A curated list of awesome Letta projects, tools, tutorials, and resources for building stateful AI agents with persistent memory.
Letta is the leading platform for building AI agents with persistent memory. Unlike traditional chatbots that forget everything between sessions, Letta agents remember, learn, and improve over time.
- Official Resources
- Tutorials & Guides
- Example Projects
- Tools & Integrations
- Agent Templates
- Research & Papers
- Videos & Talks
- Community
- Contributing
- Letta Website - Official website and product information
- Letta Documentation - Comprehensive documentation and API reference
- Letta GitHub - Official Letta repository
- Letta Cloud - Hosted Letta platform
- Letta Blog - Official blog with technical deep-dives and announcements
- Letta Leaderboard - Leaderboard to determine how to choose the best language models for your agent [Repo]
- Letta Python SDK - Python SDK for Letta
- Letta TypeScript SDK - TypeScript SDK for Letta
- AI Memory SDK - A lightweight agent memory SDK for Letta for adding agentic memory and learning in a pluggable way
- Letta Quickstart - Official quickstart guide
- Building Your First Agent - Step-by-step tutorial
- DeepLearning.AI Course - Free course on building with Letta
- Create Letta demo applications - Create Letta App lets you create apps with Letta
- Memory Architecture Design - Guide to designing effective memory blocks
- Letta's Filesystem - Using Letta's filesystem capabilities
- Multi-Agent Systems - Building coordinated agent teams
- Custom Tools Development - Creating custom tools for agents
- Thought stream agent handler - Deploy Letta agents onto the thought stream.
- Thought stream web viewer, an ATProto-powered multi-agent chatroom.
- Thought stream CLI for using the thought stream, not unlike IRC.
- Letta Chatbot template - An example Next.js chatbot application built on the Letta API, which makes each chatbot a stateful agent (agent with memory) under the hood.
- Letta Examples Repository - Official example implementations
- Vercel AI SDK Provider Examples - AI SDK integration examples
- Discord bot An example Discord chatbot built on the Letta API, which uses a stateful agent (agent with memory) under the hood.
- CharacterPlus - Example CharacterAI-style web app that runs on Letta to create characters with memory.
- Vercel AI SDK Provider - Use Letta with Vercel AI SDK v5
- Zapier Integration - Use Letta with Zapier
- Telegram - A Modal application for serving a Letta agent on Telegram.
- Obsidian - A Obsidian plugin for serving a Letta agent on Obsidian.
- n8n - Connect your Letta agent to n8n workflows.
- Your tool here! - Submit a PR
- Letta CLI - Command-line interface for Letta
- Agent Development Environment - Web-based agent IDE
Letta's agent file format is a standard file format for serializing statful AI agents. Learn more about it in our blog post.
In this section, you should add pre-configured agent templates for common use cases:
- Personal Assistant - General-purpose assistant with user preferences tracking
- Research Companion - Knowledge accumulation and synthesis
- Customer Support - Context-aware support with conversation history
- Code Review Assistant - Codebase-aware review and suggestions
- Learning Tutor - Adaptive educational agent
Note: Submit your agent templates via PR! Include memory block structure, tools, and use case description.
- MemGPT: Towards LLMs as Operating Systems - Original MemGPT paper
- Recovery-Bench: Evaluating LLMs' Ability to Recover from Mistakes - Research on agent error recovery
- Sleep-time Compute - Research on agent sleep-time compute, with accompanying GitHub repository and blog post
- Terminal-Bench - Letta integration for terminal-bench [Blog post]
- Recovery-Bench - Recovery-Bench is a benchmark for evaluating the capability of LLM agents to recover from mistakes [Blog post]
- Introducing Recovery-Bench: Evaluating LLMs' Ability to Recover from Mistakes - August 27, 2025
- Benchmarking AI Agent Memory: Is a Filesystem All You Need? - August 12, 2025
- Building the #1 Open Source Terminal-Use Agent Using Letta - August 5, 2025
- Agent Memory: How to Build Agents that Learn and Remember - July 7, 2025
- Anatomy of a Context Window: A Guide to Context Engineering - July 3, 2025
- Letta Leaderboard: Benchmarking LLMs on Agentic Memory - May 29, 2025
- Memory Blocks: The Key to Agentic Context Management - May 14, 2025
- Sleep-time Compute - April 21, 2025
- RAG is not Agent Memory - February 13, 2025
- Stateful Agents: The Missing Link in LLM Intelligence - February 6, 2025
- The AI Agents Stack - November 14, 2024
- Introducing Letta Filesystem - July 24, 2025
- Announcing Letta Client SDKs for Python and TypeScript - April 17, 2025
- Agent File - April 2, 2025
- Introducing the Agent Development Environment - January 15, 2025
- Letta v0.6.4 Release - December 13, 2024
- New Course on Letta with DeepLearning.AI - November 7, 2024
- Letta v0.5.2 Release - November 6, 2024
- Letta v0.5.1 Release - October 23, 2024
- Letta v0.5 Release - October 14, 2024
- Letta v0.4.1 Release - October 3, 2024
- Announcing Letta - September 23, 2024
- MemGPT is now part of Letta - September 23, 2024
- The Letta YouTube channel - Official Letta YouTube channel
- Letta Memory Tool Demo - Agents that redesign their own architecture
- How to use Archival Memory - How to use Letta's archival memory for storing long-term memory
- Building a self-improving deep research agent - How to build a self-improving deep research agent using Letta in just a few minutes
- An introduction to personality design - How to design a personality for your Letta agent
- The basics of memory architecture - How to iteratively improve a Letta agent's memory architecture
- Adding knowledge graphs with neo4j to Letta - Use MCP and Letta Desktop to build a knowledge graph
- How to use the Zapier integration - Connect your Letta agent to any external service
- Stateful Agents Meetup: Networks - Recording of the Stateful Agents Meetup hosted by Letta and Nokia.
- Coming soon - share your tutorial videos!
- Discord - Official Discord community
- Forum - Official Forum
- Bluesky - Official Bluesky profile
- Twitter/X - Follow for updates
- Community Showcase - #showcase channel in Discord
- Interact with your Letta agent using n8n and Telegram - Guide to connect Letta agents with n8n and Telegram
- Submit your projects here via PR!
Contributions are welcome! Please read the contribution guidelines first.
How to contribute:
- Fork this repository
- Add your resource in the appropriate category
- Ensure your addition follows the format:
[Resource Name](url) - Brief description - Submit a pull request
Criteria for inclusion:
- Must be related to Letta or stateful agent development
- Must be functional and actively maintained (for tools/projects)
- Must provide value to the Letta community
- Preferably open source (for projects and tools)
