fitness-mcp

A personal remote MCP (Model Context Protocol) server that lets Claude read your Hevy workout data and MacroFactor nutrition data directly in conversation. Deployed on Vercel's free Hobby tier.

Status

• Hevy: implemented (read-only: recent workouts, workout detail, body measurements). Uses the official Hevy REST API directly.
• MacroFactor: implemented, but indirectly. MacroFactor's backend enabled Firebase App Check enforcement in May 2026, which blocks all third-party API access — there is no legitimate way to pull MacroFactor data live. Instead, this server reads the Google Sheets files produced by MacroFactor's manual "Granular Export" feature, which the user saves into a "Health data" Drive folder. Every MacroFactor tool call lazily syncs any newly exported files first, so a fresh manual export becomes visible to Claude on the very next question — no separate trigger/webhook needed.

Tools exposed

Tool	Description
get_recent_workouts	List recent Hevy workouts (title, time, exercises)
get_workout_detail	Full sets/reps/weight detail for one workout
get_body_measurements	Recent Hevy body measurement entries (weight, body fat %)
get_daily_macros	Daily calories/protein/carbs/fat/steps from MacroFactor exports
get_weight_trend	Daily weight, MacroFactor's smoothed weight trend, and body fat %
get_nutrition_trends	Precomputed monthly/yearly averages and weight change (cheap — reads a precomputed rollup, not raw daily data)

All tools are read-only.

How the MacroFactor sync works

MacroFactor has no usable API, so data instead flows: MacroFactor app → manual "Granular Export" → Google Drive folder "Health data" → this server reads it on demand.

• Each export creates a new MacroFactor-<timestamp> Google Sheet in that folder (never overwritten). Export date ranges can overlap or have gaps — the sync does not assume the latest file has full history.
• On every MacroFactor tool call, the server checks the Drive folder for export files it hasn't processed yet, merges any new ones into a small JSON store (Health data/_store/daily-summary.json), and recomputes precomputed monthly/yearly rollups for just the affected periods.
• If nothing new was exported since the last call, this is a fast no-write no-op — repeated questions ("how's my year going?") don't re-scan or re-download anything.
• When two exports cover the same date, the more recently exported one wins (compared by the timestamp encoded in the file name), regardless of Drive's file ordering.

Setting up Google Drive access (one-time)

1. Create or select a Google Cloud project.
2. Enable the Google Drive API and Google Sheets API for it.
3. Create a Service Account (IAM & Admin → Service Accounts). No IAM roles needed.
4. Create and download a JSON key for the service account.
5. Base64-encode it: base64 -w0 key.json
6. Set the result as the GOOGLE_SERVICE_ACCOUNT_KEY_BASE64 env var (see below).
7. In Google Drive, share the "Health data" folder with the service account's email (the client_email field in the JSON key) as Editor — the app creates and writes to a _store subfolder inside it.
8. No domain-wide delegation needed — this is a personal Gmail account, a plain folder share is enough.

Local development

npm install
cp .env.example .env.local   # fill in real values
vercel dev

Smoke test (replace $MCP_BEARER_TOKEN):

curl -X POST http://localhost:3000/api/mcp \
  -H "Authorization: Bearer $MCP_BEARER_TOKEN" \
  -H "Content-Type: application/json" \
  -H "Accept: application/json, text/event-stream" \
  -d '{"jsonrpc":"2.0","id":1,"method":"tools/list"}'

Should return the 6 tools above. A request with a missing/wrong token should get 401.

Environment variables

Variable	Purpose
HEVY_API_KEY	Hevy Pro API key from https://hevy.com/settings?developer
MCP_BEARER_TOKEN	Shared secret this server requires on every request. Generate with openssl rand -hex 32
GOOGLE_SERVICE_ACCOUNT_KEY_BASE64	Base64-encoded service-account JSON key with Drive/Sheets access to the "Health data" folder — see setup steps above

Set these in the Vercel project's Environment Variables (Production + Preview). Never commit real values — .env.example only documents the names.

Deploy

1. vercel link
2. vercel env add HEVY_API_KEY / vercel env add MCP_BEARER_TOKEN / vercel env add GOOGLE_SERVICE_ACCOUNT_KEY_BASE64 (repeat for each environment you use)
3. Connect this GitHub repo in the Vercel dashboard for auto-deploy on push to main, or run vercel --prod manually.
4. Note the deployed URL, e.g. https://fitness-mcp.vercel.app/api/mcp.

Connect to Claude

Custom connectors can only be added from claude.ai (web) or the desktop app — not from the mobile app. Once added there, they're usable from mobile automatically.

1. On claude.ai: Settings → Connectors → Add custom connector.
2. Name: Fitness Data. URL: https://fitness-mcp.vercel.app/api/mcp.
3. Under "Request headers", add Authorization: Bearer <MCP_BEARER_TOKEN> (the same value set in Vercel).
4. Save. Claude should list the 6 tools above.

Try asking: "直近のワークアウトを教えて" (tell me about my recent workouts) or "今月の平均カロリーは?" (what's my average calorie intake this month?).