TrainHeroic
БесплатноНе проверенAllows for management of TrainHeroic Athlete accounts via MCP and the unofficial API
Описание
Allows for management of TrainHeroic Athlete accounts via MCP and the unofficial API
README
TrainHeroic MCP server — connect TrainHeroic to Claude via the Model Context Protocol.
Give Claude (and other AI agents) direct access to your TrainHeroic workout data — history, exercise stats, personal records, and personal calendar — through the Model Context Protocol.
Built from the TrainHeroic mobile API (iOS app v8.25.0, endpoints captured via mitmproxy).
What you can do
Ask Claude things like:
- "What workouts did I do this week?"
- "What's my working max for back squat and how has it changed?"
- "Show me my bench press PRs by rep count."
- "Log today's session — I did 4×5 back squat at 225 lbs, RPE 8."
- "Create a personal session for tomorrow and add deadlifts and Romanian deadlifts."
- "How did I feel after Monday's workout? What was my energy and stress survey?"
- "Who's on the leaderboard for Tuesday's workout?"
Quick Start
Prerequisites: Python 3.12+ and uv
# 1. Clone and install
git clone https://github.com/cmagorian/trainheroicMcp
cd trainheroicMcp
make install
# 2. Add your credentials
cp .env.example .env
# Edit .env — see "Credentials" section below
# 3. Register with your AI client
make setup-claude # Claude Code
make setup-openclaw # OpenClaw
# See below for Claude Desktop and Cursor
Restart your AI client and ask: "What did I train this week?"
Credentials
Copy .env.example to .env and choose one of two methods:
Option A — Email + password (recommended)
[email protected]
TRAINHEROIC_PASSWORD=yourpassword
The server logs in on first start and caches the session token to ~/.config/trainheroic/session.json. Re-login is automatic when the token expires.
Option B — Session token
If you'd rather not store your password:
- Log in at trainheroic.com
- Open DevTools (
F12) → Network tab - Click any request to
api.trainheroic.com - Under Request Headers, copy the
session-tokenvalue
TRAINHEROIC_SESSION_TOKEN=<your-session-token>
Verify your credentials before registering:
make check-env # confirms .env is present and populated
make run # starts the server — look for "Ready — logged in as ..." on stderr
Registering with your AI client
Claude Code
make setup-claude
This registers the server in .claude/settings.json for this project. Credentials are loaded from .env automatically.
Run /mcp in Claude Code (or restart) to pick up the new server.
Claude Desktop
Open the config file for your OS:
| OS | Path |
|---|---|
| macOS | ~/Library/Application Support/Claude/claude_desktop_config.json |
| Windows | %APPDATA%\Claude\claude_desktop_config.json |
| Linux | ~/.config/Claude/claude_desktop_config.json |
Add the trainheroic entry — replace the path and credentials:
{
"mcpServers": {
"trainheroic": {
"command": "uv",
"args": [
"run",
"--directory", "/absolute/path/to/trainheroicMcp",
"python", "-m", "trainheroic_mcp.server"
],
"env": {
"TRAINHEROIC_EMAIL": "[email protected]",
"TRAINHEROIC_PASSWORD": "yourpassword"
}
}
}
}
Restart Claude Desktop after saving.
Cursor
Open Cursor Settings → MCP → Add new MCP server, or edit ~/.cursor/mcp.json directly:
{
"mcpServers": {
"trainheroic": {
"command": "uv",
"args": [
"run",
"--directory", "/absolute/path/to/trainheroicMcp",
"python", "-m", "trainheroic_mcp.server"
],
"env": {
"TRAINHEROIC_EMAIL": "[email protected]",
"TRAINHEROIC_PASSWORD": "yourpassword"
}
}
}
}
Restart Cursor after saving.
OpenClaw
make setup-openclaw
This registers the server in ~/.openclaw/openclaw.json. Restart OpenClaw to pick it up.
Example prompts
Checking history
What workouts did I complete last week?
Show me everything I trained in May.
Did I train on Monday?
Exercise stats and PRs
What's my current working max for back squat?
Show me my bench press PRs broken down by rep count.
