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TrainBud

by Zsadigzadeversion 0.9.0i★ –iRuns on your computer
Registry nameio.github.Zsadigzade/trainbud

Install

Overview

Description from the maker (original English)

Talk to your own fitness data. Findings computed in code against your own 28-day baselines.

PopNx MCP’s three pillars

These three are never merged into one score: opinions, measurements and popularity are different things.

What you can do with it

We have not written a plain-language summary for this one yet. Below are the facts we read from the registry.

  • Connection: Runs on your computer
  • Transport: stdio
  • Category: Clinics & health
  • You need to fill in: GARMIN_EMAIL, GARMIN_PASSWORD, ANTHROPIC_API_KEY

Install

Pick the AI app you use, then copy the settings.

Before you install

  • Basic checks: 1 of 1 passed
  • Runs on your computer with your user’s permissions (files, network, apps).
  • You fill in yourself: GARMIN_EMAIL, GARMIN_PASSWORD, ANTHROPIC_API_KEY

Values marked secret are keys to your account. Never share them or paste them into a chat.

You need

  • npmNode.js installed (for the npx command)

Which app do you use?

Pick your app above. We remember it, so next time the button says “Install in …”.

Open Claude Desktop → Settings → Developer → Edit Config, and paste this into claude_desktop_config.json

{
  "mcpServers": {
    "trainbud": {
      "command": "npx",
      "args": [
        "-y",
        "trainbud",
        "start"
      ],
      "env": {
        "GARMIN_EMAIL": "your-value",
        "GARMIN_PASSWORD": "your-value",
        "ANTHROPIC_API_KEY": "your-value"
      }
    }
  }
}

Run this in your terminal

claude mcp add trainbud --env GARMIN_EMAIL=your-value --env GARMIN_PASSWORD=your-value --env ANTHROPIC_API_KEY=your-value -- npx -y trainbud start

Fill in the empty values before running it.

Open in Cursor

Or copy the settings yourself

Paste into .cursor/mcp.json in your project, or ~/.cursor/mcp.json

{
  "mcpServers": {
    "trainbud": {
      "command": "npx",
      "args": [
        "-y",
        "trainbud",
        "start"
      ],
      "env": {
        "GARMIN_EMAIL": "your-value",
        "GARMIN_PASSWORD": "your-value",
        "ANTHROPIC_API_KEY": "your-value"
      }
    }
  }
}

Your browser asks to open the app, then the app shows the settings and asks you to confirm. Key values are left empty for you to fill in.

Open in VS Code

Or copy the settings yourself

Paste into .vscode/mcp.json in your project

{
  "servers": {
    "trainbud": {
      "type": "stdio",
      "command": "npx",
      "args": [
        "-y",
        "trainbud",
        "start"
      ],
      "env": {
        "GARMIN_EMAIL": "your-value",
        "GARMIN_PASSWORD": "your-value",
        "ANTHROPIC_API_KEY": "your-value"
      }
    }
  }
}

Your browser asks to open the app, then the app shows the settings and asks you to confirm. Key values are left empty for you to fill in.

This one runs on your computer, and ChatGPT can only connect to servers on the internet. Pick another app.

Your choice stays on this device in a cookie; no account needed.

Values you fill in

  • GARMIN_EMAIL required env
    The email address for your Connect account. Stored only in your local .env; `npx trainbud setup` writes it for you.
  • GARMIN_PASSWORD secret required env
    Your Connect password. Stored only in your local .env. Accounts with MFA enabled are not supported, because the unofficial library this drives cannot complete that flow.
  • ANTHROPIC_API_KEY secret env
    Optional, and only for the watch app's Ask card and daily insight. The MCP tools themselves need no model key: every finding is computed in code, and the model only phrases it.

These settings are generated from the maker’s registry entry. If the README says otherwise, follow the README.

What it can do

Runs on your computer; the tool list appears in your AI app after you install it.

