Compartment

Encrypted, fully offline memory for AI agents. One vault on your own computer, read and written by Claude Code, Claude Desktop, Hermes Agent, OpenClaw, Cursor, Codex and any other MCP client. No API key, no account, no network, no telemetry.

One-click install (after pip install compartment && compartment init):

Claude Code, Claude Desktop, Hermes Agent and OpenClaw are wired by one command instead: compartment integrate claude, hermes or openclaw.

Compartment is persistent memory for AI agents, stored on your own computer. What an agent learns in one session is available in every later session, in every project, to every agent on the machine, and nothing leaves the machine.

Each memory is a single claim, recorded with its source and the date it was learned. Memories can expire: set expires and the memory is removed after that date. When a preference changes, the new one replaces the old one. Recall is a hybrid vector and keyword search over an in-memory index. It answers in about 12 ms and returns only what is relevant.

The embedding model is included in the package. Everything on disk is encrypted, including the embedding vectors, and only your passphrase opens it. A new vault comes with about 6,700 reference facts about hardware, operating systems, ports, encodings and shell tools. They are ordinary memories, and one switch removes them from search.

How it compares with other memory servers

Where each server keeps memory and what protects it, as documented by each project on 2 September 2026. Sources and the full table are in docs/COMPARISON.md; corrections are welcome as a PR against that file.

	Memory at rest	Encrypted	Account / API key	Network at runtime
Compartment	one encrypted file; index in RAM	yes, vectors too	none	none, CI-enforced
@modelcontextprotocol/server-memory	plaintext memory.jsonl, substring search	no	none	none
mem0 (open source)	vector store + LLM-extracted facts; its MCP server is hosted only	not documented	LLM key	LLM calls; telemetry on by default
Graphiti (Zep) / Letta	Neo4j / server + database	not documented	LLM key	LLM calls; telemetry on by default
claude-mem	local SQLite + Chroma	not documented	sign-in required	account + provider calls; telemetry on by default
basic-memory (AGPL)	Markdown + SQLite	not documented	none	telemetry on by default
Hindsight (Vectorize)	one container with embedded PostgreSQL	not documented	LLM key (local models configurable)	LLM calls; vendor states no telemetry
Supermemory	cloud service, or a self-hosted prebuilt binary	not documented	account (cloud) or LLM key (self-host)	cloud calls; self-host: vendor states no telemetry
Cognee	SQLite + LanceDB + Kuzu locally, or cloud	not documented	LLM key	LLM calls; telemetry on by default
MemOS	Neo4j + Qdrant self-hosted, or cloud	not documented	LLM key	LLM calls; telemetry on by default

The memory logic

Almost everything is stored. Only empty turns are dropped. A bare "OK" is a decision, not noise: when the agent asks "Want me to send this reply to the client now?" and the user answers "OK", Compartment stores the decision together with the question it answered. Small talk is kept but ranked last.