AIm

A workout tracker your AI assistant writes to. AIm is an MCP server plus a mobile web app (PWA): you describe a session in Claude or ChatGPT in your own words, the assistant logs it through MCP, and the app shows the program, the history, records, estimated 1RM and per muscle load. The coaching prompts live on the server, so the assistant plans from your logged weights instead of generic advice.

Live at aim-journal.com. Free, and it runs inside the AI subscription you already pay for rather than being a second one. Guides: connect a workout tracker over MCP, AI personal trainer, 1RM calculator.

How it works

There are two ways in, on the same host, and both resolve to the same user_id:

https://<app>/mcp                OAuth 2.1 — add as a connector, approve in the browser
https://<app>/{token}            mobile web app / installable PWA
https://<app>/{token}/mcp        the original connector address, still supported
https://<app>/{token}/api/*      read only JSON the UI consumes

OAuth is what a connector uses now. The server is an OAuth 2.1 resource server: an unauthenticated call gets a 401 carrying RFC 9728 protected-resource metadata, the client discovers the authorization server from it, registers itself dynamically, and the user approves on a consent screen this app serves. Supabase Auth is the authorization server, so no authorization codes or access tokens are stored here; the access token's sub is mapped to an account through users.supabase_user_id. Nothing secret is pasted by hand.

The URL token predates it and still works, which is why every link already in someone's inbox kept working when OAuth landed. A token resolver middleware maps the leading path segment to a user and scopes every query by user_id; the OAuth path sets the same context variable from a verified token instead. Two doors, one scoping rule.

Related MCP server: aiTrainer

What the MCP server exposes

20 tools over stateless streamable HTTP (FastMCP):

• Logging: log_session, update_session, update_set, delete_session, import_document (paste an export from another tracker or a photo of a notebook page).

• Reading: get_sessions, get_session, get_stats (volume, progression, estimated 1RM via Epley), get_program, get_goals, get_body_metrics.

• Catalogue: search_exercise_pool (a curated global pool with illustrations), list_exercises, upsert_exercise.

• Coaching: get_coaching_context is the important one. It returns this user's goal, experience, equipment, injuries and recent loads together with the prompt for the task at hand (next workout, new program, weekly review), so the assistant plans from data rather than from nothing. review_program_draft, update_coach_profile, upsert_goal, log_coach_event, log_body_metric keep that context current.

Repo layout

api/index.py      Vercel entrypoint (must stay at repo root, see below). Imports backend/src.
requirements.txt  Vercel's Python build reads this (must also stay at repo root).
backend/          Python package, tests, scripts, DB migrations.
web/              Vite + React SPA (own package.json, own dev server) and the static guide pages.

api/index.py and requirements.txt cannot move: Vercel's zero config Python builder only auto detects functions under a root level api/, and only installs a root level requirements.txt alongside them. Everything else in backend/ (pyproject.toml, uv.lock, tests, scripts, supabase/) is hidden from the Vercel build by .vercelignore, so Vercel treats the repo as a static SPA plus one Python function.

One thing to know before you go reading: some code comments cite internal planning documents by path, such as docs/COACHING_PLAN.md, docs/TEST_CASES.md or docs/DEPLOYMENT.md. Those are product and research notes that are not published here, so the paths will not resolve. Nothing in the code depends on them; they are provenance for a decision, not a dependency. Everything you need to build, test and run what is in this repository is in this README.

Stack

• Backend (backend/): Python 3.12, FastMCP (stateless HTTP), psycopg3, Supabase Postgres (transaction pooler). MCP and the read API live in backend/src/workout_storage/, served by api/index.py.

• Frontend (web/): Vite, React, Tailwind v4, shadcn/ui, recharts, React Query, vite-plugin-pwa. Data layer in web/src/app/lib/ (token to api to adapter to hooks). The guide pages under web/guides/ are generated to static HTML at build time and ship no bundle.

• Hosting: one Vercel project. vercel.json routes mcp, api and cron to the function and everything else to the SPA.

Frontend dev

cd web
npm install
echo 'VITE_API_ORIGIN=https://workout-storage.vercel.app' > .env.local  # dev against prod API
npm run dev              # http://localhost:5173/{token}
npm run test             # vitest: pure function + component tests
npx playwright install chromium   # one time, before the first test:e2e run
npm run test:e2e         # Playwright, against /demo (no backend needed)

Backend dev

cd backend
uv sync --extra dev           # install deps
cp ../.env.example ../.env     # fill DATABASE_URL etc. (kept at repo root, shared by all tooling)
uv run pytest                  # unit + integration + e2e
uv run ruff check . && uv run mypy .

Create a user (prints the token to open in the browser and to paste into an assistant):

cd backend
uv run python scripts/create_user.py --name "Alex"

Running your own

Everything needed is here, but this is the source of a hosted service rather than a turnkey self host kit: you supply a Supabase project (migrations in backend/supabase/migrations/), a Vercel project, and the environment variables listed in .env.example. Analytics, email and backup integrations are optional and stay dormant without their keys.

Attribution

Exercise illustrations are third party works under CC BY-SA, each credited in web/ATTRIBUTIONS.md. They keep their own license regardless of the license on this repository.

License

MIT, see LICENSE. The exercise illustrations are the one exception, see Attribution above.