Basic checksi

We check information anyone can see; we have not read the code. Checks that do not apply are left out of the count. · Checked Nov 7, 2026

  • ✓ Pass

    Maker matches the repo

    The registry name was verified with the GitHub account Zsadigzade, which owns the repo

  • … Not checked yet

    Still maintained

    We have not read this repo from GitHub yet

  • … Not checked yet

    Has a licence

    We have not read this repo from GitHub yet

  • – Not applicable

    Endpoint responds

    This one runs on your computer; there is no internet endpoint

  • – Not applicable

    Sign-in with OAuth

    Runs on your computer and uses local settings instead

  • … Not checked yet

    No hidden instructions in tool descriptions

    Runs on your computer; we can only read tool lists from internet endpoints

Compared with others in Clinics & healthi

  • More stars than 0% of the other 871 servers in this category
  • Published to the registry more recently than 41% of the other 871 servers in this category
  • Basic checks equal to or better than 100% of the other 871 servers in this category

Compared with every active server in this category in the registry. Stars count only when the publisher owns the repo.

Common questions

Is TrainBud safe?

It passed 1 of 1 applicable basic checks. We have not read the code. Before adding a key or token, see what access the server asks for and use a key with only the permissions you need.

What keys or codes does it need?

You need to fill in: GARMIN_EMAIL, GARMIN_PASSWORD, ANTHROPIC_API_KEY

Does it run on my computer or in the cloud?

It runs on your computer. Your AI app starts it when needed, and data does not pass through the maker’s servers (unless it calls an online service itself).

Is it still maintained?

The GitHub repo last changed –, and the latest version (0.9.0) reached the registry 2 months ago.

Which apps can use it?

Apps that support MCP, such as Claude Desktop, Claude Code, Cursor and VS Code. You also need Node.js, Docker on your computer.

What can I use instead?

In the same category: Mirobody, FHIR MCP Server, Google Health MCP

Alternatives

Servers in the same category from other makers, sorted by stars.

Reading a card:★ GitHub starsiThree pillars: reviews · checks · usageiUpdated = latest version published to the registryi

Mirobody

by thetahealth

Lab results to LOINC codes and UCUM units, symptoms and diagnoses to ICPC-3. Offline, no API key.

Runs on your computer★ 1,408Apache-2.0Updated 6 days ago
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MCP server providing seamless access to FHIR APIs for AI tools and healthcare applications

Runs on your computer★ 137Apache-2.0Updated 9 days ago
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Google Health MCP

by davidmosiah

Privacy-first unofficial Google Health API v4 MCP server for health, sleep, activity, HR agents

Runs on your computer★ 79MITUpdated 4 months ago
Install

README from the maker

Open the README

Copied from the maker’s repo as written. PopNx MCP has not reviewed or endorsed it. HTML, images and scripts are removed. Links lead off this site.

TrainBud

Talk to your training data.

TrainBud is an open-source MCP server that connects your Garmin Connect fitness data to Claude, Cursor, and other AI assistants. Ask about workouts, sleep, heart rate, recovery, and body composition in plain English — privately, on your machine.

Disclaimer: TrainBud is an unofficial community project. It is not affiliated with, endorsed by, or sponsored by Garmin Ltd. Garmin Connect is a trademark of Garmin Ltd.

Try it

Once connected to your MCP client, ask things like:

  • *"What did I do today?"*
  • *"How's my sleep been this week?"*
  • *"Am I recovered enough to train hard tomorrow?"*
  • *"Is my resting heart rate trending down?"*

See examples/prompts.md for more ideas.

Why TrainBud

  • Private — credentials stay in your local .env; data is cached on your machine
  • Local-first — SQLite cache, session tokens in .trainbud/
  • Works everywhere — Windows, macOS, Linux (Node.js 22.12+)
  • Any MCP client — Claude Desktop, Cursor, and other stdio-compatible clients
  • Smart fetching — batched API calls and automatic re-auth when sessions expire

Quick start

npx trainbud setup

The setup wizard walks you through credentials, authentication, and connecting Cursor or Claude Desktop — no MCP config editing required. Then restart your MCP client and ask it what you did today.

To keep trainbud on your PATH instead of typing npx every time:

npm install -g trainbud

trainbud setup

Needs Node 22.12+. Full walkthrough: QUICKSTART.md

From source (for contributors, or to run an unreleased commit)

git clone https://github.com/Zsadigzade/trainbud.git

cd trainbud npm install npm run build npm link # puts trainbud on your PATH; undo with npm unlink -g trainbud trainbud setup

Without npm link, every trainbud in this README is node dist/index.js run from the repo root. If dist/ does not exist yet, run npm run build first.

Claude Code plugin (recommended)

Install as a Claude Code plugin — skills and MCP server in one step:

/plugin marketplace add Zsadigzade/trainbud

/plugin install trainbud@trainbud

Set credentials, then restart Claude Code:

export GARMIN_EMAIL="your@email.com"

export GARMIN_PASSWORD="yourpassword"

CommandWhat it does
/trainbud:trainbud-setupFirst-time setup and diagnostics
/trainbud:trainbudAsk about workouts, sleep, recovery, HR, stress, VO2 max

Plugin files live in plugin/. See plugin/README.md.

Claude Code skills (in-repo)

This repo also ships project skills in .claude/skills/ for development without installing the plugin:

CommandWhat it does
/trainbud-setupInstall, authenticate, configure MCP, run live check
/trainbudAsk about workouts, sleep, recovery, HR, stress, VO2 max

Open the repo in Claude Code (claude in this directory) — skills load automatically.

To use skills in every project without the plugin, copy them to ~/.claude/skills/.

After setup, restart your MCP client and try /trainbud with *"What did I do today?"*

Dashboard

trainbud serve hosts a dashboard at /dashboard. It is phone-first, because the pairing flow is: you are standing next to the watch holding a phone when you approve a code.

It shows what stands out today against your own baselines, this week against last week, and resting heart rate and sleep plotted against your own 30-day median — all read from the local history store, so it paints instantly and works even when your Connect session has expired. A break in a line is a day with no measurement, not a zero.

It is also where you tell TrainBud who it is talking to:

SettingWhat it changes
Name, units, primary sport, weekly goalEvery renderer, and what the AI is told about you
ThresholdsWhere green becomes amber and amber becomes red — on the watch too
Watch cardsWhich cards appear on the wrist and in what order, live on the next sync
AI model, tone, answer lengthHow the Ask card and the daily insight sound
Your own Ask questionsUp to five, 32 characters each. They lead the watch's Ask menu; the rest of the slots stay generated from what fired
Monthly spending capOptional. Refuses an Ask past the cap instead of spending past it
PrivacyLocal feature counters, on by default, with a delete button

Usage. TrainBud runs on your own AI provider key, so every question and every daily insight is charged to you. The dashboard shows the tokens and cost per call, the month to date, and a 30-day chart. A model this build has no published price for is recorded with its cost left *unknown* rather than as zero — a call priced at zero would make a cap that can never trip.

Nothing on this page leaves your machine. There is no endpoint to send it to.

Garmin watch widget (Connect IQ)

View recovery, sleep, activity, stress, and VO2 max on your Garmin watch via a Connect IQ widget in ciq/.

Requires: trainbud serve running + HTTPS tunnel (same setup as web AI).

  1. Start the server and tunnel:
   trainbud serve

cloudflared tunnel --url http://127.0.0.1:3847

2. Build and sideload the widget — see [ciq/README.md](./ciq/README.md)
  1. In Garmin Connect Mobile → Connect IQ → TrainBud settings, set:
  • Server URL — your tunnel URL (e.g. https://abc.trycloudflare.com)
  1. Open the widget on your watch — it shows a pairing code. Approve it in the dashboard (/dashboard?token=YOUR_API_KEY) to complete setup. The dashboard swaps that token for a session cookie and drops it from the URL, so the address bar is safe to screenshot afterwards.

The glance shows recovery and sleep, or the top finding in a few characters ("RHR +4 bpm"), from the last cached summary, so it renders without waiting on the network; once that is more than two hours old it says so. Open it and tap or swipe to cycle through the cards you left switched on in the dashboard. The watch calls GET /api/watch — a compact JSON summary, not the full MCP protocol.

