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Adaptive Memory Graph

Official registry AI and agents

Persistent memory for Claude via weighted, interconnected knowledge nodes.

Source code Documentation

What can you do with 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

Install

Add this to your client's MCP configuration (Claude Desktop: claude_desktop_config.json; Cursor: .cursor/mcp.json; VS Code and others use the same "mcpServers" shape).

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

Documentation

From the project's README on GitHub, refreshed weekly. Links open on GitHub.

Contents
  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

Frequently asked questions

What is Adaptive Memory Graph?

Persistent memory for Claude via weighted, interconnected knowledge nodes.

How do I install Adaptive Memory Graph?

It runs on your machine. In Claude Code: claude mcp add adaptive-memory-graph -- uvx adaptive-memory-graph==1.1.1. For other clients, paste the JSON configuration from this page into their MCP settings.

Does Adaptive Memory Graph need an API key?

Its registry entry lists no required key or secret. Some features may still need an account with the service it connects to.

Is Adaptive Memory Graph open source?

Yes. Its code is on GitHub under the MIT license.

Who maintains Adaptive Memory Graph?

It is published by raskolnikovdd. AI.tn lists it but does not maintain or endorse it.

From the official MCP Registry. Listing is not an endorsement: review a server's code and permissions before giving it access to your data.