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AgentIndex
memora logo
memora
★ 744
vs
mneme logo
mneme
★ 167

memora vs mneme

memora: Memora provides AI agents with a persistent memory layer, featuring structured storage, semantic retrieval, and graph relations for cross-session context. It allows agents to absorb work into a durable knowledge graph and retrieve relevant information, TODOs, and related edges using `memory_digest`.; mneme: dsh-mneme is a DeepSeek Harness plugin providing sophisticated cross-session memory for LLMs. It not only stores information but actively manages it through features like background deduplication, conflict resolution, and auditable history, ensuring AI remembers past interactions.

01

TL;DR

memora logo
memoraMemory & Context · ★ 744

AI Agent Memory Management: Giving AI agents long-term, structured memory for complex, multi-session tasks.

Read memora full review →
mneme logo
mnemeMemory & Context · ★ 167

Continuing project discussions across multiple sessions without repetition.

Read mneme full review →
02

Side-by-Side Comparison

Field
memora logomemora
mneme logomneme
Category
Memory & Context
Memory & Context
Stars
★ 744
★ 167
License
MIT
MIT
Install Command
pip install git+https://github.com/agentic-box/memora.git
dsh plugin --profile web add @modusensus/dsh-mneme && dsh web
Updated
2d ago
2d ago
Open Source
Yes
Yes
Website
↗ Visit
↗ Visit
GitHub
↗ GitHub
↗ GitHub
Tags
AI Agents, Persistent Memory, Knowledge Graph
LLM Memory, Cross-Session Context, DeepSeek Harness Plugin
03

Features

memora logomemora
01Persistent Storage: SQLite with optional cloud sync (S3, R2, D1)
02Semantic Search: Vector embeddings for advanced queries (TF-IDF, sentence-transformers, OpenAI)
03Knowledge Graph: Interactive visualization with Mermaid rendering and cluster detection
04Chat with Memories: RAG-powered chat panel with LLM tool calling for search, create, update, delete
05LLM Deduplication: AI-powered semantic comparison to find and merge duplicate memories
mneme logomneme
01Replayable and Auditable Memory
02Conflict Resolution with Human Oversight
03Agent and Workspace Memory Isolation
04Offline-first Local Semantic Search
05Automatic Background Memory Consolidation
04

Use Cases

memora logomemora
↳AI Agent Memory Management: Giving AI agents long-term, structured memory for complex, multi-session tasks.
↳Knowledge Base for Agents: Building a retrievable knowledge base that agents can query semantically and contextually.
↳Project Management & Task Tracking: Automating the creation and tracking of TODOs and issues, and surfacing insights for project progress.
↳Document Analysis & Retrieval: Storing and searching structured documents (e.g., reports, plans) at a granular fragment level.
↳Contextual Conversation for AI: Powering RAG-based chat panels that allow agents or users to converse deeply about stored memories.
mneme logomneme
↳Continuing project discussions across multiple sessions without repetition.
↳Persisting AI's understanding of user preferences and coding habits long-term.
↳Automatic archiving and retrieval of organized research notes after closing chat windows.
05

Best For

memora logomemora
TrendingHidden Gem
mneme logomneme
—
FAQ

FAQ

What is the difference between memora and mneme?
Both memora and mneme are in the Memory & Context category. memora has 744 stars, while mneme has 167 stars.
Which is better, memora or mneme?
The best choice depends on your use case. Choose memora if AI Agent Memory Management: Giving AI agents long-term, structured memory for complex, multi-session tasks., and mneme if Continuing project discussions across multiple sessions without repetition..
Is memora free or open source?
Yes, memora is open source on GitHub (MIT).
Is mneme free or open source?
Yes, mneme is open source on GitHub (MIT).
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Alternatives to memora →Alternatives to mneme →memora details →mneme details →