Ori-Mnemos MCP Server
aayoawoyemi/Ori-Mnemos
[](https://agentrank-ai.com/tool/aayoawoyemi--Ori-Mnemos/?utm_source=badge&utm_medium=readme&utm_campaign=agentrank_badge) Local-first persistent agentic memory powered by Recursive Memory Harness (RMH). Open source must win.
claude mcp add agentrank -- npx -y agentrank-mcp-server Overview
aayoawoyemi/Ori-Mnemos is a TypeScript tool licensed under Apache-2.0. Local-first persistent agentic memory powered by Recursive Memory Harness (RMH). Open source must win. Topics: agent-memory, ai-agent, ai-memory, knowledge-graph, llm, markdown, mcp, mcp-server, model-context-protocol, persistent-memory, semantic-search, typescript, vector-search, ai-agents, local-first, memory, sqlite, rmh, persistent-ai-memory, recursive-memory-harness.
Ranked #857 out of 24846 indexed tools.
In the top 4% of all indexed tools.
Ecosystem
Score Breakdown
332 stars → growing community
Last commit 22d ago → recently updated
17/18 issues closed → responsive maintainer
3 contributors → small team
No dependents → no downstream usage
Weights: Freshness 20% · Issue Health 20% · Dependents 22% · Stars 10% · Contributors 8% · How we score →
Badge all embed codes →
[](https://agentrank-ai.com/tool/aayoawoyemi--Ori-Mnemos/?utm_source=badge&utm_medium=readme&utm_campaign=agentrank_badge) <a href="https://agentrank-ai.com/tool/aayoawoyemi--Ori-Mnemos/?utm_source=badge&utm_medium=readme&utm_campaign=agentrank_badge"><img src="https://agentrank-ai.com/api/v1/badge/aayoawoyemi--Ori-Mnemos" alt="AgentRank"></a> Matched Queries
From the README
# 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](#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. **v0.7.0** · [npm](https://www.npmjs.com/package/ori-memory) · [Paper](https://orimnemos.com/rmh) · Apache-2.0 --- ## Use Ori is three surfaces over one index. The markdRead full README on GitHub →
Get the weekly AgentRank digest
Top movers, new tools, ecosystem insights — straight to your inbox.