On the Today card, START (or tap) opens a finding to the rule it fired on — "Each of the last 3 days was at least 3 bpm and 2 deviations above your 28-day median of 48 bpm" — and from there it can be muted for three days (POST /api/mute). The Sleep card names what moved last night against your own nights ("Deep 40m (1h24m)"). On the Forerunner 55, whose widget has 64 KB, those two are compiled out so the rest still fits.

Detector rules

Every finding fires on a rule you can see and move. The dashboard's Detector rules section holds the bars — resting HR days/bpm/deviations, sleep-debt hours, HRV drop, the training-load ratios, and "several signals together" (resting HR up, HRV down and sleep stress up at once) — bounded so no setting makes every day, or no day, a finding. Every surface shows the rule a finding fired on, with the numbers that were in force.

Voice (/voice)

Hold a button on your phone, ask a question out loud, hear the answer read back. Open https://YOUR-HOST/voice?token=YOUR_API_KEY once; it trades the key for a cookie and redirects to a clean URL.

  • Android / Chrome — speech recognition happens in the browser. Free, no key.
  • iPhone / Safari — records audio and transcribes it server-side via Groq (whisper-large-v3-turbo, about $0.04 per hour of audio). Add the key on the dashboard.
  • Both — answers are spoken back, and Read me my day / Read today's insight cost nothing at all: they are composed in code from data already on hand, not generated.

Not a watch feature and it cannot be one: Connect IQ exposes no microphone or speaker to a widget. Not hands-free either — mobile browsers suspend the microphone when the tab is backgrounded, so the phone has to be awake with the page in front of you.

Full detail: docs/VOICE.md

Always on (/voice and the watch, without babysitting a terminal)

trainbud serve in a terminal lasts until the terminal closes. To have the server and the tunnel come back by themselves after a reboot:

.\scripts\install-always-on.ps1 -Hostname trainbud.example.com

That registers a scheduled task for the server and a watchdog that checks both halves every five minutes — because a tunnel that answers is not a server that answers: a tunnel with nothing behind it serves its own error page under a 200, so the link looks alive while the watch reports HTTP -400. systemd, launchd and Docker Compose recipes are in the guide.

Full detail, including Cloudflare named tunnels: docs/ALWAYS-ON.md

Connect to Claude Desktop

Edit claude_desktop_config.json:

Windows: %APPDATA%\Claude\claude_desktop_config.json macOS: ~/Library/Application Support/Claude/claude_desktop_config.json

{

"mcpServers": { "trainbud": { "command": "node", "args": ["C:/path/to/trainbud/dist/index.js", "start"], "env": { "GARMIN_EMAIL": "your@email.com", "GARMIN_PASSWORD": "yourpassword" } } } }

With trainbud on your PATH (npm install -g trainbud, or npm link from a clone), point the client at the command instead of a path:

{

"mcpServers": { "trainbud": { "command": "trainbud", "args": ["start"] } } }

Restart your MCP client, then start asking questions.

Tools

ToolWhat it answers
get_latest_activityYour most recent workout — distance, pace, HR, elevation
get_activities_rangeActivities between two dates
get_sleep_dataSleep duration, stages, score, awakenings — and which parts of last night were unusual for you
get_heart_rate_trendsResting, max, and average HR over time
get_recovery_statusRecovery score from HRV, sleep, stress, resting HR
get_body_compositionWeight, body fat, and muscle mass trends
get_stress_levelsDaily stress averages and trends
get_vo2_max_trendsVO2 max fitness trends over time
get_training_insightsCombined weekly summary (activities, sleep, recovery, stress)
get_findingsWhat stands out against your own 28-day baselines, with the rule each finding fired on
get_week_reviewThis week against last, the load forecast, sleep debt, and your next race
compare_workoutsOne workout against your own earlier efforts of the same type and distance
remember_contextRecord a goal, a race and its date, an injury, or a note
get_user_contextWhat is on record about you, on any date
log_subjectiveHow a session actually felt — RPE, soreness, mood

CLI

trainbud setup          # Interactive first-time setup (recommended)

trainbud serve # Remote HTTP

Only the beginning is shown; read the rest in the repo

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