Creating a Garmin "MCP"
jackantico.io
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Honestly I've been wondering if in the near future I can basically have a big machine and some sort of "ingest" program.
Then keep connect my devices to it, where it will backup all the data, and mine the backups for information I want.
Mine my iphone backups for text messages or contacts
mine all my devices for photos or videos
mine my watch or bike computer or gps or whatever else for where I've been and how I've exercised.
instead, everyone wants your data and imposes themselves in the middle.
but a lot of these folks are uploading everything to garmin connect and letting it have your data and do the work.
Strava (and I assume to some extent Garmin) apply some smoothing to these raw GPX traces to try and improve the path, or remove some of the noise.
You'd be missing out on this post-processing by taking the data raw. Ofc you can implement something similar yourself, but I wanted to point out that these platforms are doing a little bit more than just displaying the GPX trace.
I wander often on many smartwatch/sport tracking forums/subreddits, and it's fairly frequent that people ask how to deal with smoothing and get back raw data. Some love how Garmin smooths out a race track run for them and make gps trail stick perfectly to a lane. Some pull their hair out seeing their lake run being smoothed out to make it look like they jumped over fences and private properties.
I often find my garmin traces confusing as well, it's not objectively better.
All fitness trackers (and mobile devices in general) do some level of smoothing on location data before recording it to an activity. There is no "raw data" to get back. The developers try to select smoothing algorithms that produce a good result in most cases but there will always be occasional discrepancies. This is usually due to poor signal quality including multipath reflections when the device doesn't have a clear line of sight to the sky due to structures or trees.
Garmin devices don't only use "GPS". They support multiple GNSS constellations including Glonass and Galileo, and depending on the selected mode may use all of those simultaneously to improve location accuracy.
Workout data might take it a step further, as you tell it the type of workout, and I'm assuming WorkoutKit might do something like adjust the distance filter that specifies how far the device has to travel before triggering a location update event to minimize battery use during the workout.
Interesting article (which I think is relevant)
https://claude.ai/artifact/162zJUVejDdrAAw6yz9ETs
fyi - most of the functionality already working, but the key factor is how to get the data from the vendors.I currently rely on run-gap but i realise this is not a long-term solution. Last time i have checked intervals icu api I just couldn't stop throwing up for a few days -but this might be better in the mean time.
long term solution is to have something like rungap, server side without the ridiculous fees some of the vendors charge (terra, rook,...)
if anybody wants to test what I currently got, or just has some feedback - let me know.
They charge an absolute fortune.
I've been trying to get developer access to my watch, but seems for months the Garmin Developer Program doesn't seem to accept any "requests". The only thing I've seen working, is the full account export, but that takes ~3 days for me from pressing the button until I get the email. Besides that, syncing via Bluetooth and reverse-engineer their own protocol that runs there, seems to be the only way, sadly.
Leadership is very aware of this and is accordingly being very careful about how easy we make it for people to instantly offload all of the data they've entered that makes our product worth using vs. a competitor.
I'm not saying this is good, obviously as a consumer I'd like the opposite. All I'm saying is, don't expect companies to be naive about this. If you don't want to be "locked in", you'll likely have to pay for that in some other way.
> If you don't want to be "locked in", you'll likely have to pay for that in some other way.
That "some other way" is almost never via the wallet. From Apple to Whoop to Snowflake to Oracle, the most expensive ecosystems are often the ones with the most lock-in. More often than not, the "some other way" you pay is by having to put up with janky UX and incomplete featuresets.
How is it working for you in Garmin for sleep tracking? I tried it a few years ago and loved it at first, but then noticed how incorrect sleep data was.
No, I'm not affiliated with Tredict :) (but if you guys are reading it, good job)
I've been using taxuspt/garmin_mcp[0] via claude desktop and recommend it. It reads my data and it is able to create and schedule workouts. I've decided to fork it because it was not able to create the type of workouts that i wanted (swim, bike, run and gym) and it also pushes into my garmin calendar which syncs directly to the watch/gps unit).
