AgentIndex icon
AgentIndex
rlm-claude logo
rlm-claude
★ 39
vs
remem logo
remem
★ 34

rlm-claude vs remem

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.; remem: `remem` is a local-first memory solution for AI coding agents like Claude Code and OpenAI Codex, preventing repetitive explanations by automatically capturing and injecting project context. It distills, searches, and stores project decisions, bug fixes, and preferences locally using SQLite, accessible via CLI, hooks, and a REST API.

01

TL;DR

rlm-claude logo
rlm-claudeMemory & Context · ★ 39

Preventing context and decision loss during long Claude Code development sessions.

Read rlm-claude full review →
remem logo
rememMemory & Context · ★ 34

Avoiding repetitive project explanations to AI coding agents.

Read remem full review →
02

Side-by-Side Comparison

Field
rlm-claude logorlm-claude
remem logoremem
Category
Memory & Context
Memory & Context
Stars
★ 39
★ 34
License
MIT
MIT
Install Command
pip install mcp-rlm-server[all]
curl -fsSL https://raw.githubusercontent.com/majiayu000/remem/main/install.sh | env REMEM_NO_CONFIG=1 sh && ~/.local/bin/remem install --target codex
Updated
2w ago
2d ago
Open Source
Yes
Yes
Website
↗ Visit
↗ Visit
GitHub
↗ GitHub
↗ GitHub
Tags
Persistent Memory, Claude Code Integration, Context Management
AI Agent Memory, Context Management, Coding Assistant
03

Features

rlm-claude logorlm-claude
01Automatic 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.
remem logoremem
01Automatic memory capture and injection for coding agents.
02Searchable history of project decisions, bug fixes, and rationale.
03Local-first memory storage with SQLite and SQLCipher encryption.
04Accessible via CLI, coding agent hooks, MCP tools, and REST API.
05Single Rust binary with no external database dependencies.
04

Use Cases

rlm-claude logorlm-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.
remem logoremem
↳Avoiding repetitive project explanations to AI coding agents.
↳Searching and recalling past project decisions and bug-fix rationale.
↳Maintaining an auditable and project-scoped history of engineering memory.
↳Reducing the need for manual upkeep of large memory documentation files.
FAQ

FAQ

What is the difference between rlm-claude and remem?
Both rlm-claude and remem are in the Memory & Context category. rlm-claude has 39 stars, while remem has 34 stars.
Which is better, rlm-claude or remem?
The best choice depends on your use case. Choose rlm-claude if Preventing context and decision loss during long Claude Code development sessions., and remem if Avoiding repetitive project explanations to AI coding agents..
Is rlm-claude free or open source?
Yes, rlm-claude is open source on GitHub (MIT).
Is remem free or open source?
Yes, remem is open source on GitHub (MIT).
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