morsel

morsel

Enables logging food meals by letting AI assistants analyze food photos and write structured meal data via MCP tools to a shared store, which can then be viewed in a dashboard.

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README

Morsel

The storehouse your AI fills. Morsel is a MCP-first, camera-first food tracker. There is no chat inside the app — you log by chatting with your existing assistant (Claude, ChatGPT) and uploading a photo; the assistant's agent reads the photo, calls Morsel's MCP tools, and writes structured food data to your store. Morsel is the data store + dashboard + agent skill; the intelligence lives in the agent you already use.

Why this exists

People chat with Claude/ChatGPT every day but can't keep context or structured data. Generic calorie apps re-implement their own AI, locked inside a silo.

Morsel flips it:

  • No in-app chat. The app has no AI brain and no chat UI.
  • MCP-first. The app is a Model Context Protocol server + a data store. Your agent connects over MCP and knows the exact data structure to write.
  • Camera-first. You upload a food photo in your chat app; the agent's vision estimates macros and calls log_meal.
  • Dashboard. A native iOS app (or PWA) renders your history, totals, and goals — reading the same store the agent writes.

Architecture (one line)

Supabase (Postgres + auth + RLS + storage) ↔ thin remote MCP server ↔ your agent (Claude/ChatGPT) and ↔ native iOS dashboard. One store, two clients.

Repo layout

morsel/
├── docs/            # design docs (start here)
├── server/          # remote MCP server (Bun + Hono + MCP SDK)
├── app/             # native iOS dashboard (SwiftUI) — reads Supabase
├── db/              # Postgres migrations + seed
├── packages/schema/ # canonical types + JSON schemas for the tool contract
├── skills/          # agent skill(s) you attach to Claude / ChatGPT
└── supabase/        # project config

Docs

  • ARCHITECTURE — components, data flow, auth, backend decision
  • DATA_MODEL — tables, enums, RLS
  • MCP_TOOLS — the tool contract (input/output schemas) — what the agent writes
  • TARGETS — computed calorie/macro goal from body metrics
  • IN_CHAT_RENDER — Tier-1 snapshot rendering inside Claude/GPT
  • ROADMAP — milestones
  • CLAUDE.md — context for any agent working in this repo (AGENTS.md is a symlink to it)

Status

Design scaffold with quality guardrails in place (strict TypeScript, anti-slop ESLint + SwiftLint, CI on every PR). Working name morsel (rename freely — it's a folder + a README).

License

MIT — see LICENSE.

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