Model Context Protocol server for the Hevy workout-tracking API.
Project description
hevy-mcp
Connect Claude to your Hevy workout log.
hevy-mcp is a Model Context Protocol server that lets Claude (Desktop or claude.ai) read your workouts, design new routines, save them to your Hevy library, and analyze your training trends — the same kind of access ChatGPT users get from Hevy's official integration.
You: "Build me a 4-day upper/lower hypertrophy split focused on the muscle groups
I've trained least over the last 30 days, and save it in a folder called
'Hypertrophy Block 1'."
Claude: ✓ checked your last 30 days of training (lats and rear delts are behind)
✓ created folder "Hypertrophy Block 1"
✓ resolved 22 exercises against Hevy's library
✓ saved 4 routines: Upper A, Lower A, Upper B, Lower B
Open the Hevy app to start any of them.
What you can ask Claude to do
- Look back — "Show me my last 10 workouts and tell me which muscle groups I've been neglecting."
- Plan ahead — "Based on my bench press history, what's a good top set for tomorrow?"
- Build routines — "Build me a 4-day upper/lower hypertrophy split and save it."
- Edit routines — "On 'Push Day A', swap dumbbell shoulder press for a barbell overhead press, 4 sets of 5."
- Analyze — "Estimate my 1RM on the main lifts and chart squat progression over the last 90 days."
Requirements
- A Hevy PRO subscription (the developer API requires it).
- Your Hevy API key — get it at https://hevy.com/settings?developer.
- Either Python 3.11+ or Docker.
- Claude Desktop, or a claude.ai workspace that supports custom connectors.
Quick start — Claude Desktop (5 minutes)
1. Install
# Easiest, with uv (https://docs.astral.sh/uv/):
uv tool install hevy-mcp
# Or with pipx:
pipx install hevy-mcp
# Or with plain pip:
python -m pip install hevy-mcp
2. Add it to Claude Desktop
Open Claude Desktop's config file:
- 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 hevy entry under mcpServers (create the file if it doesn't exist):
{
"mcpServers": {
"hevy": {
"command": "hevy-mcp",
"env": {
"HEVY_API_KEY": "sk_live_paste_your_key_here"
}
}
}
}
If
hevy-mcpisn't on your PATH (uv-tool installs sometimes aren't picked up by the Claude Desktop launcher), use the absolute path you get fromwhich hevy-mcp— for example/Users/you/.local/bin/hevy-mcp.
3. Restart Claude Desktop
Quit fully (⌘Q on macOS) and reopen. You should see a tools indicator showing the hevy server is connected.
4. Try it
"Use the hevy tool to fetch my last 3 workouts and summarize them."
If Claude shows your real workouts, you're done. 🎉
Alternative — claude.ai (remote connector)
If you use claude.ai in the browser instead of Claude Desktop, run hevy-mcp as an HTTP service and add it as a custom connector.
1. Run the server somewhere with HTTPS
The simplest path is Docker on Fly.io / Render / Railway:
docker build -t hevy-mcp .
docker run --rm -p 8000:8000 -e HEVY_API_KEY=sk_live_... hevy-mcp
Or directly with the CLI:
hevy-mcp --http --host 0.0.0.0 --port 8000
The MCP endpoint is at /mcp.
2. Add it as a custom connector
In claude.ai, go to Settings → Connectors → Add custom connector and use your public HTTPS URL ending in /mcp (e.g. https://hevy-mcp.fly.dev/mcp).
Multi-user note
If multiple users will share the same deployment, don't bake HEVY_API_KEY into the container env — instead, send it as a per-request header. The server reads X-Hevy-Api-Key if present and falls back to the env var. A small auth-injecting reverse proxy (Cloudflare Worker, Nginx) in front of the server is the usual pattern.
