rlm-claude
★ 39
vs
letta
★ 25.2k
rlm-claude vs letta
rlm-claude: RLM is an MCP server designed to provide Claude Code with persistent memory, preventing loss of conversation history and context after `/compact` operations. It offers advanced memory management features including insights, chunking, and intelligent retention, enabling more productive and context-aware AI interactions.; 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.
01
TL;DR
rlm-claudeMemory & Context · ★ 39
Preventing context and decision loss during long Claude Code development sessions.
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.
02
Side-by-Side Comparison
Field
rlm-claudelettaCategory
Memory & Context
Memory & Context
Stars
★ 39
★ 25.2k
License
MIT
Apache-2.0
Install Command
pip install mcp-rlm-server[all]
npm install -g @letta-ai/letta-code
Updated
2w ago
5d ago
Open Source
Yes
Yes
Tags
Persistent Memory, Claude Code Integration, Context Management
Stateful AI, Agent Platform, Advanced Memory
03
Features
rlm-claude01Automatic snapshot saving before context loss during `/compact`.
02Dual memory systems: 'Insights' for key decisions/facts and 'Chunks' for full conversation segments.
03Hybrid search combining BM25 keyword matching and semantic cosine similarity.
04Smart retention lifecycle with active, archive, and purge zones, and immunity for critical data.
05Multi-project and multi-domain organization for memory and search filtering.
letta01Build 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
04
Use Cases
rlm-claude↳Preventing context and decision loss during long Claude Code development sessions.
↳Efficiently recalling past project details, architectural decisions, and technical findings.
↳Organizing and searching through AI-generated knowledge across different projects and domains.
↳Revisiting debug sessions and past solutions for problem-solving and code refactoring.
↳Maintaining universal rules and preferences that apply across all AI interactions.
letta↳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.
05
Best For
rlm-claude—
lettaMost PopularEssentialTrending
FAQ
FAQ
What is the difference between rlm-claude and letta?
Both rlm-claude and letta are in the Memory & Context category. rlm-claude has 39 stars, while letta has 25.2k stars.
Which is better, rlm-claude or letta?
The best choice depends on your use case. Choose rlm-claude if Preventing context and decision loss during long Claude Code development sessions., and letta if Running AI agents locally in your terminal for coding and general tasks..
Is rlm-claude free or open source?
Yes, rlm-claude is open source on GitHub (MIT).
Is letta free or open source?
Yes, letta is open source on GitHub (Apache-2.0).
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