by fellowgeek · MCP Server · ★ 198
Last updated: · Indexed by AgentSkillsHub · Auto-synced every 8h
git clone https://github.com/fellowgeek/mcp-memory
Taken from the project's README on GitHub.
None of the 42 rules matched — no credential harvesting, no data exfiltration, no curl-pipe-shell installer. Scanned against 42 published rules built on the SlowMist agent-security taxonomy, refreshed every 8 hours.
The quality score combines nine heuristic checks of the repo and its README: completeness, clarity, specificity, examples, structure, agent readiness, step-by-step content, instruction quality and security notes. It rates how well the project explains itself to an agent, not the code.
| Stars | 198 |
| Forks | 12 |
| Language | Python |
| Category | MCP Server |
| License | MIT |
| Quality Score | 68/100 |
| Open Issues | 1 |
| Last Updated | 2026-08-30 |
| Created | 2026-08-13 |
| Platforms | mcp, python |
| Est. Tokens | ~7k |
MCP-Memory: OKF-Backed Agent Memory Server MCP-Memory is a Model Context Protocol (MCP) server that equips AI agents (such as Claude Desktop, Cursor, Antigravity, Windsurf, or Codex) with persistent, long-term memory capabilities.
These tools work well together with mcp-memory for enhanced workflows:
Explore other popular mcp server tools:
Grades come from a rule-based scan built on the SlowMist agent-security taxonomy: 42 published rules, covering credential harvesting, data exfiltration, curl | sh installers and more. 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: