmin Connect health and fitness data, including sleep, HRV, training load, and activities, with an optional coaching plugin for personalized training plans.
README
GC-MCP
Disclaimer: GC-MCP is an independent, community-made project. It is not affiliated with, endorsed by, or created by Garmin Ltd. Garmin and Garmin Connect are trademarks of Garmin Ltd.
A Model Context Protocol server that connects AI assistants to your Garmin Connect account. Ask about your health metrics, training load, activities, and trends — directly from conversation.
Installation (Required)
The MCP server must be installed before anything else — including the gc-coach plugin — will work.
Run this in your terminal:
npx @ace4seven/gc-mcp setup
The wizard will:
- Ask for your Garmin Connect email and password
- Save authentication tokens to
~/.gc-mcp/on your machine - Detect all installed AI clients and configure each one automatically
Then restart any configured AI client — you're done.
Supported clients: Claude Desktop, Cursor, Windsurf, VS Code, Zed, Claude Code CLI
Re-authenticate when tokens expire
npx @ace4seven/gc-mcp login
What You Can Ask
Once configured, ask your AI assistant things like:
- "How was my sleep last week?"
- "Show me my HRV trend for the past 30 days"
- "What was my resting heart rate on Monday?"
- "List my last 10 runs with pace and distance"
gc-coach Plugin (Optional)
An optional Claude Code plugin that turns Claude into a personalised fitness coach with persistent memory, daily readiness decisions, weekly planning, and automatic red-flag detection.
Requires the MCP server to be installed first (see Installation above).
Install
/plugin marketplace add ace4seven/GC-MCP
/plugin install gc-coach@gc-mcp-marketplace
Slash Commands
| Command | Description |
|---|---|
/coach-onboard |
First-run setup. Infers an athlete profile from 90 days of Garmin data, confirms with 5 questions, and writes a conservative starter training block. |
/coach-today |
Morning decision. Reads today's readiness, HRV, sleep, and body battery; cross-checks the weekly plan; outputs one prescription + fallback. |
/coach-checkin |
Daily log. Asks energy, soreness, sleep, session done, and RPE in a single prompt. Detects patterns and opens flags automatically. |
/coach-plan-week |
Builds a periodised Monday–Sunday week with session rationale. Saves to weekly-plan.md. |
/coach-review |
Weekly retrospective. Reports adherence, load trajectory, opened/closed flags, and exactly one thing to change next week. |
State Files
All coaching state is stored locally in ~/.gc-mcp/coach/ — no cloud sync.
~/.gc-mcp/coach/
├── profile.json # Athlete profile (modalities, baselines, voice prefs)
├── goals.md # Goals in the athlete's own words
├── current-block.md # Active training block description
├── weekly-plan.md # Current week's session plan
├── flags.md # Active and closed red flags
├── daily-log/
│ └── YYYY-MM-DD.md # Per-day check-in
└── history/
└── YYYY-Wnn-review.md # Weekly retrospective archive
Available Tools
Daily Health
| Tool | Description | Parameters |
|---|---|---|
get_daily_summary |
Steps, calories, floors, active minutes, and distance | start_date?, end_date? |
get_heart_rate |
Resting heart rate and intraday HR curve | start_date?, end_date? |
get_stress |
Average/max stress levels and timeline | start_date?, end_date? |
get_body_battery |
Energy charge/drain curve | start_date?, end_date? |
get_sleep_data |
Deep/light/REM/awake breakdown, sleep score, SpO2 | start_date?, end_date? |
get_hrv_status |
Nightly HRV score and 5-night rolling average | start_date?, end_date? |
get_respiration |
Breathing rate throughout the day | start_date?, end_date? |
get_spo2 |
Blood oxygen readings | start_date?, end_date? |
get_hydration |
Water intake log | start_date?, end_date? |
Fitness & Performance
| Tool | Description | Parameters |
|---|---|---|
get_training_status |
Fitness level: peaking, productive, maintaining, etc. | start_date?, end_date? |
get_training_readiness |
Readiness score with contributing factors | start_date?, end_date? |
get_training_load |
Acute vs chronic load balance (ACWR) over 28 days | date? |
get_vo2max |
VO2 max estimate for running and cycling | date? |
get_race_predictor |
Predicted 5K, 10K, half marathon, marathon times | — |
get_personal_records |
All-time personal records across all sport types | — |
Activities
| Tool | Description | Parameters |
|---|---|---|
list_activities |
List activities with summary stats | limit? (1–100), sport_type?, start_date?, end_date? |
get_activity |
Full details for a single activity | activity_id (required) |
get_activity_splits |
Lap/split data for a single activity | activity_id (required) |
Body Composition
| Tool | Description | Parameters |
|---|---|---|
get_body_composition |
BMI, body fat percentage, and muscle mass | start_date?, end_date? |
get_weight_history |
Weight measurements over a date range | start_date (required), end_date (required) |
Gear & Profile
| Tool | Description | Parameters |
|---|---|---|
list_gear |
Shoes, bikes, and other gear with usage mileage | — |
get_user_profile |
Display name, date of birth, weight, preferred units | — |
Date Range Support
Most tools accept optional start_date and end_date (YYYY-MM-DD format, max 90-day range). Omit both for today's data.
