garmin-connect-mcp-server
Provides access to Garmin Connect data including daily health metrics, sleep, activities, training status, and body composition via read-only tools.
Click on "Deploy Server".
Wait a few minutes for the server to deploy. Once ready, it will show a "Started" state.
In the chat, type
@followed by the MCP server name and your instructions, e.g., "@garmin-connect-mcp-server what's my training status?"
That's it! The server will respond to your query, and you can continue using it as needed.
Here is a step-by-step guide with screenshots.
garmin-connect-mcp-server
A read-only Model Context Protocol (MCP) server that gives Claude Desktop access to your Garmin Connect data — daily health metrics, sleep, activities, training status, and body composition.
Non-technical? Follow the step-by-step QUICKSTART — or, if you use Claude Cowork/Claude Code, paste the one-shot prompt in SETUP-PROMPT.md and let Claude do the setup for you.
Why this exists
Garmin's official APIs (Health API, Activity API) are only available through the
Garmin Connect Developer Program,
which is gated to approved businesses. This server instead uses the well-established
unofficial garminconnect Python
library, which signs in with your own Garmin account using the same OAuth flow as the
official Garmin Connect mobile app. No developer program membership, no API keys — you
log in once and the long-lived tokens refresh themselves on use.
Unlike most Garmin MCP servers (which expose 60–110 thin endpoint wrappers), this one follows Anthropic's tool-design guidance: six consolidated, purpose-built tools that return compact tables designed for an LLM's context window.
Related MCP server: DkwtMCP
Tools
Tool | What it returns |
| Per-day steps, resting HR, overnight HRV + status, Body Battery high/low, stress, intensity minutes, active calories (≤31 days/call) |
| Per-night sleep score, quality, stage durations (deep/light/REM/awake), overnight HRV, SpO2, resting HR (≤31 days/call) |
| Activity list with IDs, distance, duration, HR, pace/speed, elevation, training effect; filterable by type (≤90 days/call) |
| One activity in depth: pace/power/cadence/calories, plus lap splits and HR-zone breakdown in |
| Training readiness, training status, acute load, VO2max, HRV status, and 5K/10K/half/marathon race predictions in one call |
| Weight, body fat %, muscle mass, body water, BMI from a Garmin Index scale or manual entries (≤90 days/call) |
All tools are read-only and marked with readOnlyHint — nothing is ever written to
your Garmin account. Tools degrade gracefully: an account with no watch data returns
clearly-empty tables rather than errors (activity-only accounts, e.g. from a Tacx
trainer, still get full activity data).
Requirements
Python 3.12+ (required by
garminconnect0.3.x)A free Garmin Connect account (no device required to test auth; data appears once a device or app syncs to the account)
Claude Desktop to use the tools (optional for development)
Install
With uv (recommended):
uv syncWithout uv (plain venv + pip) — macOS/Linux:
python3 -m venv .venv
.venv/bin/pip install -r requirements.txtWindows (PowerShell):
py -m venv .venv
.venv\Scripts\pip install -r requirements.txtBoth paths create the environment in .venv/, so the Claude Desktop config below is
identical either way.
Authenticate (one time)
uv run python login.py # or: .venv/bin/python login.pyEnter your Garmin email and password (plus MFA code if enabled). OAuth tokens are saved
to ~/.garminconnect and refresh themselves on use. Your password is never stored —
only the tokens are. Re-run the same command whenever tokens expire, or with --force
to switch to a different Garmin account.
To store tokens somewhere else, set the GARMINTOKENS env var — but note it must then
be set in both places: in your shell when running login.py, and in the Claude
Desktop config's env block (GUI apps don't inherit your shell environment):
"garmin": {
"command": "...",
"args": ["..."],
"env": { "GARMINTOKENS": "/path/to/tokens" }
}Test locally (optional)
uv run fastmcp dev inspector server.py # or: .venv/bin/fastmcp dev inspector server.pyThis opens the MCP Inspector in your browser to exercise each tool by hand.
