letta logo
letta
★ 25.2k
vs
mnemo logo
mnemo
★ 12

letta vs mnemo

letta: Letta is a powerful platform for building stateful AI agents equipped with advanced memory, enabling them to learn and self-improve over time. It provides both a command-line interface for local agent execution and a comprehensive API with Python and TypeScript SDKs for seamless integration into applications.; mnemo: Mnemo is an open, free, and unlimited persistent AI memory system featuring hybrid search and embedded synchronization. It integrates full-text search with vector search, temporal decay, and importance boosting for advanced retrieval.

01

TL;DR

letta logo
lettaMemory & Context · ★ 25.2k
When to choose:
  • You want a long-lived agent that remembers past work and rewrites its own memory and context over time.
  • You want one agent reachable from CLI, desktop, browser, mobile and messaging apps, with subagents, schedules and hooks.
  • You want memory you can inspect: the README says context is tracked in git and can sync to your own repository.
When to skip:
  • You only need to add memory to an agent you already use through MCP; a small MCP memory server is a lighter fit.
  • You rely on older Letta tutorials or the V1 API server: the project restructured, and the V1 server is retired.
  • You want everything to work without signing in: Letta Cloud is the default backend and some features need it.
mnemo logo
mnemoMemory & Context · ★ 12

Providing persistent long-term and short-term memory for AI agents to enhance their context and decision-making.

02

Side-by-Side Comparison

Field
letta logoletta
mnemo logomnemo
Category
Memory & Context
Memory & Context
Stars
★ 25.2k
★ 12
License
Apache-2.0
Apache-2.0
Install Command
npm install -g @letta-ai/letta-code
/plugin marketplace add n24q02m/claude-plugins && /plugin install mnemo-mcp@n24q02m-plugins
Updated
5d ago
1d ago
Open Source
Yes
Yes
Tags
Stateful AI, Agent Platform, Advanced Memory
AI Memory, Hybrid Search, Vector Database
03

Features

letta logoletta
01Build stateful AI agents with advanced memory
02Agents capable of learning and self-improvement over time
03CLI tool for running agents locally in your terminal
04Comprehensive API for integrating agents into applications
05Support for skills and subagents; fully model-agnostic
mnemo logomnemo
01Hybrid retrieval combining full-text search (FTS5) and vector search, fused via Reciprocal Rank Fusion, then re-ranked with temporal decay and importance boost.
02Automatic entity extraction and relation tracking to build a temporal knowledge graph, boosting top search results by graph proximity.
03Multi-machine sync via Google Drive with JSONL-based merge sync, and end-to-end encrypted passport sync using AES-256-GCM and Argon2id for secure cross-device bootstrap.
04LLM-driven compression of older memories and LLM summarization of related memories for STM-to-LTM consolidation, achieving significant token reduction.
05Zero-config local setup using Fastretrieval's built-in Qwen3 ONNX embedding and reranking models, requiring no external API keys for basic operation.
04

Use Cases

letta logoletta
↳Running AI agents locally in your terminal for coding and general tasks.
↳Integrating stateful AI agents into custom applications using the API and SDKs.
↳Developing self-improving AI systems that adapt and learn continually.
mnemo logomnemo
↳Providing persistent long-term and short-term memory for AI agents to enhance their context and decision-making.
↳Building and querying a temporal knowledge graph to understand historical states and relationships of entities within an AI system's memory.
↳Synchronizing AI memory across multiple machines or devices securely, enabling a consistent knowledge base for agents.
↳Improving the efficiency of LLM interactions by compressing older memories and consolidating related information.
↳Integrating with various AI clients (e.g., Claude Code, Gemini CLI, Cursor) as an MCP server for advanced memory management.
05

Best For

letta logoletta
Most PopularEssentialTrending
mnemo logomnemo
—
FAQ

FAQ

What is the difference between letta and mnemo?
Both letta and mnemo are in the Memory & Context category. letta has 25.2k stars, while mnemo has 12 stars.
Which is better, letta or mnemo?
The best choice depends on your use case. Choose letta if Running AI agents locally in your terminal for coding and general tasks., and mnemo if Providing persistent long-term and short-term memory for AI agents to enhance their context and decision-making..
Is letta free or open source?
Yes, letta is open source on GitHub (Apache-2.0).
Is mnemo free or open source?
Yes, mnemo is open source on GitHub (Apache-2.0).
Cloud Infrastructure
Ad

Deploy on DigitalOcean

Host your MCP servers, Docker containers, and AI agents with $200 free credit over 60 days.

Claim $200 Free Credit
→

Related