open-memory-protocol — security grade SAFE, quality 70/100

Security audit verdict: SAFE · quality 70/100

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 SMJAI · MCP Server · ★ 73

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

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

About open-memory-protocol

Open Memory Protocol (OMP) An open standard for portable, interoperable AI memory across tools, sessions, and devices. The Problem Every AI tool remembers you differently — and only within its own walls. Claude knows what you told it yesterday. Cursor doesn't. ChatGPT learned your preferences. Your custom agent hasn't. Copilot saw your code style. Your terminal AI is starting from zero. Every time you switch tools, your AI forgets you. You repeat yourself. Context is lost. The AI that was finally starting to know you resets to a stranger. This is the AI memory silo problem. And it has the same solution as every silo problem before it: an open protocol. What is OMP? Open Memory Protocol is a vendor-neutral specification for how AI tools store, retrieve, and share memory about users and their context. It is: A specification — a precise definition of memory objects, storage format, and HTTP API A reference server — self-hostable, open-source, runs in Docker in one command A set of SDKs — TypeScript and Python libraries for building OMP-compatible tools A set of adapters — plug-ins for Claude (MCP), OpenAI, Cursor, and more Any AI tool that implements OMP can

ai-memoryclaudeclaude-aiclaude-codellmmcpmemoryopen-standardopen-standardsopenai

Quick Facts

Stars73
Forks2
LanguageTypeScript
CategoryMCP Server
Quality Score69.71909475477/100
Open Issues1
Last Updated2026-07-02
Created2026-06-29
Platformsclaude-code, mcp, node
Est. Tokens~14k

Compatible Skills

These tools work well together with open-memory-protocol for enhanced workflows:

  • codemem — semantic(0.35)+complementary+same_lang+similar_pop+shared_platform (62%)

open-memory-protocol alternative? Top 6 similar tools

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

  • omega-memory by omega-memory · ⭐ 218

    Persistent memory for AI coding agents

  • Grov by TonyStef · ⭐ 193

    Grov automatically captures the context from your private AI sessions and syncs it to a shared team memory. It

  • claude-historian-mcp by Vvkmnn · ⭐ 177

    📜 An MCP server for conversation history search and retrieval in Claude Code

  • mcp-linker by milisp · ⭐ 323

    mcp store manager, add & syncs MCP server configurations across clients like Claude code, Cursor💡mcphub

  • MoltBrain by nhevers · ⭐ 253

    Long-term memory layer for OpenClaw & MoltBook agents that learns and recalls your project context automatical

  • c4-genai-suite by codecentric · ⭐ 173

    c4 GenAI Suite

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Frequently Asked Questions

What is open-memory-protocol?

open-memory-protocol is An open standard for portable, interoperable AI memory across tools, sessions, and devices.. It is categorized as a MCP Server with 73 GitHub stars.

What programming language is open-memory-protocol written in?

open-memory-protocol is primarily written in TypeScript. It covers topics such as ai-memory, claude, claude-ai.

How do I install or use open-memory-protocol?

You can find installation instructions and usage details in the open-memory-protocol GitHub repository at github.com/SMJAI/open-memory-protocol. The project has 73 stars and 2 forks, indicating an active community.

What are the best alternatives to open-memory-protocol?

The top alternatives to open-memory-protocol on Agent Skills Hub include omega-memory, Grov, claude-historian-mcp. 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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