Install in Claude Desktop
Prefer not to hand-edit JSON? The QUICKSTART has a copy-paste prompt that asks Claude (Claude Code, or Claude Desktop with file access) to write this config for you.
Edit claude_desktop_config.json:
macOS:
~/Library/Application Support/Claude/claude_desktop_config.jsonWindows:
%APPDATA%\Claude\claude_desktop_config.json
(Claude Desktop → Settings → Developer → Edit Config opens it for you.) Add:
{
"mcpServers": {
"garmin": {
"command": "/ABSOLUTE/PATH/TO/garmin-connect-mcp-server/.venv/bin/python",
"args": ["/ABSOLUTE/PATH/TO/garmin-connect-mcp-server/server.py"]
}
}
}On Windows, command is C:\\...\\garmin-connect-mcp-server\\.venv\\Scripts\\python.exe.
No env block or secrets are needed — auth comes from the token store. Fully quit and
reopen Claude Desktop (it reads the config only on launch), then try:
"What were my Garmin workouts this month?"
Troubleshooting
429/ rate limited during login — Garmin rate-limits its SSO endpoint by IP. Don't retry in a loop; wait 30–60 minutes or switch networks (a phone hotspot changes your IP) and runlogin.pyagain.Authentication failed / token errors — re-run the login script (
uv run python login.pyor.venv/bin/python login.py); tokens die if you change your Garmin password or Garmin revokes them. The running server picks up fresh tokens on the next tool call — no restart needed.Tools return empty tables / all
-— the account has no synced data for that range. Health metrics (sleep, HRV, Body Battery, training status) require a Garmin watch; activities can come from any source that syncs to Garmin Connect (trainer, Zwift, phone app).Login suddenly breaks for everyone — Garmin occasionally changes their SSO flow, which temporarily breaks the unofficial library until it's patched. Update with
uv sync --upgrade(or.venv/bin/pip install -U garminconnect) and retry.Claude Desktop doesn't show the tools — check the config file for JSON errors (a trailing comma breaks the whole file), verify both paths are absolute and the
.venvexists, then fully quit and reopen the app.
How it works
Claude Desktop ──stdio──> server.py (FastMCP, 6 read-only tools)
│
├── reads OAuth tokens from ~/.garminconnect
│ (written once by login.py; auto-refreshed)
│
└── garminconnect (unofficial lib, >= 0.3.6)
└── Garmin Connect private web APIserver.py — the MCP server; never sees your password, only reads tokens.
login.py — one-time interactive sign-in (handles MFA); saves tokens.
Fair warning
This uses Garmin Connect's private web API via your personal account — technically a gray area under Garmin's ToS, though it's the same approach used for years by Home Assistant integrations and many other community projects without issue. Use reasonable request volumes and your own account. This project is not affiliated with or endorsed by Garmin.
Development
uv run python -m compileall server.py login.py # syntax check
uv run fastmcp dev inspector server.py # manual tool testingTool design notes: tools are namespaced garmin_* to compose cleanly with sibling
health MCP servers (Oura, Strava, …); outputs are compact markdown tables (roughly
40 tokens/day-row); date ranges are capped per call with actionable error messages.
License
Available Tools
6 toolsgarmin_get_activity_detailARead-only
Deep-dive a single Garmin activity: distance, time, HR, pace/speed, cadence, power, elevation, calories, training effect — plus lap splits and heart-rate-zone breakdown in 'detailed' mode. Get activity_id from garmin_list_activities first.
Inputs: activity_id (required), response_format. Returns: result
garmin_get_body_compositionARead-only
Body composition entries (Garmin Index scale or manual) as a table (max 90 days, default last 30). Columns: date, weight_kg, body_fat_pct, muscle_mass_kg, body_water_pct, bmi. Only days with a measurement appear.
Inputs: end_date, start_date. Returns: result
garmin_get_daily_summaryARead-only
Day-by-day Garmin health metrics as a compact table (max 31 days, default last 7).
