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Adaptive Memory Graph

Registre officiel IA et agents

Persistent memory for Claude via weighted, interconnected knowledge nodes.

Code source Documentation

Que pouvez-vous faire avec Adaptive Memory Graph ?

  • Weighted memory nodes — Important memories stay prominent; stale ones fade
  • Cross-domain connections — Link related knowledge across topics
  • Time-based decay — Graph self-prunes so only relevant memories persist
  • Encrypted storage — AES-256-GCM encryption with macOS Keychain key storage
  • Session logging — Tracks which memories were accessed and how they were received
  • Domain organization — Nodes organized by domain (e.g. health_and_safety, personal, ideas_and_projects)
  • Chat history ingestion — Review and extract knowledge from past Claude Code sessions

Installation

Ajoutez ceci à la configuration MCP de votre client (Claude Desktop : claude_desktop_config.json ; Cursor : .cursor/mcp.json ; VS Code et les autres utilisent la même forme « mcpServers »).

PYPI package adaptive-memory-graph
Claude Code 
claude mcp add adaptive-memory-graph -- uvx adaptive-memory-graph==1.1.1
Configuration JSON (Claude Desktop, Cursor, VS Code) 
{
    "mcpServers": {
        "adaptive-memory-graph": {
            "command": "uvx",
            "args": [
                "adaptive-memory-graph==1.1.1"
            ]
        }
    }
}

Documentation

Tirée du README du projet sur GitHub, actualisée chaque semaine. Les liens ouvrent GitHub.

Sommaire
  1. Adaptive Memory Graph
  2. Features
  3. Installation
  4. Setup
  5. Tools
  6. How It Works
  7. Requirements
  8. License

Adaptive Memory Graph

An MCP server plugin that gives Claude persistent, intelligent memory across sessions. It stores knowledge as weighted, interconnected nodes in a graph that evolves through conversation — nodes that get used gain weight, unused ones decay and eventually archive.

Works with Claude Code and Claude Desktop.

Features

  • Weighted memory nodes — Important memories stay prominent; stale ones fade
  • Cross-domain connections — Link related knowledge across topics
  • Time-based decay — Graph self-prunes so only relevant memories persist
  • Encrypted storage — AES-256-GCM encryption with macOS Keychain key storage
  • Session logging — Tracks which memories were accessed and how they were received
  • Domain organization — Nodes organized by domain (e.g. health_and_safety, personal, ideas_and_projects)
  • Chat history ingestion — Review and extract knowledge from past Claude Code sessions

Installation

pip install adaptive-memory-graph

Or with uv:

uv pip install adaptive-memory-graph

Setup

Claude Code
claude mcp add adaptive-memory-graph -s user -- amg-server
Claude Desktop

Add to your claude_desktop_config.json:

{
  "mcpServers": {
    "adaptive-memory-graph": {
      "command": "amg-server"
    }
  }
}

Config file location:

  • macOS: ~/Library/Application Support/Claude/claude_desktop_config.json
  • Windows: %APPDATA%\Claude\claude_desktop_config.json

Tools

ToolDescription
amg_load_indexLoad lightweight graph index at session start
amg_expand_branchFetch full node content when contextually relevant
amg_get_connected_nodesFind related nodes across domains
amg_log_sessionLog session summary at conversation end
amg_update_graphProcess pending logs and apply weight decay
amg_export_reportGenerate human-readable graph summary
amg_manual_adjustBoost, decay, archive, or delete nodes
amg_add_nodeAdd new nodes to the graph
amg_search_nodesSearch nodes by title, summary, tags, or content
amg_list_chat_sessionsList available Claude Code chat sessions for review
amg_read_chat_sessionRead a chat session's conversation content

How It Works

  1. Session start — Claude calls amg_load_index to get a lightweight summary of your memory graph
  2. During conversation — If a topic is relevant, Claude expands specific nodes for deeper context
  3. Session end — Claude silently logs which nodes were accessed and suggests new ones
  4. Between sessions — Weight decay runs, archiving memories that haven't been useful

Nodes are stored as encrypted JSON on disk (~/.amg/graph.json.enc). The encryption key is stored in your macOS Keychain.

Requirements

  • Python 3.10+
  • macOS (for Keychain-based encryption key storage)

License

MIT

Questions fréquentes

Qu'est-ce que Adaptive Memory Graph ?

Persistent memory for Claude via weighted, interconnected knowledge nodes.

Comment installer Adaptive Memory Graph ?

Il s'exécute sur votre machine. Dans Claude Code : claude mcp add adaptive-memory-graph -- uvx adaptive-memory-graph==1.1.1. Pour les autres clients, collez la configuration JSON de cette page dans leurs réglages MCP.

Faut-il une clé API pour Adaptive Memory Graph ?

Son entrée au registre n'indique aucune clé ni secret obligatoire. Certaines fonctions peuvent tout de même demander un compte auprès du service auquel il se connecte.

Adaptive Memory Graph est-il open source ?

Oui. Son code est sur GitHub sous licence MIT.

Qui maintient Adaptive Memory Graph ?

Il est publié par raskolnikovdd. AI.tn le référence sans le maintenir ni le recommander.

Issu du registre MCP officiel. Être listé n'est pas une recommandation : vérifiez le code et les permissions d'un serveur avant de lui donner accès à vos données.