Garmin Connect

Read and write Garmin Connect: activities, strength sets, health data, workouts and weigh-ins.

OtherPythonv0.3.1

garmin-connect-api

Read and write Garmin Connect from an MCP client such as Claude, from Python, or over a local HTTP API: activities with per-set strength detail, daily health data, planned workouts, completed strength sessions, and weigh-ins with full body composition.

Unofficial. Not affiliated with or endorsed by Garmin. It uses the same private endpoints as the Garmin Connect website, through python-garminconnect, because Garmin offers no public API for individuals. Those endpoints can change without notice, and using them is not sanctioned by Garmin's terms. It is meant for your own account and your own data.

Status

v0.3. Reads activities with per-set strength detail, laps and pool-swim lengths, daily health, trends over up to two years and named personal records; writes strength, run, ride and swim workouts, completed strength sessions, set corrections and weigh-ins with body composition. 38 tools, every one checked against a real account. Bug reports and feature requests go to GitHub Issues.

Quick start

You need uv and Python 3.12 or newer.

1. Log in once, at a terminal:

uvx --from garmin-connect-api garmin login

This is the only place a password is ever typed. It asks for your Garmin email, password and any multi-factor code, then stores tokens in ~/.garmin-api/default, readable by your user only. Nothing else ever prompts for a password; without tokens, every tool says to run this.

2. Add the server to your MCP client.

Claude Code:

claude mcp add --scope user --transport stdio garmin -- uvx garmin-connect-api@latest

Claude Desktop, in claude_desktop_config.json (in ~/Library/Application Support/Claude/ on macOS, %APPDATA%\Claude\ on Windows):

{
  "mcpServers": {
    "garmin": {
      "command": "uvx",
      "args": ["garmin-connect-api@latest"]
    }
  }
}

@latest makes uvx check for a new release each time the server starts. Without it, uvx keeps running the first version it downloaded.

3. Ask. "How did I sleep this week?", "Did my pace hold up in yesterday's swim?", "How has my resting heart rate moved since summer?", "Show my last strength session's sets, and change sets 3 to 5 to dumbbell rows", "Schedule a swim for Thursday: 200 easy, then 8 x 100 free on 20 seconds rest, in a 25-yard pool".

What it can do

38 tools, each annotated so your client knows which only read (24), which add something (8) and which delete or overwrite (6), and can ask before running those. Every argument, down to a workout step's pace target, carries a description.

ReadWrite
Activities, filtered by type and dateCreate a strength workout, schedule it, push it to a watch
Per-set strength detail: exercise, reps, weightCreate a run, ride or pool swim workout, with targets
Laps for runs and rides; pace per 100 for pool swimsLog a completed strength session, with every set
A day in one answer: steps, heart rate, stress, body battery, sleep, HRV, readinessCorrect a session's sets: exercise, reps, weight
Trends over up to two years: twelve metrics, daily, weekly or monthlyRecord a weigh-in, or a full body composition reading
Personal records, named and in unitsRename an activity or change its description
Every weigh-in with body compositionDelete an activity, workout or weigh-in
Planned workouts and the calendar
Garmin's 1,527-exercise catalogue, offline

Four tools are written for a model rather than mirrored from an endpoint: garmin_status checks the login without calling Garmin, find_exercise finds Garmin's name for a lift, and recent_strength_sessions and week_summary answer common questions in one call.

Logging a finished workout is the write Garmin's own developer programme has never offered. A session is encoded as a FIT activity file with set messages and uploaded, so it appears in Garmin Connect as a Strength Training activity, exercise by exercise.

Body composition from a smart scale (fat, water, skeletal muscle, bone, BMI, basal metabolic rate, visceral fat) is written as a FIT weight-scale file, the way Garmin's own Index scales do it. A plain weigh-in carries weight alone.

Example output

Answers come back compact, summarised the way a person would read them. These are from made-up data in the shapes Garmin returns.

"Did my pace hold up in yesterday's swim?" calls get_activity_laps:

{
  "sport": "lap_swimming",
  "pool_length": 25.0,
  "pool_unit": "m",
  "summary": {
    "lengths": 80,
    "distance": 2000.0,
    "average_pace": "1:52/100m",
    "first_half_pace": "1:50/100m",
    "second_half_pace": "1:54/100m",
    "by_stroke": {"FREESTYLE": 1800.0, "BACKSTROKE": 200.0},
    "fastest_segment": {"lengths": "5-8", "pace": "1:44/100m"},
    "slowest_segment": {"lengths": "77-80", "pace": "2:01/100m"}
  }
}

"How has my resting heart rate moved since summer?" calls get_trend, which rolls a long range into weeks:

{
  "metric": "resting_hr",
  "unit": "bpm",
  "aggregation": "week",
  "summary": {
    "days_with_data": 88,
    "average": 54.2,
    "min": 49.0,
    "max": 61.0,
    "first_period_average": 57.3,
    "last_period_average": 51.6,
    "change": -5.7
  }
}

Before you write anything

  • Activities you log may be shared automatically. If your Garmin account is connected to Strava or another app, an uploaded session can be posted there too, and deleting it from Garmin does not delete it there.
  • Rate limits are taken seriously. Garmin puts Cloudflare and per-account rate limits in front of its login, and a run of failed logins can lock an account out for a day or more. Nothing here retries a login, and a rate limit stops every call path rather than being retried. If you see one, wait.
  • Exercises need Garmin's own names, such as BENCH_PRESS / BARBELL_BENCH_PRESS. Every write but the raw workout DTO checks them against the catalogue first and suggests near misses, so a typo fails with a useful message rather than Garmin's bare 400. Common gym names work in search: "rdl", "ohp", "pull ups", "bench presses".
  • To correct a logged session, edit its sets. Logging it again with a set changed creates a second activity; logging the identical session again is reported as a duplicate.
  • Sessions and body-composition readings need a timezone offset, or a 7am reading would land hours out. They are refused without one.

Command line

garmin doctor                          # setup check, no network
garmin activities --type strength_training --limit 5
garmin sets <activity-id>              # per-set detail
garmin day 2026-10-18                  # one day of health data
garmin exercises "lat pulldown"        # search the catalogue, offline
garmin workout create workout.json     # plan a strength workout
garmin log-session session.json        # log a completed one
garmin encode-session session.json     # build its FIT file without uploading
garmin decode-fit activity.zip         # read sets out of a Garmin export
garmin serve                           # the HTTP API on 127.0.0.1:8765

Run them with uvx --from garmin-connect-api garmin ..., or install with uv tool install garmin-connect-api. Example specs: session.json, workout.json.

An encoded session file can also be imported by hand on the Garmin Connect website, if you would rather nothing logged in on your behalf.

Python library

from datetime import datetime, timedelta, timezone
from garmin_api.services import activities, health, uploads
from garmin_api.models.workouts import (
    StrengthSessionSpec, StrengthSessionExercise, StrengthSessionSet,
)

for activity in activities.list_activities(limit=5, activity_type="strength_training"):
    sets = activities.get_sets(activity.activity_id)
    print(activity.name, sets.total_volume_kg, "kg")

print(health.day("2026-10-18").steps)

uploads.log_strength_session(StrengthSessionSpec(
    name="Push A",
    start_time=datetime(2026, 10, 18, 7, 0, tzinfo=timezone(timedelta(hours=-4))),
    exercises=[StrengthSessionExercise(
        category="BENCH_PRESS",
        exercise_name="BARBELL_BENCH_PRESS",
        sets=[StrengthSessionSet(reps=10, weight_kg=60.0, rest_s=120)],
    )],
))

Responses are pydantic models with Garmin's inconsistencies ironed out: kilograms rather than grams, timezone-aware instants, snake_case throughout. Garmin's own payload is still on raw when something is not mapped.

HTTP API

garmin serve runs the same API on 127.0.0.1:8765, with interactive docs at /docs. The MCP tools are generated from these routes, so the two cannot drift apart. Because it can write to your account, the service refuses writes from web pages open in your browser and requests naming any host but localhost, which defeats DNS rebinding. Binding beyond localhost requires GARMIN_API_KEY, and the host name clients will use must be listed in GARMIN_API_HOSTS. garmin mcp --http serves the MCP tools over HTTP behind the same guard.

Configuration

VariablePurpose
GARMINTOKENSWhere tokens are stored. Defaults to ~/.garmin-api/default.
GARMIN_API_KEYRequired to bind the HTTP service beyond localhost.
GARMIN_API_HOSTSExtra host names the HTTP and MCP servers answer to, comma-separated. Needed for any name but localhost.

Docker

The Dockerfile builds the MCP server from a checkout. Tokens live in /tokens inside the container; mount an existing directory there and run as your own user, so refreshed tokens stay yours. Logging in works inside the container too:

mkdir -p ~/.garmin-api/default
docker build -t garmin-connect-api .
docker run -it --rm --user "$(id -u):$(id -g)" -v ~/.garmin-api/default:/tokens garmin-connect-api garmin login
docker run -i --rm --user "$(id -u):$(id -g)" -v ~/.garmin-api/default:/tokens garmin-connect-api

Development

git clone https://github.com/happyc0der/garmin-connect-api
cd garmin-connect-api
uv sync
uv run pytest

480 offline tests, needing no network and no account, run on Linux, macOS and Windows. They cover the models against real Garmin response shapes, the FIT codec's round trip, every one of the 1,527 catalogue exercises against the FIT profile, the HTTP routes, and every MCP tool's output against its own advertised schema, which strict clients enforce.

Tests against a real account are opt-in, and the ones that create data need a second opt-in:

GARMIN_LIVE=1 uv run pytest tests/live                      # read only
GARMIN_LIVE=1 GARMIN_LIVE_WRITE=1 uv run pytest tests/live  # creates, then deletes

Why the unofficial route

Garmin's official Connect Developer Program is for businesses, has no endpoint that uploads a completed activity, and was closed to new applicants in 2026. The aggregators that wrap it cost hundreds of dollars a month and are read-only or plans-only. So this uses the endpoints Garmin's own website uses, gently: no polling, no retries on a rate limit.

Citing

If you use this in research, cite it with the metadata in CITATION.cff; GitHub's "Cite this repository" button formats it.

Licence

MIT. Garmin and Garmin Connect are trademarks of Garmin Ltd., used here only to say what this works with.

Installation

Source-derived launch command. Check the maintainer’s required arguments and credentials before running:

bash
uvx garmin-connect-api

Set up in your AI client

Merge this template into ~/Library/Application Support/Claude/claude_desktop_config.json. Keep existing servers. Add any arguments, credentials, and permissions required by the maintainer; this template has not been install-tested.

json
{
  "mcpServers": {
    "io-github-happyc0der-garmin-connect-api": {
      "command": "uvx",
      "args": [
        "garmin-connect-api"
      ]
    }
  }
}

Restart Claude Desktop completely for changes to take effect. Confirm the server appears connected in the client’s tool list, then try a read-only example from its documentation.

Claude Desktop setup reference

Package

garmin-connect-apipypi

Compatible MCP Clients

Garmin Connect works with any MCP-compatible client. Copy the config snippet from the Configuration section above and add it to the file shown for your client, then restart the application.

  • Claude Desktop~/Library/Application Support/Claude/claude_desktop_config.jsonRestart Claude Desktop completely for changes to take effect.
  • Cursor~/.cursor/mcp.jsonRestart Cursor for changes to take effect.
  • VS Code.vscode/mcp.jsonReload VS Code window for changes to take effect.
  • Windsurf~/.codeium/windsurf/mcp_config.jsonRestart Windsurf for changes to take effect.
  • Claude Code.mcp.jsonSave at the project root, then start Claude Code in that project and review the MCP server approval prompt. Keep real credentials out of shared files.

Learn More