recallLABSCO SUMMARY
Schema-level isolation and per-agent consent, not one shared table with a user column.
Giving every user their own PostgreSQL schema removes a whole class of leak, and per-table consent rules mean a meal-tracking agent and a coding assistant do not see the same rows. The trade-off compared with a local memory file is real infrastructure — Postgres with pgvector — but the self-hosted path is one compose file and the data stays yours either way.
What it is
A portable identity and memory service backed by PostgreSQL with pgvector. Each user gets their own database schema rather than row-level filtering, so cross-user access is impossible at the SQL level. Run it hosted or self-host the whole thing with Docker Compose.
What you get
- Three MCP tools — recall, memorize and review — the whole surface an agent needs
- Structured tables, vector semantic memory and key-value storage in one place, all queryable and exportable
- A structured profile any agent reads instantly, so a new tool starts knowing you rather than cold
- Confidence scoring and source attribution: memories earn trust through reinforcement instead of being taken at face value
- A knowledge graph of entities connected by typed, weighted edges
- Per-table consent rules per agent, and an append-only activity log of every access
Requirements
For the hosted service, an API key from Settings → API Keys, sent as an Authorization bearer header to https://epitome.fyi/mcp over Streamable HTTP; Claude Code registers it with claude mcp add --transport http. To self-host, clone the repository, copy .env.example to .env with your credentials and run docker compose up -d, then sign in at localhost:5173 with Google or GitHub OAuth and point clients at http://localhost:3000 instead. Built on Node.js 22 LTS and PostgreSQL 17 with pgvector.
Setup effort
One command plus a key — claude mcp add --transport http --header "Authorization: Bearer <YOUR_API_KEY>" epitome https://epitome.fyi/mcp
USE CASES
01
Not re-introducing yourself to every new AI tool
A new agent reads the profile and starts the first conversation already knowing you.
02
Carrying context between assistants
What one agent learned is available to the next, rather than trapped in that app's chat history.
03
Controlling what each agent may see
Set per-table permissions so a given agent reaches only the data it needs.
04
Keeping the data on your own machine
Run the compose stack locally and point clients at your own endpoint.
3 tools
Listed in project docs. Your client may show a different list.
memorizereviewBEFORE YOU INSTALL
What to know first
Tools you get
3 tools named in the project's documentation.
Requires
A client that can reach a remote MCP server over HTTP
Where it runs
The documented client connects to a hosted endpoint.
INSTALLATION
Connect your client
Server setup
claude mcp add
Claude Code
TERMINAL
claude mcp add --transport http --header "Authorization: Bearer <YOUR_API_KEY>" epitome https://epitome.fyi/mcpHosted endpoint
ENDPOINT URL
https://epitome.fyi/mcpAdd this hosted endpoint to your MCP client using the credentials listed under Requirements.
