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 ukkit · MCP Server · ★ 73
Last updated: · Indexed by AgentSkillsHub · Auto-synced every 8h
🔒 Is memcord safe to install? View the security audit →
MEMCORD v4.0.2 (mcp server) This privacy-first, self-hosted MCP server helps you organize chat history, summarize messages, search across past chats with AI — and keeps everything secure and fully under your control. Never Lose Context Again Transform your Claude conversations into a searchable, organized knowledge ba
| Stars | 73 |
| Forks | 11 |
| Language | Python |
| Category | MCP Server |
| License | MIT |
| Quality Score | 68.4818011205697/100 |
| Last Updated | 2026-08-07 |
| Created | 2025-06-27 |
| Platforms | claude-code, mcp, python |
| Est. Tokens | ~16k |
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memcord is 🧠 Self-hosted, privacy-first MCP server for long-term AI memory — save, search & summarize Claude/ChatGPT chat history locally. No cloud, no database.. It is categorized as a MCP Server with 73 GitHub stars.
memcord is primarily written in Python. It covers topics such as ai-assistant, ai-memory, antigravity.
You can find installation instructions and usage details in the memcord GitHub repository at github.com/ukkit/memcord. The project has 73 stars and 11 forks, indicating an active community.
memcord is released under the MIT license, making it free to use and modify according to the license terms.
The top alternatives to memcord on Agent Skills Hub include roampal-core, task-orchestrator, roampal. 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: