Garmin Connect

io.github.happyc0der由 GitHub 账号 happyc0der 发布v0.3.2更新于 Oct 29, 2026

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

已验证STDIO仅桌面位置与生活数据与分析

概览

AI 生成的概览

非官方 Garmin Connect 服务器,让助手读取活动、健康数据与训练计划,并写入训练、已完成的训练记录和称重数据。

可以做什么
  • 读取活动,含力量训练每组明细、跑步与骑行分段、泳池游泳每趟数据,以及计划训练和日历
  • 读取每日健康数据(步数、心率、压力、身体电量、睡眠、HRV、准备度)、最长两年的趋势与个人纪录
  • 离线搜索 Garmin 动作库,并快速获取登录状态、近期力量训练和每周汇总
  • 创建力量、跑步、骑行和游泳训练,安排日程并推送到手表
  • 记录已完成的力量训练并修正其组数,记录称重与身体成分,重命名或删除活动
适用场景
适合在 Garmin Connect 记录训练的人,让助手回答关于自己活动、睡眠、心率和趋势的问题,或在不打开网站的情况下安排训练、记录已完成的训练。
运行要求
通过 uvx 以 stdio 在本地运行,需要 uv 和 Python 3.12 或更高版本。需在终端一次性登录 Garmin 账号(邮箱、密码及多因素验证码),令牌保存在 GARMINTOKENS 指定的目录,默认 ~/.garmin-api/default。需要访问 Garmin 的网络。
安装前请注意
非官方:使用 Garmin 的私有接口,接口可能随时变动,且不受 Garmin 条款认可;仅用于自己的账号。Garmin 密码只在登录时输入一次,令牌会保存在磁盘上。写入操作会创建、覆盖或删除真实数据,记录的活动可能自动同步到 Strava 等应用。登录失败过多可能导致账号被锁定,遇到限流不要重试。

安装

在 SourceWeft 中

  1. 打开 控制台中的 Garmin Connect,将其添加到工作区。
  2. 为需要使用其工具的对话启用该服务。

Desktop only,通过 STDIO。 STDIO 服务会启动本地进程,因此需要 SourceWeft 桌面宿主。

其他 MCP 客户端

参照 仓库 中的启动说明。

README

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:

bash
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:

bash
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):

json
{  "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:

json
{  "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:

json
{  "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

bash
garmin doctor                          # setup check, no networkgarmin activities --type strength_training --limit 5garmin sets <activity-id>              # per-set detailgarmin day 2026-10-18                  # one day of health datagarmin exercises "lat pulldown"        # search the catalogue, offlinegarmin workout create workout.json     # plan a strength workoutgarmin log-session session.json        # log a completed onegarmin encode-session session.json     # build its FIT file without uploadinggarmin decode-fit activity.zip         # read sets out of a Garmin exportgarmin 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

python
from datetime import datetime, timedelta, timezonefrom garmin_api.services import activities, health, uploadsfrom 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:

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

Development

bash
git clone https://github.com/happyc0der/garmin-connect-apicd garmin-connect-apiuv syncuv run pytest

487 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:

bash
GARMIN_LIVE=1 uv run pytest tests/live                      # read onlyGARMIN_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.

来源:README.md,提交 8d7779f

工具

0
SourceWeft 尚未在沙箱中启动过该软件包,因此其工具未知。

版本历史

3
  1. v0.3.2最新Oct 29, 2026
  2. v0.3.1Oct 20, 2026
  3. v0.2.4Oct 19, 2026

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