Articles
Notes on memory, evaluation and local-first design, written as we build rather than after. Short, and dated so you can tell what's changed since.
Claude Code memory vs. an MCP memory layer: what actually changes
CLAUDE.md is scoped to one project. An MCP memory layer is a file you own that any assistant can read across projects.
Most MCP memory servers store text. Few tag where it came from.
Six real MCP memory servers, compared on storage, provenance tagging, and whether an account is required.
Local-first software examples: where memory fits the pattern
Eight real local-first examples, Obsidian to Huly, and where an AI assistant's memory usually falls outside the pattern.
ModelBrain's MCP server tools: the full list of five calls
remember, recall, forget, expand, connector_sync: the entire tool surface, on purpose.
How ModelBrain tags what it remembers
Source evidence, stated assertion, or model-generated summary, kept distinct instead of one opaque blob.
Why managed backup is included, not billed separately
It comes with device sync; the only thing metered is the space it uses, at the same $0.05/GB as everything else we store.
What Per-Node Pricing Means, and Why We Don't Count People
The free tier has no login for a seat count to attach to, so we bill machines, not people.
What a Forget Call Actually Has to Guarantee
Undo versus deletion, and why we test them as separate cases.
Designing the recall test before writing the product
Why the evaluation came before most of the features it measures.
What Local-First Software Actually Rules Out
Where the line is between local-first and merely local-by-default.
Why we didn't build vault encryption first
The tradeoff behind the decision, and what protects the local tier instead.
Five questions to ask any AI memory tool before you trust it with your work
A checklist for evaluating recall claims, including ours, before you rely on one.