omega-memory — security grade SAFE, quality 66/100

Security audit verdict: SAFE · quality 66/100

No red flags found in any of the 11 categories — no credential harvesting, no data exfiltration, no curl-pipe-shell installer. Scanned against the SlowMist agent-security taxonomy, refreshed every 8 hours. Full audit →

by omega-memory · MCP Server · ★ 215

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

🔒 Is omega-memory safe to install? View the security audit →

About omega-memory

OMEGA Cross-model memory for AI agents. Local-first. Works with Claude, GPT, Gemini, Cursor, Claw Code, and any MCP client. Your agent's brain shouldn't live on someone else's server, or be locked to one provider. []() The Problem AI coding agents are stateless. Every new session starts from zero. The "solutions" either lock you into one model provider or send your codebase context to their cloud. Context loss. Agents forget every decision, preference, and architectural choice between sessions. Developers spend 10-30 minutes per session re-explaining context that was already established. Repeated mistakes. Without learning from past sessions, agents make the same errors over and over. They don't remember what worked, what failed, or why a particular approach was chosen. Cloud memory = someone else's database. Services like Mem0 require API keys and send your data to their servers. When they change pricing, get acquired, or go down, your agent's accumulated intelligence disappears. Vendor lock-in. Anthropic's Memory Tool only works with Claude. OpenAI's memory only works with GPT.

ai-agentai-memoryclaudeclaude-codecoding-agentcontext-engineeringcursorknowledge-graphllmlocal-first

Quick Facts

Stars215
Forks26
LanguagePython
CategoryMCP Server
LicenseApache-2.0
Quality Score66.2545533370149/100
Open Issues5
Last Updated2026-09-07
Created2026-02-13
Platformsclaude-code, mcp, python
Est. Tokens~16k

omega-memory alternative? Top 6 similar tools

Looking for a omega-memory alternative? If you're comparing omega-memory 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.

  • Ori-Mnemos by aayoawoyemi · ⭐ 319

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

  • roampal-core by roampal-ai · ⭐ 50

    Outcome-based persistent memory MCP server for Claude Code and OpenCode. Good advice promoted, bad advice demo

  • Zikkaron by amanhij · ⭐ 62

    Biologically-inspired persistent memory engine for Claude Code. 26 cognitive subsystems, Hopfield networks, pr

  • memorix by AVIDS2 · ⭐ 767

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

  • Overture by SixHq · ⭐ 630

    Overture is an open-source, locally running web interface delivered as an MCP (Model Context Protocol) server

  • vestige by samvallad33 · ⭐ 623

    Vestige enhances agents by deterministic root-cause retrieval that reaches backward through time to find the q

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Frequently Asked Questions

What is omega-memory?

omega-memory is Persistent memory for AI coding agents. It is categorized as a MCP Server with 215 GitHub stars.

What programming language is omega-memory written in?

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

How do I install or use omega-memory?

You can find installation instructions and usage details in the omega-memory GitHub repository at github.com/omega-memory/omega-memory. The project has 215 stars and 26 forks, indicating an active community.

What license does omega-memory use?

omega-memory 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 omega-memory?

The top alternatives to omega-memory on Agent Skills Hub include Ori-Mnemos, roampal-core, Zikkaron. 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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