Claude's official strava connector[1] is able to read the data (garmin -> strava -> claude), yes. But my point of view for strava is that it's not really meant to be for workouts - it's a social media to give/receive kudos and see what your friends and 'influencers' are doing (i'm not really interested). All the metrics of cadence/vertical oscilation/sleep, for example, are not synced to strava and therefore not accessible.
[0]: https://github.com/taxuspt/garmin_mcp [1]: https://claude.com/marketplace/connectors/strava
The web and mobile based workout builder has a terrible UI if your workout changes between sessions so I've lifted some features from an app called liftosaur and got it to send activities to my watch. Unfortunately Garmin don't seem to care very much about strength training, so are missing a lot of pretty key exercises from their list, with no ability to create custom ones
See also: the OG App : https://techcrunch.com/2022/09/27/og-app-promises-you-an-ad-...
This is why I don't understand why MCPs (or in other words open documented APIs right?) are being pushed so much.
What's the value in e.g. Amazon opening up their APIs to competitors, lowering the cost of scraping their data? Or allowing their consumers to more easily analyze dynamic pricing? Isn't the whole point to steer people towards closed proprietary apps that work in walled garden that prevent reverse-engineering and any kind of modification?
Not a great example considering how easy it is to get Amazon data from both official and unofficial APIs (which is very cheap at scale)
Also sounds like a great candidate for backing up (automatically) your Garmin data locally !
- Syncs Garmin every 30 min into a database, so you don't hit garmin's API but rather my own
- Week/month trends for HRV, resting HR, sleep, training readiness, race predictions
- A "how am I today" brief: last night's sleep, HRV vs baseline, readiness, recent load
- Read-only SQL for the weird questions, like "does less sleep hurt my runs?"
My agents use it for daily briefs to me and when i ask about random health/exercise stuff - https://github.com/BrianVia/garmin-mcp-cloudflare-workers
It's been working great. The Claude morning brief compares my sleep, HRV, training status, calendar, and weather and then tells me when and how hard to workout that day.
I've found it can also give quite good suggestions for what kind of run to do after looking at my previous weeks activities on the Strava website.
For example after I complete a run on Strava I want my agents to know about it, they already have all the context, they know what weekly volume I'm aiming for and what I'm training for
Its funny because I literally just used it, opened HN, then saw this post
-> www.fitsel.app
I have been experimenting with using run-gap paid and my own agregation / mcp for a little over a year, and for me and my coach it works great. You'll get to dive into the numbers the way you prefer either via api or using any LLM which offers some new ways of looking at your data. And the whole thing is liberated from vendor specific interpretation. but thats just me, be curious to get some more thoughts on it.
This works perfectly for me. Couldn't be happier.
For example, if you want to track your maintenance calories (TDEE, total daily expenditure), Garmin isn't going to be much useful.
I add them to a spreadsheet along with other metrics I've been collecting manually for a long time, like tape, caliper measurements etc.
I do it weekly and then ask Claude to analyse the sheet.
It's super manual but just once a week and it can be really helpful / spots insights I often miss like how sleep affected something etc.
We actually operate a MacroFactor competitor: MacroCodex (which is completely free). https://macrocodex.app/ we've like 17,000+ users so far.
It adapts much faster than MacroFactor, and it's completely free of subscriptions and ads.
Guaranteed weight gain or loss within 2-3 weeks, consider reading reviews if in doubt, many people will see results from the very first week on macrocodex!
Many people waste their time by adding "calorie burn" from different activities by tracking all of them individually in smartwatches or fitness bands.
Why not?
You can't use a sensor and stack calorie burn from bunch of activities and add them all up to workout maintenance calories.
The sensorless method we use is more reliable, https://macrocodex.app/knowledge/rethink/adaptive-tdee/
You can see the reviews and guaranteed results within 2-3 weeks, all for free.
Currently experimenting with prompt-injecting my sleep score etc with a startup hook, so agents automatically give simpler responses when I'm not "all there." (Also using this data to make it suggest less complicated/demanding perfume samples to try on those days.) Curious if anyone else has cool use cases for feeding health data to the AI overlords.
I've been using a local LLM (Gemma) to tag my personal documents (invoices, receipts, etc.) and there's no way I'd ever send that data to Anthropic or OpenAI.