Compartment — security grade CAUTION, quality 63/100

Security audit verdict: CAUTION · quality 63/100

Flagged: installs a background service. Scanned against the SlowMist agent-security taxonomy, refreshed every 8 hours. Full audit →

by MaxFreedomPollard · MCP Server · ★ 592

Last updated: · Indexed by AgentSkillsHub · Auto-synced every 8h

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About Compartment

Compartment Listed on: PyPI · Glama · LobeHub · MCP Toplist · mcpservers.org · TensorBlock · Libraries.io · Snyk Advisor · deps.dev Durable agentic memory, encrypted at rest. Your AI agent forgets you the moment the session ends. Compartment ends that. With Compartment, your AI agent gets better with experience: it keeps every decision, preference and detail you give it, permanently, encrypted, on your own computer. Hermes, Claude, OpenClaw and other AI Agents can install in one command. One fully-transferable memory store is shared simultaneously by all agents on the computer. 100% offline: no

agent-memoryai-agentsai-memoryclaudeclaude-codeclaude-desktopencryptiongemini-cli-extensionhermes-agentlocal-first

Quick Facts

Stars592
Forks3
LanguagePython
CategoryMCP Server
LicenseApache-2.0
Quality Score63.4111333759923/100
Last Updated2026-09-06
Created2026-07-20
Platformsclaude-code, cli, gemini, mcp, python
Est. Tokens~23k

Compartment alternative? Top 6 similar tools

Looking for a Compartment alternative? If you're comparing Compartment with other mcp server tools, these 6 projects are the closest alternatives on Agent Skills Hub — ranked by topic overlap, star count, and community traction.

  • mcp-memory-service by doobidoo · ⭐ 1.9k

    Open-source persistent memory for AI agent pipelines (LangGraph, CrewAI, AutoGen) and Claude. REST API + knowl

  • memorix by AVIDS2 · ⭐ 761

    Open-source cross-agent memory layer for coding agents via MCP. Compatible with Claude Code, Codex, Cursor, Wi

  • Ori-Mnemos by aayoawoyemi · ⭐ 319

    Local-first persistent agentic memory powered by Recursive Memory Harness (RMH). Open source must win.

  • shodh-memory by varun29ankuS · ⭐ 279

    Local, LLM-free memory for AI agents. A single offline Rust binary — deterministic and auditable — that learns

  • omega-memory by omega-memory · ⭐ 215

    Persistent memory for AI coding agents

  • mengram by alibaizhanov · ⭐ 194

    Human-like memory for AI agents — semantic, episodic & procedural. Experience-driven procedures that learn fro

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Frequently Asked Questions

What is Compartment?

Compartment is Encrypted, fully offline agentic memory. One click install, GUI w/ memory map, all OS and agents. Superior memory creation, storage and retrieval.. It is categorized as a MCP Server with 592 GitHub stars.

What programming language is Compartment written in?

Compartment is primarily written in Python. It covers topics such as agent-memory, ai-agents, ai-memory.

How do I install or use Compartment?

You can find installation instructions and usage details in the Compartment GitHub repository at github.com/MaxFreedomPollard/Compartment. The project has 592 stars and 3 forks, indicating an active community.

What license does Compartment use?

Compartment is released under the Apache-2.0 license, making it free to use and modify according to the license terms.

What are the best alternatives to Compartment?

The top alternatives to Compartment on Agent Skills Hub include mcp-memory-service, memorix, Ori-Mnemos. Each offers a different approach to the same problem space — compare them side-by-side by stars, quality score, and community activity.

How this security grade is produced

Grades come from a rule-based scan built on the SlowMist agent-security taxonomy, covering 11 red-flag categories including credential harvesting, data exfiltration, and curl | sh installers. It is a first-layer scan, not a manual audit — we say so rather than overstate it.

The scale of the problem is documented independently: Liu et al. (2026), in a study of 31,132 agent skills, report that 26.1% contain security vulnerabilities. Our own full-catalog census is published as a citable open dataset.

Sources & who's responsible:

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