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 aayoawoyemi · MCP Server · ★ 324
Last updated: · Indexed by AgentSkillsHub · Auto-synced every 8h
🔒 Is Ori-Mnemos safe to install? View the security audit →
Ori Mnemos Open-source persistent memory infrastructure for AI agents. Ori implements human cognition as mathematical models on a knowledge graph. Activation decay from ACT-R. Spreading activation along wiki-link edges. Hebbian co-occurrence from retrieval patterns. Reinforcement learning on retrieval itself. Recursive graph traversal with sub-question decomposition. The system learns what matters, forgets what doesn't, and optimizes its own retrieval pipeline. Persistent memory across sessions, clients, and machines. Zero-infrastructure retrieval that matches and in several cases strongly outperforms incumbents on benchmarks — and you own every byte of your data. Markdown on disk. Wiki-links as graph edges. Git as version control. No database lock-in, no cloud dependency, no vendor capture. v0.5.0 · npm · Paper · Apache-2.0 Benchmarks HotpotQA — Multi-Hop Retrieval Head-to-head against Mem0, the most widely adopted agent memory system. HotpotQA tests multi-hop reasoning — questions that require connecting information across multiple documents to answer.
| Stars | 324 |
| Forks | 31 |
| Language | TypeScript |
| Category | MCP Server |
| License | Apache-2.0 |
| Quality Score | 67.9931067454706/100 |
| Open Issues | 1 |
| Last Updated | 2026-09-20 |
| Created | 2026-02-20 |
| Platforms | mcp, node |
| Est. Tokens | ~19k |
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Ori-Mnemos is Local-first persistent agentic memory powered by Recursive Memory Harness (RMH). Open source must win.. It is categorized as a MCP Server with 324 GitHub stars.
Ori-Mnemos is primarily written in TypeScript. It covers topics such as agent-memory, ai-agent, ai-agents.
You can find installation instructions and usage details in the Ori-Mnemos GitHub repository at github.com/aayoawoyemi/Ori-Mnemos. The project has 324 stars and 31 forks, indicating an active community.
Ori-Mnemos is released under the Apache-2.0 license, making it free to use and modify according to the license terms.
The top alternatives to Ori-Mnemos on Agent Skills Hub include omega-memory, shodh-memory, vestige. 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: