rlm-claude
Active·★ 39·MIT·Updated 2026-10-07
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.
#Persistent Memory#Claude Code Integration#Context Management#Semantic Search#AI Agent Memory#Data Retention#Multi-Project Support
01
Features
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.
02
Compatibility
Python
Runtime
Verified via docs
Claude Code CLI
Tool Integration
Verified via docs
Docker
Deployment
Verified via docs
Model Context Protocol (MCP)
Protocol
Verified via docs
03
Quick start
1
$ pip install mcp-rlm-server[all]
04
Use cases
↳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.
05
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