adaptive-memory-graph
Click on "Install Server".
Wait a few minutes for the server to deploy. Once ready, it will show a "Started" state.
In the chat, type
@followed by the MCP server name and your instructions, e.g., "@adaptive-memory-graphRemember that I prefer dark mode in code editors"
That's it! The server will respond to your query, and you can continue using it as needed.
Here is a step-by-step guide with screenshots.
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
Related MCP server: Fuzzy Memory MCP Server
Installation
pip install adaptive-memory-graphOr with uv:
uv pip install adaptive-memory-graphSetup
Claude Code
claude mcp add adaptive-memory-graph -s user -- amg-serverClaude 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.jsonWindows:
%APPDATA%\Claude\claude_desktop_config.json
Tools
Tool | Description |
| Load lightweight graph index at session start |
| Fetch full node content when contextually relevant |
| Find related nodes across domains |
| Log session summary at conversation end |
| Process pending logs and apply weight decay |
| Generate human-readable graph summary |
| Boost, decay, archive, or delete nodes |
| Add new nodes to the graph |
| Search nodes by title, summary, tags, or content |
| List available Claude Code chat sessions for review |
| Read a chat session's conversation content |
How It Works
Session start — Claude calls
amg_load_indexto get a lightweight summary of your memory graphDuring conversation — If a topic is relevant, Claude expands specific nodes for deeper context
Session end — Claude silently logs which nodes were accessed and suggests new ones
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
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