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Garmin Workouts MCP Server

Project description

Garmin Workouts MCP Server

CI/CD Pipeline

An MCP server that allows you to create, list, and manage Garmin Connect workouts using natural language descriptions through MCP-compatible clients.

Features

  • Create workouts: Generate structured Garmin workouts from natural language descriptions using AI
  • List workouts: View all your existing workouts on Garmin Connect
  • Get workout details: Retrieve detailed information about specific workouts
  • Schedule workouts: Schedule workouts on specific dates in Garmin Connect
  • Delete workouts: Remove workouts from Garmin Connect
  • Activity management: List, view, and get weather data for completed activities
  • Calendar integration: View calendar data with workouts and activities
  • MCP Integration: Works with any MCP-compatible client (Claude Desktop, etc.)

Setup

  1. Install and run using uvx:
uvx garmin-workouts-mcp
  1. Configure in your MCP client (e.g., Claude Desktop):

Add to your MCP client configuration:

{
  "mcpServers": {
    "garmin-workouts": {
      "command": "uvx",
      "args": ["garmin-workouts-mcp"],
      "env": { # See Authentication section for details
        "GARMIN_EMAIL": "your_email@example.com",
        "GARMIN_PASSWORD": "your_password"
      }
    }
  }
}

Authentication

The Garmin Workouts MCP Server authenticates with Garmin Connect using garth [https://github.com/matin/garth]. There are two primary ways to provide your Garmin credentials:

1. Using Environment Variables

You can set your Garmin Connect email and password as environment variables before starting the MCP server.

  • GARMIN_EMAIL: Your Garmin Connect email address.
  • GARMIN_PASSWORD: Your Garmin Connect password.

Example:

export GARMIN_EMAIL="your_email@example.com"
export GARMIN_PASSWORD="your_password"
uvx garmin-workouts-mcp

2. Out-of-Band Authentication with garth

Alternatively, you can log in to Garmin Connect once using the garth library directly and save your authentication tokens to a directory, which the MCP server will then use for subsequent sessions. This method is useful if you prefer not to store your credentials as environment variables or as part of your MCP client configuration.

To log in out-of-band:

  1. Install garth:

    pip install garth
    
  2. Run the following Python script in your terminal:

    import garth
    from getpass import getpass
    
    email = input("Enter email address: ")
    password = getpass("Enter password: ")
    # If there's MFA, you'll be prompted during the login
    garth.login(email, password)
    
    garth.save("~/.garth")
    

    Follow the prompts to enter your Garmin Connect email and password. Upon successful login, garth will save your authentication tokens to ~/.garth.

    The MCP server will automatically look for these saved tokens. If you wish to store them in a custom location, you can set the GARTH_HOME environment variable.

Usage

This server provides the following MCP tools that can be used through any MCP-compatible client:

Generate Workout Data Prompt

Use the generate_workout_data_prompt tool to create a prompt for an LLM to generate structured workout data:

generate_workout_data_prompt("10 min warmup, 5x(1km at 4:30 pace, 2min recovery), 10 min cooldown")

Upload Workout

Use the upload_workout tool to upload structured workout data to Garmin Connect:

upload_workout(workout_data_json)

Schedule Workout

Use the schedule_workout tool to schedule a workout on a specific date:

schedule_workout("workout_id_here", "2024-01-15")

Delete Workout

Use the delete_workout tool to remove a workout from Garmin Connect:

delete_workout("workout_id_here")

List Workouts

list_workouts()

Get Workout Details

get_workout("workout_id_here")

List Activities

Use the list_activities tool to view completed activities (runs, rides, swims, etc.) from Garmin Connect:

list_activities()

Optional parameters:

  • limit: Number of activities to return (default: 20)
  • start: Starting position for pagination (default: 0)
  • activityType: Filter by activity type (e.g., "running", "cycling", "swimming")
  • search: Search for activities containing specific text

Example with filters:

list_activities(limit=50, activityType="running", search="Marathon")

Get Activity Details

Use the get_activity tool to retrieve detailed information about a specific activity:

get_activity("activity_id_here")

Returns comprehensive activity data including distance, duration, pace, heart rate, and more.

Get Activity Weather

Use the get_activity_weather tool to get weather conditions during a specific activity:

get_activity_weather("activity_id_here")

Returns weather data including temperature, humidity, wind conditions, and weather descriptions.

Get Calendar Data

Use the get_calendar tool to view calendar data with workouts and activities:

get_calendar(2024, 7)  # Monthly view for July 2024
get_calendar(2024, 7, 15)  # Weekly view including July 15th

The tool supports various workout types:

  • Running: pace targets, distance/time based intervals
  • Cycling: power, cadence, speed targets
  • Swimming: time/distance based sets
  • Strength training: circuit-style workouts
  • General cardio: heart rate based training

Workout Description Examples

Creating New Workouts

  • "30min easy run at conversational pace"
  • "5km tempo run at 4:15 min/km pace"
  • "10 min warmup, 3x(20min at 280w, 5min at 150w), 10min cooldown"
  • "Swimming: 400m warmup, 8x(50m sprint, 30s rest), 400m cooldown"
  • "Strength circuit: 5x(30s pushups, 30s squats, 30s plank, 60s rest)"

Querying Activities

  • "Show me my last 10 running activities"
  • "Find all cycling activities from last month"
  • "What was the weather like during my morning run on July 4th?"
  • "Get details for my longest run this year"

Supported Activity Types

The list_activities tool supports filtering by the following activity types:

  • running, cycling, swimming, walking, hiking
  • fitness_equipment, multi_sport, yoga, diving
  • auto_racing, motorcycling, surfing, windsurfing
  • skiing variants: backcountry_skiing_snowboarding_ws, cross_country_skiing_ws, resort_skiing_snowboarding_ws, skate_skiing_ws
  • climbing variants: bouldering, indoor_climbing
  • specialized: breathwork, e_sport, safety
  • water_sports: offshore_grinding, onshore_grinding
  • other and winter_sports for general categorization

Environment Variables

  • GARMIN_EMAIL: Your Garmin Connect email address (optional)
  • GARMIN_PASSWORD: Your Garmin Connect password (optional)
  • GARTH_HOME: Custom location for Garmin credentials (optional, defaults to ~/.garth)

Credits

This project incorporates ideas and prompt designs inspired by openai-garmin-workout, which is licensed under the MIT License.

License

This project is licensed under the MIT License - see the LICENSE file for details.

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