







Platform for stateful agents: AI with advanced memory that can learn and self-improve over time.
mem-agent: Equipping LLM Agents with Memory Using RL
The insights and the technical report behind Mem-Agent, our 4B model for persistent memory in LLMs
MemGPT
Memory-GPT (MemGPT) - Towards LLMs as Operating Systems - Teach LLMs to manage their own memory for unbounded context!
Memory in Agents: What, Why and How
LLM memory gives language models persistent context across sessions. Learn how it works, how it differs from RAG and context windows, and how to add LLM memory to your agents with Mem0.

The AI Operating System: Stateful Agents with Letta | Cameron Pfiffer, AI By the Bay25
MemGPT: Towards LLMs as Operating Systems
Large language models (LLMs) have revolutionized AI, but are constrained by limited context windows, hindering their utility in tasks like extended conversations and document analysis. To enable using context beyond limited context windows, we propose virtual context management, a technique drawing inspiration from hierarchical memory systems in traditional operating systems that provide the appearance of large memory resources through data movement between fast and slow memory. Using this technique, we introduce MemGPT (Memory-GPT), a system that intelligently manages different memory tiers in order to effectively provide extended context within the LLM's limited context window, and utilizes interrupts to manage control flow between itself and the user. We evaluate our OS-inspired design in two domains where the limited context windows of modern LLMs severely handicaps their performance: document analysis, where MemGPT is able to analyze large documents that far exceed the underlying LLM's context window, and multi-session chat, where MemGPT can create conversational agents that remember, reflect, and evolve dynamically through long-term interactions with their users. We release MemGPT code and data for our experiments at https://memgpt.ai.

Pieces | Infinite Artificial Memory for your Digital Workers and Agents
Pieces is your AI companion that captures live context from browsers to IDEs and collaboration tools, manages snippets and supports multiple llms - all while processing data locally for maximum control.

Stevens: a hackable AI assistant using a single SQLite table and a handful of cron jobs
There’s a lot of hype these days around patterns for building with AI. Agents, memory, RAG, assistants—so many buzzwords! But the reality is, you don’t need fancy techniques or libraries to build useful personal tools with LLMs.

Supermemory
The memory layer for AI agents. Context engineering platform powering enterprise APIs, developer plugins, and a personal app that remembers everything.

I Benchmarked OpenAI Memory vs LangMem vs Letta (MemGPT) vs Mem0 for Long-Term Memory: Here’s How They Stacked Up
145 votes, 53 comments. Lately, I’ve been testing memory systems to handle long conversations in agent setups, optimizing for: Factual consistency…
Letta
Making machines that learn. Create stateful agents that remember everything, learn continuously, and improve themselves over time.

OpenMemory - AI Memory MCP Server for Coding Agents | Mem0
With OpenMemory, add persistent, project-aware memory to Cursor, Windsurf, and VS Code agents. Store preferences, patterns, and context that get retrieved automatically.

crockpotveggies/execlaw
Self-hosted AI agent with persistent memory, plugins, tools, and skills written in Rust
Understanding memory management
Learn MemGPT memory management techniques for controlling LLM context windows with in-context and external storage.

Heaps do lie: debugging a memory leak in vLLM. | Mistral AI
The most powerful AI platform for enterprises. Customize, fine-tune, and deploy AI assistants, autonomous agents, and multimodal AI with open models.
project-you-apps/membot
MCP server that gives AI agents physics-enhanced memory via swappable brain cartridges
Memvid - Give your AI Agent Photographic Memory
Replace complex RAG pipelines with a single portable file that gives every agent instant retrieval and long-term memory.
