Ori-Mnemos
Active·★ 306·Apache-2.0·Updated 2026-05-05
★ Memory & Context★ RAG / Knowledge Base
Local-first persistent agentic memory powered by Recursive Memory Harness (RMH). Open source must win.
Ori Mnemos is an open-source persistent memory infrastructure for AI agents that implements human cognition models on a knowledge graph. It uses ACT-R decay, spreading activation, and Hebbian learning to manage memory, and achieves state-of-the-art retrieval performance while being zero-infrastructure and portable.
#agent-memory#ai-agent#ai-agents#ai-memory#knowledge-graph#llm#local-first#markdown
01
Features
01Persistent memory across sessions, clients, and machines
02Knowledge graph with wiki-links, PageRank, and community detection
03Three memory spaces with cognitive forgetting (ACT-R decay)
04Four-signal fusion retrieval (semantic, BM25, PageRank, warmth)
05Retrieval intelligence with Q-learning and meta-learning
02
Compatibility
Claude Code
Claude Code
Verified via docs
Cursor
Cursor
Verified via docs
Windsurf
Windsurf
Verified via docs
Cline
Cline
Verified via docs
Hermes
Hermes
Verified via docs
03
Quick start
1
$ npm install -g ori-memory
2
$ ori init my-agent
3
$ cd my-agent
04
Use cases
↳Multi-hop retrieval QA (e.g., HotpotQA)
↳Long-term conversational memory (e.g., LoCoMo)
↳Persistent AI agent identity and knowledge
05
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Comments
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- SSasha KimMay 3, 2026
Memory that actually persists across sessions without a remote dependency.
- PPeyton WhiteApr 14, 2026
Recursive Memory Harness for local-first persistent agent memory is well-designed.
- Dakota ChenMar 30, 2026
Local-first means no latency from remote memory retrieval.
- MMarlowe KimMar 9, 2026
Good for developers who want agent context that survives process restarts.