Skillget

trainingpeaks-mcp

mcp
SUMMARY

TrainingPeaks MCP server for Claude Desktop, Code and Cowork. No API approval needed - works with any account. Query workouts, CTL/ATL/TSB fitness data, power PRs via natural language.

README.md

TrainingPeaks MCP Server

TrainingPeaks MCP server

Connect TrainingPeaks to Claude and other AI assistants via the Model Context Protocol (MCP). Query workouts, build structured intervals, manage your calendar, track fitness trends, and control your training through natural conversation.

No API approval required. The official Training Peaks API is approval-gated, but this server uses secure cookie authentication that any user can set up in minutes. Your cookie is stored in your system keyring, never transmitted anywhere except to TrainingPeaks.

What You Can Do

Example conversation with Claude using TrainingPeaks MCP

Ask your AI assistant things like:

  • "Build me a 4x8min threshold session for Tuesday with warm-up and cool-down"
  • "Compare my FTP progression this year vs last year"
  • "Copy last week's long ride to this Saturday"
  • "Log my weight at 74.5kg and sleep at 7.5 hours"
  • "What's my weekly TSS so far? Am I on track for my ATP target?"
  • "Show my race calendar and how many weeks until my A race"
  • "Set my FTP to 310 and update my power zones"
  • "Add a calendar note for next Monday: rest day, travel"

Tools (52)

Workouts

Tool Description
tp_get_workouts List workouts in a date range (max 90 days)
tp_get_workout Get full details for a single workout
tp_create_workout Create a workout with optional interval structure, auto-computed IF/TSS
tp_update_workout Update any field of an existing workout
tp_delete_workout Delete a workout
tp_copy_workout Copy a workout to a new date (preserves structure and planned fields)
tp_reorder_workouts Reorder workouts on a given day
tp_validate_structure Validate interval structure without creating a workout
tp_get_workout_comments Get comments on a workout
tp_add_workout_comment Add a comment to a workout

Analysis & Performance

Tool Description
tp_analyze_workout Detailed analysis with time-series data, zones, and laps
tp_get_peaks Power PRs (5s-90min) and running PRs (400m-marathon)
tp_get_workout_prs PRs set during a specific session
tp_get_fitness CTL, ATL, and TSB trend (fitness, fatigue, form)
tp_get_weekly_summary Combined workouts + fitness for a week with totals
tp_get_atp Annual Training Plan - weekly TSS targets, periods, races

Athlete Settings

Tool Description
tp_get_athlete_settings Get FTP, thresholds, zones, profile
tp_update_ftp Update FTP and recalculate Coggan 5-zone model
tp_update_hr_zones Update heart rate zones
tp_update_speed_zones Update run/swim pace zones
tp_update_nutrition Update daily planned calories
tp_get_pool_length_settings Get pool length options

Health Metrics

Tool Description
tp_log_metrics Log weight, HRV, sleep, steps, SpO2, pulse, RMR, injury
tp_get_metrics Get health metrics for a date range
tp_get_nutrition Get nutrition data for a date range

Equipment

Tool Description
tp_get_equipment List bikes and shoes with distances
tp_create_equipment Add a bike or shoe
tp_update_equipment Update equipment details, retire
tp_delete_equipment Delete equipment

Events & Calendar

Tool Description
tp_get_focus_event Get A-priority focus event with goals
tp_get_next_event Get nearest future event
tp_get_events List events in a date range
tp_create_event Add a race/event with priority (A/B/C) and CTL target
tp_update_event Update event details
tp_delete_event Delete an event
tp_create_note Create a calendar note
tp_delete_note Delete a calendar note
tp_get_availability List unavailable/limited periods
tp_create_availability Mark dates as unavailable or limited
tp_delete_availability Remove availability entry

Workout Library

Tool Description
tp_get_libraries List workout library folders
tp_get_library_items List templates in a library
tp_get_library_item Get full template details including structure
tp_create_library Create a library folder
tp_delete_library Delete a library folder
tp_create_library_item Save a workout template
tp_update_library_item Edit a template
tp_schedule_library_workout Schedule a template to a calendar date

Reference & Auth

Tool Description
tp_get_workout_types List all sport types and subtypes with IDs
tp_get_profile Get athlete profile
tp_auth_status Check authentication status
tp_refresh_auth Re-authenticate from browser cookie

Setup Options

Option A: Auto-Setup with Claude Code

If you have Claude Code, paste this prompt:

Set up the TrainingPeaks MCP server from https://github.com/JamsusMaximus/trainingpeaks-mcp - clone it, create a venv, install it, then walk me through getting my TrainingPeaks cookie from my browser and run tp-mcp auth. Finally, add it to my Claude Desktop config.

Claude will handle the installation and guide you through authentication step-by-step.

Option B: Manual Setup

Step 1: Install

git clone https://github.com/JamsusMaximus/trainingpeaks-mcp.git
cd trainingpeaks-mcp
python3 -m venv .venv
source .venv/bin/activate  # Windows: .venv\Scripts\activate
pip install -e .

