Adaptive Memory Graph
Gives Claude a persistent memory layer that survives across sessions using a weighted graph of knowledge nodes. Each node has a title, summary, tags, and connections to related concepts. Weights increase when nodes get accessed, decrease over time if unused, and eventually archive. The server exposes tools like amg_load_index for session startup, amg_expand_branch to pull full node content on demand, amg_get_connected_nodes for traversing relationships, and amg_log_session to record what was useful. Everything stores encrypted on disk with AES-256-GCM. Reach for this if you want Claude to remember project details, preferences, or domain knowledge between conversations without manual context pasting.
- tools
- 11
- transport
- STDIO
- last updated
- Mar 11, 2026
Tools
11 toolsPublic tool metadata for what this MCP can expose to an agent.
amg_load_indexLoad lightweight graph index at session start
Load lightweight graph index at session start
No parameter schema in public metadata yet.
amg_expand_branchFetch full node content when contextually relevant
Fetch full node content when contextually relevant
No parameter schema in public metadata yet.
amg_get_connected_nodesFind related nodes across domains
Find related nodes across domains
No parameter schema in public metadata yet.
amg_log_sessionLog session summary at conversation end
Log session summary at conversation end
No parameter schema in public metadata yet.
amg_update_graphProcess pending logs and apply weight decay
Process pending logs and apply weight decay
No parameter schema in public metadata yet.
amg_export_reportGenerate human-readable graph summary
Generate human-readable graph summary
No parameter schema in public metadata yet.
amg_manual_adjustBoost, decay, archive, or delete nodes
Boost, decay, archive, or delete nodes
No parameter schema in public metadata yet.
amg_add_nodeAdd new nodes to the graph
Add new nodes to the graph
No parameter schema in public metadata yet.
amg_search_nodesSearch nodes by title, summary, tags, or content
Search nodes by title, summary, tags, or content
No parameter schema in public metadata yet.
amg_list_chat_sessionsList available Claude Code chat sessions for review
List available Claude Code chat sessions for review
No parameter schema in public metadata yet.
amg_read_chat_sessionRead a chat session's conversation content
Read a chat session's conversation content
No parameter schema in public metadata yet.
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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
Details
- Repository
- github.com/raskolnikovdd/adaptive-memory-graph
- Categories
- AI & LLM Tools, Documents & Knowledge
- Package
adaptive-memory-graph- Transport
- STDIO
- Registry
- MCP registry, active
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