This document outlines the architecture of the Digital Persona’s data ingestion system. It is designed to flexibly import a wide range of personal data sources while respecting the project’s privacy-first principles.

• Import personal content (emails, health logs, chat messages, calendar events, etc.)
• Normalize into semantically structured formats (e.g. JSON-LD, ActivityStreams)
• Store in user-owned, locally hosted memory vaults
• Expose to the rest of the system through optional MCP interfaces

• Email: via IMAP, Gmail APIs, or Huginn
• Calendar: Google Calendar, Apple Calendar (ICS exports, CalDAV)
• Health & Fitness: MyFitnessPal, Apple Health, Fitbit (via API or scraper)
• Chat Logs: Discord, SMS exports, WhatsApp (manual export), Limitless AI
• Journaling/Writing: Obsidian markdown vaults, Google Docs, Notion
• Media Metadata: EXIF from photos, YouTube watch history, Spotify playback

Each connector typically includes:

• Fetcher: A script or agent that downloads raw data (via API, scraper, or sync)
• Parser: Normalizes input to a memory object with metadata
• Serializer: Converts memory object to JSON-LD/ActivityStreams
• Storage Layer: Writes to persona_memory/<domain>/<source>/<timestamp>.json
• Log Handler: Logs success/failure per run

1. Authenticates using browser cookie
2. Scrapes daily entries
3. Converts to structured JSON
4. Writes to persona_memory/health/myfitnesspal/YYYY-MM-DD.json
5. Exposes via local MCP server at /mcp/health/mfp/today

flowchart TD
    A[Personal Data Source] --> B[Connector Script]
    B --> C[Fetch Raw Data]
    C --> D[Parse and Normalize]
    D --> E[Semantic JSON Transformation]
    E --> F[Write to Local Memory Vault]
    F --> G{Expose via MCP?}
    G -->|Yes| H[Run MCP Server Endpoint]
    G -->|No| I[Archive Only]
    H --> J[Queried by Persona Core or RAG]

All ingested data is transformed into a semantic memory entry, such as:

{
  "@context": "https://www.w3.org/ns/activitystreams",
  "type": "Note",
  "name": "Weight entry",
  "content": "Weight: 171.2 lbs",
  "published": "2025-07-11T08:45:00Z",
  "tag": ["weight", "health", "myfitnesspal"]
}

• All data pulled and stored locally by default
• No cloud upload unless explicitly opted in by user
• Use HTTPS or encryption for API connections
• Option to encrypt persona_memory directory

• For each memory domain (health, calendar, etc.), run a lightweight MCP server (FastAPI)

• Each endpoint serves filtered and structured data

• Examples:

  • /mcp/calendar/today
  • /mcp/health/latest
  • /mcp/logs/errors

To add a new source:

1. Create a new connector script
2. Follow the fetch → parse → normalize → store pattern
3. Optionally expose data via MCP
4. Register ingestion metadata in a .index.json file per domain for lookup

Next file: memory.md – will cover short-term and long-term memory mechanics.