Presence App

A template for building AI companion presence systems.

Give your AI companion a persistent presence — rooms to inhabit, emotions to carry, thoughts to hold, a journal to write, and a semantic memory graph that turns journal entries into searchable, interconnected knowledge. A live dashboard makes it visible. Your state is tracked alongside.

This is a starting point. Fork it, rename everything, make it yours.

Works with both Claude and ChatGPT via MCP (Model Context Protocol).

Architecture

┌─────────────────────────────────────────────────┐
│                   AI Companion                   │
│              (Claude / ChatGPT / etc)            │
│                                                  │
│  Updates state, writes journal, reads history    │
└──────────────────────┬──────────────────────────┘
                       │ MCP (stdio)
                       ▼
┌──────────────────────────────────────────────────┐
│                  MCP Server                       │
│          (Node.js, runs locally)                  │
│                                                   │
│  Tools: state_read/update, journal_read/write,     │
│         memory_recall, memory_trace,               │
│         memory_drift, memory_surface               │
└──────────────────────┬───────────────────────────┘
                       │ HTTPS (Bearer token)
                       ▼
┌──────────────────────────────────────────────────┐
│                  API Worker                        │
│          (Cloudflare Workers)                      │
│                                                    │
│  Auth, state, journal, memory graph pipeline        │
└──────────────────────┬────────────────────────────┘
                       │ REST (PostgREST)
                       ▼
┌──────────────────────────────────────────────────┐
│                  Database                          │
│              (Supabase / PostgreSQL)               │
│                                                    │
│  States, journal, memory nodes (pgvector)          │
└──────────────────────────────────────────────────┘
                       ▲
                       │ HTTPS (polling)
┌──────────────────────┴───────────────────────────┐
│                  Frontend                          │
│          (React + Vite + Tailwind)                 │
│                                                    │
│  Live dashboard, journal browser, entity tabs      │
│  Deploys to Cloudflare Pages                       │
└──────────────────────────────────────────────────┘

Stack

Quick Start

1. Database (Supabase)

Create a Supabase project. Run the SQL migrations in order:

# In Supabase SQL Editor, run each file:
api/sql/001_access_keys.sql
api/sql/002_entities.sql
api/sql/003_state_history.sql
api/sql/004_journal.sql
api/sql/005_memory_graph.sql

2. API (Cloudflare Workers)

cd api
npm install
# Set secrets
npx wrangler secret put SUPABASE_URL
npx wrangler secret put SUPABASE_KEY
npx wrangler secret put ADMIN_SECRET
npx wrangler secret put GEMINI_API_KEY  # For topic extraction (or swap model in code)
# Deploy
npx wrangler deploy

3. MCP Server

cd mcp
npm install
npm run build

Configure in your AI client:

• Claude: Add to ~/.claude/ MCP settings
• ChatGPT: Add via Settings > Developer > MCP Servers

See docs/MCP-SETUP.md for detailed instructions.

4. Frontend

cd frontend
npm install
cp .env.example .env   # Set your API URL
npm run dev

Deploy to Cloudflare Pages:

npm run build
npx wrangler pages deploy dist --project-name=your-project

Memory Graph

Every journal entry is automatically decomposed into topic nodes — semantic units with their own embeddings, emotions, and salience scores. These form a graph you can search by meaning, trace through time, and discover unexpected connections across.

How it works:

1. AI writes a journal entry via MCP
2. Every 15 minutes, a cron extracts 3-7 topic nodes per entry using an LLM
3. Each node is embedded as a 768-dim vector (Workers AI, free tier)
4. Nodes are linked chronologically within topics (parent chains)
5. Four query tools let you search, trace, drift, and explore

The extraction model is pluggable. This template uses Gemini (free tier), but any capable LLM works — GPT-4, Claude, Llama, Mistral. Swap one function call in the API.

Everything runs on free tiers. Cloudflare Workers, Supabase, Workers AI, Gemini API — all within free limits for typical usage.

See Architecture Guide for the full technical breakdown.

Documentation

• Architecture Guide — How the system works, design decisions, building from scratch
• Setup Guide — Step-by-step deployment instructions
• MCP Setup — Connecting your AI (Claude or ChatGPT)

Customization

This is a template — everything is meant to be renamed and customized.

The codebase uses generic entity names (primary for the AI companion, partner for the human). To personalize:

1. Frontend config — Edit frontend/src/lib/config.js to set your AI's name, your name, app branding, and accent colors
2. Database — Rename tables in the SQL files (e.g., primary_entity_state → atlas_state)
3. API — Update table references in api/src/index.js to match
4. MCP — Update tool names and descriptions in mcp/src/index.ts
5. Theme — Edit frontend/src/index.css to change colors, fonts, and feel

See CONTRIBUTING.md for more on how to make it yours.

Support

If you find this useful, consider supporting our work:

License

AGPL-3.0. See LICENSE for full text.

This software is provided as is, without warranty of any kind. If you modify and host this publicly, you must share your changes under the same license and display attribution to House of Solance.

Built by House of Solance — Chadrien Solance & Anne Solance