What were my last 3 performances on Romanian deadlifts?
Logging a session
Create a personal session for today and add back squat, bench press, and cable rows.
Log my workout — I completed all sets. RPE was 7, rating 8 out of 10.
Surveys and recovery
What were my energy and stress scores after Tuesday's workout?
Submit my readiness survey: sleep was good, mood was great, energy was ok.
Social
Who's on the leaderboard for this week's main lift?
What comments are on today's workout?
Available tools
Core data
| Tool | What it does | Key params |
|---|---|---|
get_user_profile |
Name, ID, coach status | — |
get_team_info |
Teams, program IDs, coaches | — |
get_workout_history |
Workouts in a date range (flat summary by default) | start_date, end_date, weeks_back, include_sets |
get_workout_details |
Full sets + logged weights for one session | program_workout_id, program_id |
get_exercise_stats |
Last performance, PR, working max | exercise_id, stat_date |
get_personal_records |
All PRs by rep count | exercise_id |
get_working_max |
Current working max | exercise_id |
Tip:
get_workout_historyreturns compact summaries (date, title, rating, RPE, notes) by default. Passinclude_sets=Truefor set-level data on a 1–3 day window, or callget_workout_detailsfor a single session.
Exercise library
| Tool | What it does | Key params |
|---|---|---|
get_exercise_library |
Full library; filter by name | query (optional substring) |
get_circuit_library |
Full circuit library | — |
get_recent_exercises |
Recently used exercises | — |
get_recent_circuits |
Recently used circuits | — |
Personal calendar
| Tool | What it does | Key params |
|---|---|---|
create_personal_session |
Create a new session | session_date (YYYY-MM-DD) |
add_exercises_to_session |
Add exercises in order | workout_id, exercise_ids |
log_workout |
Save a completed workout | saved_workout_id, workout_id, date_string, blocks, notes, rpe, workout_rating |
delete_session |
Delete a session | program_workout_id |
Surveys & messaging
| Tool | What it does | Key params |
|---|---|---|
get_workout_surveys |
Sleep/mood/energy/soreness/stress data | saved_workout_ids |
submit_survey |
Answer a survey question | saved_workout_id, question_id, answer_id |
get_workout_messages |
Comments on a workout | program_workout_id |
get_workout_leaderboard |
Full leaderboard for a workout | program_workout_id |
Survey reference:
| Sleep | Mood | Energy | Soreness | Stress | |
|---|---|---|---|---|---|
question_id |
8 | 9 | 10 | 11 | 12 |
answer_id |
1 | 2 | 3 | 4 | 5 |
|---|---|---|---|---|---|
| Meaning | Awful | Poor | Ok | Good | Excellent |
Deploying online (access from any machine)
Host the server on Railway so any device running Claude Code, Claude Desktop, or OpenClaw can connect to it over HTTPS — no local Python install needed on the client.
Step 1 — Generate an auth token
make generate-token
# prints: MCP_AUTH_TOKEN=e5b7a8e3...
Copy the full line — you'll need it in Steps 2 and 3.
Step 2 — Deploy to Railway
- Push this repo to GitHub
- Go to railway.app → New Project → Deploy from GitHub repo
- Select the repository — Railway auto-detects the
Dockerfile - In Variables, add:
| Variable | Value |
|---|---|
MCP_TRANSPORT |
http |
TRAINHEROIC_EMAIL |
your email |
TRAINHEROIC_PASSWORD |
your password |
MCP_AUTH_TOKEN |
the token from Step 1 |
- Click Deploy. Railway assigns a URL like
https://trainheroicmcp-production.up.railway.app
Check the deploy logs for:
INFO [trainheroic-mcp] Ready — logged in as Your Name (team: Your Team)
INFO [trainheroic-mcp] HTTP transport — listening on 0.0.0.0:8000/mcp
Step 3 — Connect from any machine
Replace YOUR_URL with your Railway URL and YOUR_TOKEN with the token from Step 1.
Claude Code:
claude mcp add \
--transport http \
--header "Authorization: Bearer YOUR_TOKEN" \
trainheroic \
https://YOUR_URL/mcp
Claude Desktop / Cursor (claude_desktop_config.json or ~/.cursor/mcp.json):
{
"mcpServers": {
"trainheroic": {
"type": "http",
"url": "https://YOUR_URL/mcp",
"headers": {
"Authorization": "Bearer YOUR_TOKEN"
}
}
}
}
OpenClaw:
openclaw mcp set trainheroic \
'{"type":"http","url":"https://YOUR_URL/mcp","headers":{"Authorization":"Bearer YOUR_TOKEN"}}'
Test the connection:
curl -s \
-H "Authorization: Bearer YOUR_TOKEN" \
-H "Content-Type: application/json" \
https://YOUR_URL/mcp
# Should return an MCP protocol response, not 401
Run HTTP transport locally (before deploying):
MCP_AUTH_TOKEN=test-token make run-http
# Server starts on http://localhost:8000/mcp
Troubleshooting
| Symptom | Likely cause | Fix |
|---|---|---|
No TrainHeroic credentials found |
.env missing or empty |
cp .env.example .env and add credentials |
401 Unauthorized on startup |
Expired or invalid token | Delete ~/.config/trainheroic/session.json and restart; the server re-logs in |
401 from get_workout_details |
Wrong team resolved | Pass program_id from the get_workout_history item alongside program_workout_id |
| Server starts but Claude can't find it | Not registered or client not restarted | Re-run make setup-claude and restart Claude |
| Responses seem incomplete | Date range too wide | Use 1–2 week windows; call get_workout_details per session for set data |
Known limitations
| Feature | Reason unavailable |
|---|---|
| Lift goals | Requires Athlete Pro subscription |
| Nutrition calendar | Requires Athlete Pro subscription |
| Program listing | Coach accounts only |
| Data export | Backend returns 504 timeout |
Development
Running tests
No credentials needed — all HTTP is intercepted by pytest-httpx.
make test # quiet summary
make test-v # verbose, one line per test
uv run pytest -k "TestLogin" # single class
uv run pytest tests/test_client.py # single file
Project structure
src/trainheroic_mcp/
├── client.py # TrainHeroicClient — auth, token cache, HTTP helpers
└── server.py # FastMCP server — 19 tool definitions, response projectors
tests/
├── conftest.py # fixtures: cache isolation (autouse), th_client, patched_server
├── helpers.py # shared constants + add_init_responses helper
├── test_client.py # init, login, token cache, HTTP helpers
└── test_tools.py # one test class per tool
Adding a new tool
- Add the function to
server.pywith@mcp.tool(). - Add a test class to
tests/test_tools.pyusing thepatched_serverfixture.
# server.py
@mcp.tool()
def get_athlete_pro_status() -> dict:
"""Check whether the user has an active Athlete Pro subscription."""
return _get_client()._get("/v5/athletePro/access")
# tests/test_tools.py
class TestGetAthleteProStatus:
def test_calls_correct_endpoint(self, patched_server, httpx_mock):
httpx_mock.add_response(
method="GET",
url=f"{BASE}/v5/athletePro/access",
json={"hasAthleteProAccess": False},
)
result = server.get_athlete_pro_status()
assert result["hasAthleteProAccess"] is False
Установка TrainHeroic
У этого сервера нет опубликованного пакета — он собирается из исходников. Открой репозиторий и следуй инструкции в README.
▸ github.com/cmagorian/trainheroicMcpFAQ
TrainHeroic MCP бесплатный?
Да, TrainHeroic MCP бесплатный — установка в пару кликов через Unyly без оплаты.
Нужен ли API-ключ для TrainHeroic?
Нет, TrainHeroic работает без API-ключей и переменных окружения.
TrainHeroic — hosted или self-hosted?
Доступен hosted-вариант: Unyly запускает сервер в облаке, локальная установка не обязательна.
Как установить TrainHeroic в Claude Desktop, Claude Code или Cursor?
Открой TrainHeroic на unyly.org, выбери вкладку своего клиента (Claude Desktop, Claude Code, Cursor) и нажми Install — конфиг сгенерируется автоматически, без правки JSON.
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