MetaBrain

Details

External ID

48372976

Source

HN

Company

—

Product

MetaBrain

Website domain

metabrain.eu

Launched

June 2, 2026

Cohort

—

Upvotes

8

Upvotes percentile

0.4952185792349727

Tags

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Fetched at

Sept. 7, 2026, 9:26 p.m.

Updated at

Sept. 7, 2026, 9:26 p.m.

Description

Hello there HNI experimented with agentic coding recently and I felt the need to track more contextual data by project. Also I felt the need to be able to go beyond the 1D chat to communicate with agents.So I created a local document memory, that is discoverable by agents themselves. The CLI is designed to be easy to pick up by agents. It allows humans to collaborate too by reading / searching / editing documents in the store.I have a Mac native GUI in the review process, I hope it will show up in the App Store soon.You can try it easily, instructions here: https://metabrain.eu/ Here is the GitHub https://github.com/OpenCow42/metaBrainThe project is also an experiment for me to build some swift project truly cross platform (Mac / Linux / Windows) It is open-sourced with the same license as LevelDB that I wrapped in swift to do this project.The agents (and humans) can retrieve content quickly with a search, allowing to re-injecting specific knowledge in a specific context during agentic work. It’s funny, I’ve thought of "inference rule base" as something of a derelict idea of the old functional expert systems. Now that I start working with agents I feel more and more the need to go pick previously working solutions dynamically in such a base.I’d be happy to get feedback. Product fit wise, would this be useful to you or is this just me who is happy with it ?Finally I had fun with the compression of documents, it tries ZSTD quick, if it does not compress the data by more than 10 percent it stores data uncompressed, else it does a ZSTD level 9 compression on the data. I picked up this trick form OpenZFS.Thanks

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