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-mcp isn't on your PATH (uv-tool installs sometimes aren't picked up by the Claude Desktop launcher), use the absolute path you get from which 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)

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

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.

• Check that you pasted the key into the env block (not the args block).

• Confirm your Hevy PRO subscription is active.

• Rotate your key at https://hevy.com/settings?developer and try again.

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").

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.