memora logo
memora
★ 744
vs
claude-mem-lite logo
claude-mem-lite
★ 67

memora vs claude-mem-lite

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`.; claude-mem-lite: claude-mem-lite provides a persistent, cross-session memory system for Claude Code, automatically capturing coding observations and decisions. It uses an MCP server and hooks for efficient, cost-optimized context recall via hybrid full-text and semantic search.

01

TL;DR

memora logo
memoraMemory & Context · ★ 744

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

claude-mem-lite logo
claude-mem-liteMemory & Context · ★ 67

Recalling past bug fixes and coding decisions across sessions.

02

Side-by-Side Comparison

Field
memora logomemora
claude-mem-lite logoclaude-mem-lite
Category
Memory & Context
Memory & Context
Stars
★ 744
★ 67
License
MIT
MIT
Install Command
pip install git+https://github.com/agentic-box/memora.git
npx github:sdsrss/claude-mem-lite
Updated
1d ago
1d ago
Open Source
Yes
Yes
Tags
AI Agents, Persistent Memory, Knowledge Graph
Persistent Memory, LLM Memory Management, Claude Code 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
claude-mem-lite logoclaude-mem-lite
01Automatic observation capture via Claude Code hooks.
02Hybrid full-text and semantic search (FTS5 + TF-IDF) with RRF.
03Episode batching for significant LLM cost reduction.
04Error-triggered and proactive file history recall.
05Cross-language synonym expansion (CJK↔EN) for enhanced search.
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.
claude-mem-lite logoclaude-mem-lite
↳Recalling past bug fixes and coding decisions across sessions.
↳Maintaining project context for AI coding agents over long periods.
↳Automatically getting relevant historical context when interacting with files.
↳Optimizing LLM token usage and cost for AI agent memory.
↳Zero-touch documentation of coding workflows and lessons learned.
05

Best For

memora logomemora
TrendingHidden Gem
claude-mem-lite logoclaude-mem-lite
—
FAQ

FAQ

What is the difference between memora and claude-mem-lite?
Both memora and claude-mem-lite are in the Memory & Context category. memora has 744 stars, while claude-mem-lite has 67 stars.
Which is better, memora or claude-mem-lite?
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 claude-mem-lite if Recalling past bug fixes and coding decisions across sessions..
Is memora free or open source?
Yes, memora is open source on GitHub (MIT).
Is claude-mem-lite free or open source?
Yes, claude-mem-lite is open source on GitHub (MIT).
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