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Agent Memory

kensavebykensave
•
3
•
개발자 도구
데이터 과학 및 ML
생산성 및 워크플로

Manages comprehensive memory for AI agents, implementing episodic, semantic, and procedural memory with automatic consolidation, intelligent decay, and hierarchical retrieval.

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둘러보기

  • MCP 검색
  • MCP 서버
  • MCP 클라이언트
  • Claude 스킬
  • MCP Market Hub
  • 카테고리
  • MCP 서버란 무엇인가요?
  • Model Context Protocol

순위

  • 오늘의 인기 MCP
  • 오늘의 인기 Claude 스킬
  • Claude 스킬 Top 100
  • MCP 서버 Top 100

소개

  • 뉴스
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  • 문의하기

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Agent Memory RS offers a sophisticated memory management system designed for LLM agents, built on modern AI research and cognitive science. It provides three distinct memory types: episodic memory for interaction events, semantic memory for consolidated knowledge, and procedural memory for learned workflows. Key capabilities include auto-consolidation of memories, intelligent decay based on composite scoring, hybrid search, and hierarchical retrieval, ensuring agents have efficient access to relevant information through its MCP server support and CLI tools.

주요 기능

01Intelligent Decay (composite scoring for memory archival)
02Hierarchical Retrieval (multi-level memory access from synopsis to archived)
03MCP Server (Model Context Protocol integration for AI assistants)
04Hybrid Search (BM25 keyword + vector semantic search with RRF fusion)
05Auto-Consolidation (nightly pattern extraction, daily synopsis generation)
060 GitHub stars

사용 사례

01Enabling LLM agents to learn and adapt workflows over time
02Providing persistent, context-aware memory for long-running AI applications
03Integrating advanced memory capabilities into custom AI assistants