What it can do (full tool list)
| Group | Tool | What it does |
|---|---|---|
| Workouts | list_workouts |
Page through your workout history, newest first. |
get_workout |
Full detail of one workout — every set, rep, weight, RPE, note. | |
get_workout_count |
Total workouts logged. | |
get_workout_events |
Stream of created/updated/deleted events since a timestamp. | |
create_workout |
Log a completed workout. | |
update_workout |
Edit an already-logged workout. | |
| Routines | list_routines, get_routine |
Read your saved routines. |
create_routine |
Save a new routine (with duplicate-title protection). | |
update_routine |
Modify an existing routine. | |
| Folders | list_routine_folders, get_routine_folder, create_routine_folder |
Organize routines. |
| Exercise library | search_exercise_templates |
Fuzzy search Hevy's ~400-exercise library by name, equipment, or muscle. |
list_exercise_templates, get_exercise_template |
Browse/look up exercises. | |
| Webhooks | create_webhook_subscription, get_webhook_subscription, delete_webhook_subscription |
One subscription per key (Hevy limit). |
| Analytics | estimate_one_rep_max |
Epley/Brzycki e1RM from your top working sets. |
volume_by_muscle_group |
Tonnage per muscle group over a window. | |
progression_trend |
e1RM-vs-time series for a single lift, with weekly slope. |
Under the hood:
- Smart caching — the exercise library is fetched once and cached for 24 hours; fuzzy search runs in memory.
- Rate-limit aware — backs off on 429s and honors
Retry-After. - Idempotent writes — creating a routine with a duplicate title in the same folder asks Claude to confirm before doubling.
- LLM-friendly errors — every error comes back as
{ error, hint }. The hint suggests the next concrete tool call. - Never logs your API key.
Troubleshooting
Claude Desktop says the server "disconnected" right after starting
Most common cause: the command in claude_desktop_config.json isn't on the launcher's PATH. Replace "command": "hevy-mcp" with the absolute path from which hevy-mcp (or where hevy-mcp on Windows). Restart Claude Desktop.
Tool calls fail with "HEVY_API_KEY is missing or invalid"
- Check that you pasted the key into the
envblock (not theargsblock). - Confirm your Hevy PRO subscription is active.
- Rotate your key at https://hevy.com/settings?developer and try again.
Claude can't find the right exercise when creating a routine
search_exercise_templates is fuzzy but not magic. If Claude picks the wrong exercise, ask it to "search again with a more specific name" or pass an equipment filter (e.g. "barbell").
It's slow on the first call
The exercise library is fetched on the first lookup (one-time, ~200ms). Every call after that hits the in-memory cache. The cache lasts 24 hours.
Development
git clone https://github.com/Vellarasan/hevy-mcp.git
cd hevy-mcp
uv sync --extra dev # creates .venv and installs deps
pytest -q # offline tests (no real API needed)
# Run against your real Hevy account:
HEVY_API_KEY=sk_live_... python smoke_test.py
# Stdio (Claude Desktop):
hevy-mcp
# HTTP (claude.ai):
hevy-mcp --http --port 8000
See CONTRIBUTING.md for the longer version.
Project layout
hevy-mcp/
├── src/hevy_mcp/
│ ├── server.py # transport bootstrap (stdio + streamable-http)
│ ├── hevy_client.py # async httpx client w/ retries & error mapping
│ ├── schemas.py # Pydantic models
│ ├── cache.py # 24-hour TTL cache
│ ├── errors.py # HevyApiError + tool_guard
│ ├── formatters.py # JSON → readable text
│ └── tools/ # workouts, routines, folders, templates, webhooks, analytics
├── tests/
└── Dockerfile
Releases
See CHANGELOG.md. Tagged releases publish to PyPI automatically.
License
MIT.
Thanks
This project's design owes ideas to two earlier community implementations: chrisdoc/hevy-mcp (TypeScript) and SrdjanCodes/hevy-mcp (Python). Not a fork — but worth a look if you want a different language or feature mix.
hevy-mcp is a community project and is not affiliated with or endorsed by Hevy.
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