Troubleshooting
"Missing credentials" error — Run npx @ace4seven/gc-mcp login to authenticate.
Tools not appearing — Re-run npx @ace4seven/gc-mcp setup, then fully restart your AI client.
Authentication expired — Run npx @ace4seven/gc-mcp login again and restart your AI client.
"Tool result is too large" — Use a shorter date range, or ask about a specific metric rather than fetching everything at once.
Privacy
- Your Garmin credentials are used only during login and are never stored.
- OAuth tokens are stored locally in
~/.gc-mcp/on your machine. - All Garmin API requests are made directly from your machine — no data passes through any intermediary server.
Development
Project Structure
src/
cli.ts # Binary entry point — setup/login/server dispatch
index.ts # MCP server: startServer()
auth.ts # Token I/O: login(), loadClient(), isLoggedIn()
garmin-client.ts # One fetch* function per tool + range helpers
tools.ts # MCP tool registration
coach/
state.ts # Coach state I/O (~/.gc-mcp/coach/*)
load-summary.ts # ACWR + modality load computation
readiness-synthesis.ts # Readiness fusion (HRV, sleep, body battery)
plugin/ # gc-coach Claude Code plugin
.claude-plugin/
commands/
skills/
Commands
npm run build # Compile TypeScript → dist/
npm run setup # Run the setup wizard
npm run login # Re-authenticate with Garmin
npm test # Run unit tests with Vitest
npx tsc --noEmit # Type-check without emitting files
Adding a New Tool
- Add a
fetch*function insrc/garmin-client.ts - Register it in
src/tools.tsfollowing the existingtry/catchpattern - Run
npm run build
License
MIT
推荐服务器
Baidu Map
百度地图核心API现已全面兼容MCP协议,是国内首家兼容MCP协议的地图服务商。
Playwright MCP Server
一个模型上下文协议服务器,它使大型语言模型能够通过结构化的可访问性快照与网页进行交互,而无需视觉模型或屏幕截图。
Magic Component Platform (MCP)
一个由人工智能驱动的工具,可以从自然语言描述生成现代化的用户界面组件,并与流行的集成开发环境(IDE)集成,从而简化用户界面开发流程。
Audiense Insights MCP Server
通过模型上下文协议启用与 Audiense Insights 账户的交互,从而促进营销洞察和受众数据的提取和分析,包括人口统计信息、行为和影响者互动。
VeyraX
一个单一的 MCP 工具,连接你所有喜爱的工具:Gmail、日历以及其他 40 多个工具。
graphlit-mcp-server
模型上下文协议 (MCP) 服务器实现了 MCP 客户端与 Graphlit 服务之间的集成。 除了网络爬取之外,还可以将任何内容(从 Slack 到 Gmail 再到播客订阅源)导入到 Graphlit 项目中,然后从 MCP 客户端检索相关内容。
Kagi MCP Server
一个 MCP 服务器,集成了 Kagi 搜索功能和 Claude AI,使 Claude 能够在回答需要最新信息的问题时执行实时网络搜索。
e2b-mcp-server
使用 MCP 通过 e2b 运行代码。
Neon MCP Server
用于与 Neon 管理 API 和数据库交互的 MCP 服务器
Exa MCP Server
模型上下文协议(MCP)服务器允许像 Claude 这样的 AI 助手使用 Exa AI 搜索 API 进行网络搜索。这种设置允许 AI 模型以安全和受控的方式获取实时的网络信息。