save_to_mindLABSCO SUMMARY
Memory that gets more useful the more it is used.
Storing notes is the easy half; the hard half is having the right ones come back. Here recall is shaped by usage — concepts that keep appearing together get more strongly connected, and links you never touch fade out of the way.
What it is
A knowledge-graph memory server built on Hebbian learning. Content is saved and queried, and related concepts surface on their own because edges strengthen when two concepts activate together and decay when they do not. It ships with 100+ predefined enterprise concept nodes spanning Systems, Security, Data and Operations.
What you get
- Content saved into an associative store and queried back
- Related concepts surfaced automatically, with no manual linking
- Edges that strengthen through co-activation and decay when unused
- 100+ predefined enterprise concept nodes across Systems, Security, Data and Operations
- Stdio transport, so it drops into Claude Desktop, Claude Code or any MCP client
- Install with pip on Windows, Linux or macOS
- RAM disk support on Linux through /dev/shm
Requirements
Python with pip for a native install; the server runs on stdio. Behaviour is set through environment variables. The graph lives where you run it — there is no external service behind it.
Setup effort
Install the PyPI package with pip, then start the server
USE CASES
01
Keeping what you learn across sessions
Save the finding as content and it enters the graph, rather than landing in a flat note file nothing reads later.
02
Getting back more than you asked for
A query returns the match plus the concepts that keep activating alongside it, so context arrives with the answer.
03
Letting stale connections go
Links that stop being co-activated decay, so an association formed once and never used again stops resurfacing.
8 tools
Listed in project docs. Your client may show a different list.
query_mindanalyze_contentget_related_nodeslist_nodesmind_statusfaiss_searchfaiss_statusBEFORE YOU INSTALL
What to know first
Tools you get
8 tools named in the project's documentation.
Requires
python on PATH
Where it runs
The documented client runs the server on your machine.
INSTALLATION
Connect your client
Server setup
TERMINAL
pip install hebbian-mind-enterprise
python -m hebbian_mind.serverMCP Clients
Claude Desktop — native
CLAUDE DESKTOP — NATIVE · JSON
{
"mcpServers": {
"hebbian-mind": {
"command": "python",
"args": [
"-m",
"hebbian_mind.server"
]
}
}
}
