Stateful agents with self-managed, layered memory that learn and improve over time
Key Features
Multi-Agent
Single Agent
Human-in-the-Loop
Streaming
Async Support
Type Safe
Short-Term Memory
Long-Term Memory
Shared Memory
Plugin System
Custom Tools
MCP Protocol
A2A Protocol
Code Execution
Web Browsing
File System Access
Sandboxing
Guardrails
Structured Output
DAG Workflows
Visual Builder
CLI
API Server
Self-Hosted
Cloud Hosted
Community Feedback
Strengths
- Best-in-class memory management
- Pioneering LLM-as-OS paradigm
- Research-backed (UC Berkeley)
- Strong documentation
- #1 model-agnostic on Terminal-Bench
Weaknesses
- Memory management complexity
- Architecture transition (MemGPT to Letta V1)
- Learning curve
Letta (MemGPT) Details
| Organization | Letta Inc (UC Berkeley spin-off) |
| Organization Type | Company |
| Funding | Seed |
| Category | Framework |
| Subcategory | Single agent |
| Deployment | Hybrid |
| Primary Language | Python |
| Runtime | Python 3.10+ |
| License | Apache-2.0 |
| Commercial Use | Permissive |
| Install Command | pip install letta |
| GitHub Stars | 21,736 |
| GitHub Forks | 2,295 |
| Release Cadence | Biweekly |
| Maturity | Stable |
| Pricing Model | Open core |
| Free Tier | Apache-2.0 licensed core is free |
| Self-Hosted Free | Yes |
| Cost Model | free + LLM costs |
| Community Size | Large (22k stars) |
| Community Activity | Very active |
| Sentiment | Positive |
| GPU Required | No |
| Confidence | High |
| Research Date | 2026-03-24 |
| LLM Providers | OpenAI, Anthropic, Google, local models |
| API Keys Required | LLM provider API key |
Use Cases
- Long-running conversational agents
- Agents that learn and improve over time
- Persistent personal assistants
- Knowledge management with agent memory
Similar Tools
When to Use
Best for: Long-running agents needing persistent, self-managed memory
Avoid when: Simple stateless agent workflows or rapid prototyping
Original data from HuggingFace, OpenCompass and various public git repos.
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Release v20260324