Columns: date, steps, resting_hr (bpm), hrv_avg (ms overnight), hrv_status (balanced/unbalanced/low), bb_high/bb_low (Body Battery 0-100), stress_avg (0-100), intensity_min (moderate + 2x vigorous), active_kcal. For sleep detail use garmin_get_sleep; for workouts use garmin_list_activities.
Inputs: end_date, start_date. Returns: result
garmin_get_sleepARead-only
Garmin sleep data per night as a compact table (max 31 days, default last 7).
Columns: date (wake-up morning), score (0-100), quality, duration, deep, light, rem, awake (H:MM), overnight_hrv (ms), spo2_avg (%), resting_hr (bpm). Note: if the user also wears an Oura ring, oura_* tools report the same nights and may differ slightly; say which source you're citing.
Inputs: end_date, start_date. Returns: result
garmin_get_training_statusARead-only
Current Garmin training snapshot in one call: training readiness score, training status (e.g. productive/maintaining/strained), acute load, VO2max, HRV status, and race time predictions (5K/10K/half/marathon). Use this for 'how is my training going / how recovered am I' questions; combine with oura_* readiness for cross-source checks.
Inputs: no named parameters. Returns: result
garmin_list_activitiesARead-only
List Garmin activities in a date range as a compact table (max 90 days, default last 30).
Columns: activity_id (for garmin_get_activity_detail), date, type, name, distance_km, duration (H:MM), avg_hr, max_hr, pace_or_speed, elev_gain_m, aerobic_te (training effect 0-5), anaerobic_te.
Inputs: limit, end_date, start_date, activity_type. Returns: result
Tool Schema Changelog
Recent tool additions, removals, and schema changes observed during successful MCP inspections.
Loading tool schema changelog…
TDQS
Scored across 6 tools
Each tool targets a unique aspect of Garmin data: daily summary, activity detail, training status, body composition, sleep, and activity list. No two tools overlap in purpose, making selection unambiguous.
Tools follow a 'garmin_verb_noun' pattern (e.g., garmin_get_daily_summary, garmin_get_sleep), with 'garmin_list_activities' being the only one using 'list' instead of 'get'. This minor inconsistency is easily understood but breaks the pattern slightly.
With 6 tools covering key health and fitness domains (daily metrics, activities, training, body composition, sleep), the count feels well-scoped and sufficient for a read-only health data API.
The tool surface covers essential read-only operations: retrieving daily summaries, activity details, training status, body composition, sleep, and listing activities. Cross-references between tools indicate thoughtful design, with no obvious missing functionality for the intended purpose.
Maintenance
Related MCP Connectors
Garmin data in Claude & ChatGPT via the Garmin Health API. OAuth sign-in, no password sharing.
Garmin data in Claude: 135 tools — activities, sleep, HRV, training, workouts. Free, open source.
tri-train is a training platform for triathletes that syncs activities from Strava and Garmin and exposes them to Claude through a remote MCP server. Ask Claude how your last block went, why your run pace dropped, or whether you are fresh enough for Sunday's race, and it answers from your real data: activities with laps and grade-adjusted pace, weekly load and the performance management chart (CTL/ATL/TSB), sleep, HRV and resting heart rate, and your race calendar with predictions. Claude can also act: create and adjust planned workouts with structured intervals, push them to your Garmin watch, add races and write notes. Every change is journaled and can be undone. Read and write access are separate OAuth scopes, and the server enforces them on every call. Built and hosted in Switzerland by a triathlete; data stays on our own servers (Swiss revDSG / GDPR).
WHOOP recovery, strain, sleep and workouts in Claude via official WHOOP OAuth. Free, open source.
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- AlicenseAqualityCmaintenanceLocal MCP server that connects Claude Desktop with Garmin and Apple Health data to read training and recovery, estimate heart rate and pace zones, analyze performance, and create structured workouts.22MIT
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