Memex

Memex

A local-first, privacy-first MCP server that passively indexes personal digital activity (screenshots, clipboard, notes, downloads, links) into a local database, enabling LLMs like Claude to access your context without cloud storage.

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Memex

A local-first, privacy-first personal context engine for LLMs.

TypeScript · Swift · MCP · OpenAPI 3.1.0 · Cloudflare Tunnel


Most AI assistants don't know anything about you. Every new conversation starts from zero — they don't know what you've been reading, what links you've saved, what notes you've written, or what files you've downloaded.

Memex fixes that. It's a background daemon that runs on your Mac and passively indexes your digital activity into a local database. That database is then made available to any LLM — Claude on your desktop, ChatGPT on your phone — through standard interfaces. No cloud storage. No third-party servers. Everything stays on your machine.


What it captures

  • Screenshots — OCR'd locally using Apple's Vision framework (Swift)
  • Clipboard — monitored continuously; YouTube URLs auto-fetch transcripts, Twitter links scrape post content
  • Downloads — PDFs, markdown files, CSVs parsed and indexed on arrival
  • Apple Notes — synced periodically via AppleScript
  • Links from your phone — shared directly from Android via HTTP Shortcuts → POST to local API

How it works

[Screenshots / Clipboard / Notes / Downloads]
              ↓
     Memex Daemon (Node.js)
              ↓
     Local JSON index (db.json)
       ↙              ↘
 MCP Server          HTTP Server :4322
 (stdio)             (Bearer auth)
     ↓                    ↓
Claude Desktop      Cloudflare Tunnel
                         ↓
                   ChatGPT Mobile /
                   Android Share Sheet

The database is a flat JSON file written atomically to disk. Search runs through a custom TF-IDF model — no embeddings, no API calls, fully offline. It weights keyword relevance, recency, document type, and URL path matches to return the most relevant result for any query.

Two interfaces serve the database simultaneously:

  • A local MCP server (stdio transport) for Claude Desktop and MCP-compatible editors like Cursor
  • An HTTP server exposed over a free Cloudflare tunnel for ChatGPT Custom Actions and mobile ingestion

Setup

git clone https://github.com/arnavbee/memex
cd memex
npm install && npm run build

# Configure your API key
cp .env.example .env
# Edit .env and set API_KEY=your-secret-token

# Start the daemon
npm start

# Expose to mobile (optional)
cloudflared tunnel --url localhost:4322

Claude Desktop — add to ~/Library/Application Support/Claude/claude_desktop_config.json:

{
  "mcpServers": {
    "memex": {
      "command": "node",
      "args": ["/path/to/memex/dist/index.js"]
    }
  }
}

ChatGPT Custom Actions — import openapi.json from the repo into your GPT's action schema, pointing the server URL at your Cloudflare tunnel.


Things that were annoying to figure out

ChatGPT's 1MB tool result limit. Returning full PDF text crashed the action with a ResponseTooLargeError. Fixed by truncating all returned content to 2,000 characters server-side.

Claude Desktop's MCP connection dropping on startup. Happened because the HTTP server was initializing before the MCP transport was ready. Fixed by sequencing the boot order and adding retry logging.

Dynamic pages that block scraping. cosmos.so, Instagram, login-walled portals — @mozilla/readability extracts nothing from them. Rather than silently failing, the system now writes a URL stub with the timestamp and source URL so the LLM can still confirm the link was saved.

Android doesn't have Universal Clipboard. iCloud clipboard sync only works on Apple devices. Solved by routing phone shares through HTTP Shortcuts → Cloudflare tunnel → local ingest API instead.


Why certain things were built the way they are

Flat JSON over SQLite — the dataset is small and mostly read-heavy. Atomic file swaps give crash safety without adding a DB engine. The file is also human-readable and trivially portable.

TF-IDF over embeddings — embeddings need either a local GPU or an API round-trip. Both break the offline-first constraint. TF-IDF runs in microseconds and works well for personal context retrieval where queries tend to be specific.

Cloudflare Tunnel over ngrok — no signup, no account, no bandwidth limits, and the URL persists for the session. Free ngrok rotates URLs on restart and throttles connections.

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