innercontext

Personal health and skincare data hub. Collects structured data (products, routines, lab results, medications, skin snapshots) and exposes it via a REST API and MCP to an LLM agent.

Repository layout

backend/   Python backend — FastAPI REST API + SQLModel models

A frontend will be added in the future.

Backend quick start

Requirements: Python 3.12+, PostgreSQL, uv

cd backend

# Install dependencies
uv sync

# Set database URL (defaults to postgresql+psycopg://localhost/innercontext)
export DATABASE_URL=postgresql+psycopg://user:password@localhost/innercontext

# Start the API server (creates tables on first run)
uv run uvicorn main:app --reload

API docs available at http://localhost:8000/docs.

API overview

Prefix	Resource
/products	Skincare / medication products + inventory
/inventory	Individual inventory entries
/health/medications	Medication entries and usage history
/health/lab-results	Lab test results
/routines	AM/PM skincare routines and steps
/routines/grooming-schedule	Weekly grooming schedule
/skin-snapshots	Weekly skin condition snapshots
/health-check	Liveness probe

Development

cd backend

# Lint
uv run ruff check .

# Format
uv run black .
uv run isort .

Stack

• Runtime: Python 3.12, FastAPI, Uvicorn
• ORM: SQLModel 0.0.37 + SQLAlchemy, Pydantic v2
• Database: PostgreSQL (psycopg3)