by kitfunso · MCP Server · ★ 784
Last updated: · Indexed by AgentSkillsHub · Auto-synced every 8h
npm install -g hippo-memory && hippo init --scan ~
npm install -g hippo-memory
Taken from the project's README on GitHub. Check the security audit before running it.
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. Full audit →
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 | 784 |
| Forks | 46 |
| Language | TypeScript |
| Category | MCP Server |
| License | MIT |
| Quality Score | 68/100 |
| Open Issues | 27 |
| Last Updated | 2026-10-21 |
| Created | 2026-03-15 |
| Platforms | claude-code, codex, mcp, node |
| Est. Tokens | ~26k |
🦛 Hippo The secret to good memory isn't remembering more. It's knowing what to forget. A memory layer for AI agents. Modeled on the hippocampus. Decay by default, strength through use, provenance on every memory. SQLite under the hood, zero runtime deps, works with every CLI agent you have. One command. Every git repo on your machine gets memory.
These tools work well together with hippo-memory for enhanced workflows:
Looking for a hippo-memory alternative? If you're comparing hippo-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.
Local-first persistent agentic memory powered by Recursive Memory Harness (RMH). Open source must win.
Persistent memory for AI coding agents
Open-source cross-agent memory layer for coding agents via MCP. Compatible with Claude Code, Codex, Cursor, Wi
Open-source governed, local-first memory control plane for AI agents and teams. arXiv:2608.08253
A persistent, unified memory layer for all your AI agents (e.g. Claude Code, Codex, DSH), backed by Markdown a
Agentic AI memory with Ebbinghaus forgetting curve decay. +16pp better recall than Mem0 on LoCoMo.
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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: