memini logo
memini
★ 28
vs
claude-mem-lite logo
claude-mem-lite
★ 67

memini vs claude-mem-lite

memini: memini is a shared, persistent memory service designed for AI agents, providing a single location for agents to remember and recall information with continuously improving retrieval quality. It's built as a Go binary, offers zero-configuration startup, and scales from embedded SQLite on a laptop to Postgres in Kubernetes.; 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

memini logo
meminiMemory & Context · ★ 28

Enhancing AI Agents with Long-Term Memory: Integrate memini to give AI agents (like Claude Code, opencode, Hermes) the ability to remember past interactions and learn over time.

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

Recalling past bug fixes and coding decisions across sessions.

02

Side-by-Side Comparison

Field
memini logomemini
claude-mem-lite logoclaude-mem-lite
Category
Memory & Context
Memory & Context
Stars
★ 28
★ 67
License
AGPL-3.0
MIT
Install Command
export MEMINI_EMBED_BASE_URL=http://localhost:8081/v1 && export MEMINI_EMBED_MODEL=bge-m3 && export MEMINI_EMBED_DIMS=1024 && mise run run
npx github:sdsrss/claude-mem-lite
Updated
3d ago
1d ago
Open Source
Yes
Yes
Tags
AI Agents, Persistent Memory, Vector Search
Persistent Memory, LLM Memory Management, Claude Code Plugin
03

Features

memini logomemini
01Shared, Persistent Memory: Provides a dedicated service for AI agents to store and retrieve memories, designed for long-term persistence.
02Hybrid Retrieval & Re-ranking: Employs a hybrid (vector + keyword) retrieval method, fused with Reciprocal Rank Fusion (RRF), and re-ranks results by relevance, recency, and importance, not just similarity.
03Tiered Memory System: Implements a tiered memory structure (working, episodic, semantic, procedural) with decay mechanisms.
04Pluggable Storage: Supports flexible storage options, including embedded SQLite-vec for local use and Postgres with VectorChord for scalable deployments.
05Optional LLM Consolidation: Features an opt-in LLM consolidation pipeline for background deduplication and contradiction resolution, but can run headless (without an LLM) using marker heuristics.
06Model Context Protocol (MCP) Support: Compatible with MCP-capable agents, offering both Streamable HTTP and stdio transports.
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

memini logomemini
↳Enhancing AI Agents with Long-Term Memory: Integrate memini to give AI agents (like Claude Code, opencode, Hermes) the ability to remember past interactions and learn over time.
↳Self-Hosting a Shared Memory Service: Deploy memini for a team or homelab environment to provide a centralized, persistent memory store for multiple AI agents.
↳Improving AI Recall Quality: Tune memini's retrieval parameters to fix bad recall and achieve higher accuracy in retrieving relevant information for AI models.
↳Managing Multi-Agent Namespaces: Lay out distinct namespaces within memini to provide isolation and organized memory management for several different AI agents.
↳Backend for Open WebUI Memory: Utilize memini as a robust memory backend for platforms like Open WebUI, integrating its memory and tool capabilities.
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.
FAQ

FAQ

What is the difference between memini and claude-mem-lite?
Both memini and claude-mem-lite are in the Memory & Context category. memini has 28 stars, while claude-mem-lite has 67 stars.
Which is better, memini or claude-mem-lite?
The best choice depends on your use case. Choose memini if Enhancing AI Agents with Long-Term Memory: Integrate memini to give AI agents (like Claude Code, opencode, Hermes) the ability to remember past interactions and learn over time., and claude-mem-lite if Recalling past bug fixes and coding decisions across sessions..
Is memini free or open source?
Yes, memini is open source on GitHub (AGPL-3.0).
Is claude-mem-lite free or open source?
Yes, claude-mem-lite is open source on GitHub (MIT).
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