training-mcp

MCP server for training data — Strava activities, intervals.icu wellness and analytics, HRV4Training metrics, and cross-source correlations. Consolidates three separate servers (strava-mcp, intervals-mcp, analytics-mcp) into one process.

Tools

Strava (strava_*)

• strava_list_activities, strava_get_activity, strava_get_activity_laps, strava_get_activity_streams, strava_get_activity_zones, strava_get_activity_comments, strava_get_activity_kudos, strava_update_activity
• strava_get_athlete, strava_get_athlete_stats, strava_get_athlete_zones
• strava_get_gear, strava_list_athlete_gear, strava_get_gear_maintenance_status
• strava_list_routes, strava_get_route, strava_get_route_streams
• strava_get_segment, strava_get_segment_effort, strava_list_segment_efforts, strava_list_starred_segments, strava_get_activity_segment_efforts

intervals.icu (intervals_*)

• intervals_list_activities, intervals_search_activities, intervals_search_activities_full, intervals_interval_search_activities, intervals_get_activities_by_ids
• intervals_get_activity, intervals_update_activity, intervals_delete_activity
• intervals_get_activity_streams, intervals_get_activity_intervals, intervals_get_activity_interval_stats
• intervals_get_activity_best_efforts, intervals_get_activity_power_curve, intervals_get_activity_hr_curve, intervals_get_activity_pace_curve
• intervals_get_activity_power_histogram, intervals_get_activity_hr_histogram, intervals_get_activity_pace_histogram, intervals_get_activity_power_vs_hr, intervals_get_activity_time_at_hr
• intervals_get_activity_map, intervals_get_activity_weather, intervals_get_activity_segments
• intervals_get_activity_messages, intervals_post_activity_message
• intervals_get_athlete
• intervals_list_wellness, intervals_get_wellness, intervals_update_wellness, intervals_bulk_update_wellness, intervals_wellness_trend_alert
• intervals_create_workout, intervals_create_workouts_bulk, intervals_list_events

HRV4Training

• get_hrv_data — daily HRV metrics, sleep, and subjective wellness markers from a local CSV or Dropbox

Analytics

• correlate_hrv_with_performance — HRV vs normalized power and HR efficiency (Pearson r)
• training_load_vs_sleep — CTL/ATL/form vs sleep score (Pearson r)
• fitness_vs_segment_prs — CTL/ATL/form vs Strava segment effort times (Pearson r)

Setup

1. Create the conda environment

conda env create -f environment.yml
conda activate training-mcp

2. Configure credentials

cp .env.example .env

Fill in .env:

Variable	Where to find it
STRAVA_CLIENT_ID / STRAVA_CLIENT_SECRET	Strava API settings
INTERVALS_ATHLETE_ID	intervals.icu URL: /athlete/iXXXXXX/...
INTERVALS_API_KEY	intervals.icu Settings → API
DROPBOX_APP_KEY / DROPBOX_APP_SECRET	Dropbox App Console

3. Authorize Strava

conda activate training-mcp
python auth_strava.py

A browser window opens. Authorize, and tokens are written to .env automatically. Tokens refresh automatically on expiry — you only need to run this once.

4. Authorize Dropbox (if using HRV via Dropbox)

python auth_dropbox.py

Same flow — browser opens, tokens saved to .env.

Alternative: Set HRV4TRAINING_CSV_DIR in .env to a local directory containing HRV4Training CSV exports, and skip Dropbox entirely.

5. Configure Claude Desktop

Add to claude_desktop_config.json:

"training": {
  "command": "/path/to/miniconda3/envs/training-mcp/bin/python",
  "args": ["/path/to/training-mcp/server.py"]
}

Project structure

training-mcp/
├── app.py                 — FastMCP instance
├── server.py              — entry point
├── client_strava.py       — Strava HTTP client + token refresh
├── client_intervals.py    — intervals.icu HTTP client
├── client_dropbox.py      — HRV CSV reader (local dir or Dropbox)
├── auth_strava.py         — one-time Strava OAuth flow
├── auth_dropbox.py        — one-time Dropbox OAuth flow
├── requirements.txt
├── environment.yml
├── .env.example
└── routers/
    ├── strava/            — activities, athlete, gear, routes, segments
    ├── intervals/         — activities, athlete, events, hrv, wellness
    └── analytics/         — cross-source correlations