Step 2: Authenticate

Option A: Auto-extract from browser (easiest)

If you're logged into TrainingPeaks in your browser:

pip install tp-mcp[browser]  # One-time: install browser support
tp-mcp auth --from-browser chrome  # Or: firefox, safari, edge, auto

macOS note: You may see security prompts for Keychain or Full Disk Access. This is normal - browser cookies are encrypted and require permission to read.

Option B: Manual cookie entry

  1. Log into app.trainingpeaks.com
  2. Open DevTools (F12) -> Application tab -> Cookies
  3. Find Production_tpAuth and copy its value
  4. Run tp-mcp auth and paste when prompted

Other auth commands:

tp-mcp auth-status  # Check if authenticated
tp-mcp auth-clear   # Remove stored cookie

Step 3: Add to Claude Desktop

Run this to get your config snippet:

tp-mcp config

Edit ~/Library/Application Support/Claude/claude_desktop_config.json (macOS) or %APPDATA%\Claude\claude_desktop_config.json (Windows) and paste it inside mcpServers. Example with multiple servers:

{
  "mcpServers": {
    "some-other-server": {
      "command": "npx",
      "args": ["some-other-mcp"]
    },
    "trainingpeaks": {
      "command": "/Users/you/trainingpeaks-mcp/.venv/bin/tp-mcp",
      "args": ["serve"]
    }
  }
}

Restart Claude Desktop. You're ready to go!

Structured Workouts

Create workouts with full interval structure. The server auto-computes duration, IF, and TSS from the structure:

{
  "date": "2026-03-01",
  "sport": "Bike",
  "title": "Sweet Spot Intervals",
  "structure": {
    "primaryIntensityMetric": "percentOfFtp",
    "steps": [
      {"name": "Warm Up", "duration_seconds": 600, "intensity_min": 40, "intensity_max": 55, "intensityClass": "warmUp"},
      {"type": "repetition", "reps": 4, "steps": [
        {"name": "Sweet Spot", "duration_seconds": 480, "intensity_min": 88, "intensity_max": 93, "intensityClass": "active"},
        {"name": "Recovery", "duration_seconds": 120, "intensity_min": 50, "intensity_max": 60, "intensityClass": "rest"}
      ]},
      {"name": "Cool Down", "duration_seconds": 600, "intensity_min": 40, "intensity_max": 55, "intensityClass": "coolDown"}
    ]
  }
}

The LLM builds this JSON naturally from conversation - just say "build me 4x8min sweet spot with 2min rest".

What is MCP?

Model Context Protocol is an open standard for connecting AI assistants to external data sources. MCP servers expose tools that AI models can call to fetch real-time data, enabling assistants like Claude to access your Training Peaks account through natural language.

Security

TL;DR: Your cookie is encrypted on disk, exchanged for short-lived OAuth tokens, never shown to Claude, and only ever sent to TrainingPeaks. The server has no network ports.

This server is designed with defence-in-depth. Your TrainingPeaks session cookie is sensitive - it grants access to your training data - so we treat it accordingly.

Write access: v2.0 adds full calendar management (create, update, delete workouts, events, notes, equipment, settings). All mutations go through Pydantic validation. The server cannot access billing or payment info.

Cookie Storage

Platform Primary Storage Fallback
macOS System Keychain Encrypted file
Windows Windows Credential Manager Encrypted file
Linux Secret Service (GNOME/KDE) Encrypted file

Your cookie is never stored in plaintext. The encrypted file fallback uses AES-256-GCM authenticated encryption with a PBKDF2-derived key (600,000 iterations) and a machine-specific salt.

Cookie Never Leaks to AI

The AI assistant (Claude) never sees your cookie value. Multiple layers ensure this:

  1. Return value sanitisation: Tool results are scrubbed for any keys containing cookie, token, auth, credential, password, or secret before being sent to Claude
  2. Masked repr(): The BrowserCookieResult and CredentialResult classes override __repr__ to show cookie=<present> instead of the actual value
  3. Sanitised exceptions: Error messages use only exception type names, never full messages that could contain data
  4. No logging: Cookie values are never written to any log

Domain Hardcoding (Cannot Be Changed)

The browser cookie extraction only accesses .trainingpeaks.com:

# From src/tp_mcp/auth/browser.py - HARDCODED, not a parameter
cj = func(domain_name=".trainingpeaks.com")

Claude cannot modify this via tool parameters. The only parameter is browser (chrome/firefox/etc), not the domain. To change the domain would require modifying the source code.

No Network Exposure

The MCP server uses stdio transport only - it communicates with Claude Desktop via stdin/stdout, not over the network. There is no HTTP server, no open ports, no remote access.

Open Source

This server is fully open source. You can audit every line of code before running it. Key security files:

Authentication Flow

The server uses a two-step authentication process:

  1. Cookie to OAuth Token: Your stored cookie is exchanged for a short-lived OAuth access token (expires in 1 hour)
  2. Automatic Refresh: Tokens are cached in memory and automatically refreshed before expiry

This means:

  • You only need to authenticate once with tp-mcp auth
  • API calls use proper Bearer token auth, not cookies
  • If your session cookie expires (typically after several weeks), use tp_refresh_auth in Claude or run tp-mcp auth again

Development

pip install -e ".[dev]"
pytest tests/ -v
mypy src/
ruff check src/

Licence

MIT

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