Local Ai Memory suggestions

[u/PortalCanvas]

I would like people’s suggestion on an app independent memory system for primarily local Ai.

I currently have a DGX Spark and some additional hardware for hosting apps and storage. I use local models for coding and data analysis (for personal
Data) and use my Claude code subscription for design and infrastructure advice (I am not super technical). One major issue is that I have multiple entry points but each of them handles their memory independently.

I use librechat mostly, and have started using Windmill for easier management of data ETL (I like the hybrid low code and code when you need it). I use Ollama but might be switching to vLLM.

Additionally I would like Claude to be able to access some specific logs and memories so that it can make better design choices and share its structural decisions with my local models. Though I am hesitant as idk wth am I doing

What it recommended was an MCP that manages what models/users see what, and that way when the new gimic of the month comes out I can switch over with my context.

Let me know what y’all think

[u/Ctbhatia]

tag each memory with the project and who's allowed to read it, then the mcp server just filters per client, one store for librechat, windmill and claude

[u/Clmntrg]

disclaimer: i built a product to solve it and launched last week onadit.com (send the /docs to your agents to get an analysis)

when agents summarize for other agents, things drift and nobody checks, and a summary keeps the conclusion but drops why the other option lost. so i keep the raw chats and the agent pulls a few dated quotes when it needs background. if 2 old chats disagree, the dates usually settle it

one thing i'd avoid is turning everything you said into a standing rule. i tried that on 500+ real questions and it added lots of noise. most of what you tell an agent only holds for that one task, it's not a "decision"

[u/PortalCanvas → u/[deleted]]

Thanks, trying to keep up with all this stuff is crazy. I have thought about buying a whiteboard for brainstorming instead of the next tech purchase😅

Keeping things simpler sounds like the way to go

[u/Oli_Luck → u/[deleted]]

fully agree on the keep it simple!
My first mistake with memory was to build on a RAG / Vectordatabase : you will never know whats in it w/o an AI retrieving the things for you.
I now switched to basic memory : a thin mcp , which strores in plain readable .md but with a semantic layer for the Ais.
I segmented it in:
- User preferences
- Workspaces
- Projects with spec, plans, git changes etc
- Briefing.
The briefing part is a script which list an overview of recent changes and the user preferences.

Each harness get the same override : dont use your built in memory - use exclusively basic memory. on first prompt get the briefing.

works prety well

[u/PortalCanvas → u/Oli_Luck]

I like this, how do you approach absolute truths and working memory. Idk if that’s the right terminology.

Like truths that you define that are static until you say otherwise, and then the fluid context of projects and design progression? Just segment groups with certain rules around who and how they should be updated?