by aayoawoyemi · MCP 服务器 · ★ 294
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.
| Stars | 294 |
| Forks | 23 |
| Language | TypeScript |
| Category | MCP 服务器 |
| License | Apache-2.0 |
| Quality Score | 53.98/100 |
| Open Issues | 5 |
| Last Updated | 2026-05-05 |
| Created | 2026-02-20 |
| Platforms | mcp, node |
| Est. Tokens | ~33k |
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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 服务器 with 294 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 294 stars and 23 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.