Personal Memory MCP Server

Personal Memory MCP Server

A self-hosted MCP server providing persistent memory for AI tools, allowing them to remember, recall, and manage information across sessions using a SQLite database.

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Personal Memory MCP Server

A small, self-hosted server that gives any MCP-compatible AI tool (Claude Desktop, Claude Code, and others that support MCP) a shared, persistent memory it can read and write — independent of any single app or project.

Storage is SQLite (one file, memory.db). Tools exposed: remember, recall, list_recent, forget, list_tags.


1. Run it locally first (sanity check)

pip install -r requirements.txt
export MEMORY_SERVER_TOKEN="pick-a-long-random-string-here"
python server.py

It starts on http://localhost:8000. Leave it running.


2. Deploy it somewhere reachable from all your devices

Pick one — all are low/no cost for personal use:

Option A: Railway (easiest)

  1. This repo is already on GitHub — good to go.
  2. Go to railway.app → New Project → Deploy from GitHub repo.
  3. In the service's Variables tab, add MEMORY_SERVER_TOKEN = your secret string.
  4. Railway auto-detects the Procfile and deploys. Add a Volume mounted at /data and set MEMORY_DB_PATH=/data/memory.db so your memories survive redeploys.
  5. Copy the generated public URL (e.g. https://your-app.up.railway.app).

Option B: Render

  1. New → Web Service → connect this repo.
  2. Build command: pip install -r requirements.txt. Start command: python server.py.
  3. Add env var MEMORY_SERVER_TOKEN. Attach a persistent disk at /data, set MEMORY_DB_PATH=/data/memory.db.

Option C: Any VPS (DigitalOcean, Hetzner, etc.) with Docker

docker build -t memory-server .
docker run -d -p 8000:8000 \
  -e MEMORY_SERVER_TOKEN="your-secret" \
  -v ~/memory-data:/data \
  memory-server

Put it behind a domain + HTTPS (e.g. Caddy or nginx + Let's Encrypt) so the token isn't sent over plain HTTP.


3. Connect Claude Desktop / Claude Code to it

Add a remote MCP server in Claude Desktop: Settings → Connectors → Add custom connector, with:

  • URL: https://your-deployed-url/mcp
  • Header: Authorization: Bearer your-secret-token

(Exact UI wording may vary by version — search Claude's docs for "custom connector" if the menu looks different.)

For Claude Code, add to your MCP config (e.g. .mcp.json or via claude mcp add):

{
  "mcpServers": {
    "personal-memory": {
      "url": "https://your-deployed-url/mcp",
      "headers": {
        "Authorization": "Bearer your-secret-token"
      }
    }
  }
}

Any other MCP-compatible client (some third-party tools support MCP connectors too) can point at the same URL + token to share the exact same memory store.


4. Using it

Once connected, just talk naturally:

  • "Remember that my Mayo outreach uses 'research fellow' not 'postdoc'."
  • "What have I saved about the heme-onc template?"
  • "Forget memory #7."

The AI tool decides when to call these tools based on your conversation — you don't need to invoke them manually.


Notes / limitations

  • Security: the bearer token is the only protection. Keep it secret, use HTTPS in production, and don't commit .env or memory.db to git (already in .gitignore).
  • Search is basic: recall does a plain SQL LIKE match, not semantic search. Fine for a personal memory store with dozens–hundreds of entries; if it grows large and keyword search stops finding things, this is the first place to upgrade (e.g. add embeddings + a vector column).
  • Backups: it's one SQLite file — back it up periodically (e.g. a cron job copying /data/memory.db somewhere safe) since most free hosting tiers don't guarantee volume durability.
  • This is separate from Claude's built-in memory — that still exists and works automatically within Claude. This server is for context you want to persist and be readable across different tools, not just Claude.

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