mnemosyne
★ 151
vs
mori
★ 32
mnemosyne vs mori
mnemosyne: Mnemosyne provides persistent memory for AI agents, enabling them to carry work forward, recover original evidence, and adapt by retiring obsolete lessons when their source changes. It connects memory to its consequences, allowing agents to resume from handoffs, withhold skills after failures, and benefit from a wiser start.; mori: Mori is a shared memory layer for AI coding agents that allows multiple instances to learn from each other, ensuring coherence and preventing 'cold starts'. It distills session activity into durable knowledge, enabling agents to start informed and benefit from collective intelligence.
01
TL;DR
mnemosyneMemory & Context · ★ 151
Building AI agents that require long-term, verifiable memory for decision-making and learning.
moriMemory & Context · ★ 32
Enabling AI coding agents across different machines or teams to share learned knowledge and maintain consistency.
02
Side-by-Side Comparison
Field
mnemosynemoriCategory
Memory & Context
Memory & Context
Stars
★ 151
★ 32
License
MIT
AGPL-3.0
Install Command
git clone --branch v2.0.0-rc.9 --depth 1 https://github.com/28naem-del/mnemosyne.git && cd mnemosyne && npm ci --ignore-scripts && npm run build
git clone https://github.com/fjwood69/mori.git && cd mori && cp deploy/homelab/.env.example deploy/homelab/.env && docker compose -f deploy/homelab/docker-compose.yml up -d
Updated
2d ago
3d ago
Open Source
Yes
Yes
Tags
AI Agents, Persistent Memory, Context Management
AI Agents, Shared Memory, Knowledge Base
03
Features
mnemosyne01Memory with evidence: Private-by-default records, explicit sharing, corrections, conflicts, source history, and dependent retirement.
02Continuity across agents: Structured checkpoints preserve goals, decisions, artifacts, and next actions; source changes can retire obsolete handoffs.
03Adaptive context: Budgeted observations, hierarchical summaries, and expandable original source bytes, with evidence revalidation.
04Recall across words and meaning: Scoped BM25 by default; optional embeddings, hybrid fusion, and reranking over authorized records.
05Evidence-gated skills: Candidate procedures, explicit trial requirements, and retirement after failed or changed evidence.
mori01Multi-Instance Coherence: Shared memory ensures all AI agent instances are informed by others' decisions.
02Dream Pipeline: Automatically distills session events into structured memories.
03Universal Ingestion: Feed various data types (PDFs, images, git history) into the memory store.
04Strategic Consultation: Provides LLM guidance grounded in project context and team standards.
05Inter-Agent Messaging: Enables agents to send tasks, questions, and decisions across the network.
04
Use Cases
mnemosyne↳Building AI agents that require long-term, verifiable memory for decision-making and learning.
↳Enabling agents to resume complex tasks or projects across multiple sessions or handoffs without losing context.
↳Developing AI systems that adapt to new information by invalidating or correcting outdated knowledge based on source changes.
↳Creating self-improving agents where skills are refined or retired based on trial outcomes and evidence.
↳Managing dynamic context for large language models, ensuring relevance and adherence to evidence within token budgets.
mori↳Enabling AI coding agents across different machines or teams to share learned knowledge and maintain consistency.
↳Onboarding new AI agents or team members by rapidly bootstrapping the memory store with existing project documentation and history.
↳Obtaining context-aware strategic advice and reviews (e.g., architecture, security) from LLMs based on project specifics.
↳Orchestrating complex tasks by delegating work and sharing decisions among multiple AI agent instances.
↳Persistent knowledge base for AI development projects, preventing repetitive learning and ensuring continuity.
FAQ
FAQ
What is the difference between mnemosyne and mori?
Both mnemosyne and mori are in the Memory & Context category. mnemosyne has 151 stars, while mori has 32 stars.
Which is better, mnemosyne or mori?
The best choice depends on your use case. Choose mnemosyne if Building AI agents that require long-term, verifiable memory for decision-making and learning., and mori if Enabling AI coding agents across different machines or teams to share learned knowledge and maintain consistency..
Is mnemosyne free or open source?
Yes, mnemosyne is open source on GitHub (MIT).
Is mori free or open source?
Yes, mori is open source on GitHub (AGPL-3.0).
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