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 pinkpixel-dev · MCP Server · ★ 100
Last updated: · Indexed by AgentSkillsHub · Auto-synced every 8h
🔒 Is mem0-mcp safe to install? View the security audit →
@pinkpixel/mem0-mcp MCP Server ✨ A Model Context Protocol (MCP) server that integrates with Mem0.ai to provide persistent memory capabilities for LLMs. It allows AI agents to store and retrieve information across sessions. This server uses the Node.js SDK for its core functionality. Features 🧠 Tools : Stores a piece of text content as a memory associated with a specific . Required: (string)
| Stars | 100 |
| Forks | 13 |
| Language | TypeScript |
| Category | MCP Server |
| License | MIT |
| Quality Score | 72.7496465244043/100 |
| Open Issues | 1 |
| Last Updated | 2026-07-25 |
| Created | 2025-03-12 |
| Platforms | mcp, node |
| Est. Tokens | ~19k |
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mem0-mcp is ✨ mem0 MCP Server: A memory system using mem0 for AI applications with model context protocl (MCP) integration. Enables long-term memory for AI agents as a drop-in MCP server.. It is categorized as a MCP Server with 100 GitHub stars.
mem0-mcp is primarily written in TypeScript. It covers topics such as agent, assistant, database.
You can find installation instructions and usage details in the mem0-mcp GitHub repository at github.com/pinkpixel-dev/mem0-mcp. The project has 100 stars and 13 forks, indicating an active community.
mem0-mcp is released under the MIT license, making it free to use and modify according to the license terms.
The top alternatives to mem0-mcp on Agent Skills Hub include Ori-Mnemos, YourMemory, omega-memory. Each offers a different approach to the same problem space — compare them side-by-side by stars, quality score, and community activity.
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: