Adaptive Memory Graph

数据与存储

by raskolnikovdd

通过加权且相互连接的知识节点,为 Claude 提供可持续保存与关联检索的记忆能力。

什么是 Adaptive Memory Graph

通过加权且相互连接的知识节点,为 Claude 提供可持续保存与关联检索的记忆能力。

README

Adaptive Memory Graph

<!-- mcp-name: io.github.raskolnikovdd/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

bash
pip install adaptive-memory-graph

Or with uv:

bash
uv pip install adaptive-memory-graph

Setup

Claude Code

bash
claude mcp add adaptive-memory-graph -s user -- amg-server

Claude Desktop

Add to your claude_desktop_config.json:

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

常见问题

Adaptive Memory Graph 是什么?

通过加权且相互连接的知识节点,为 Claude 提供可持续保存与关联检索的记忆能力。

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