Rule of thumb · Pick Mem for solo personal notes with AI assist and great mobile capture. Pick Bcontext for project context shared with agents in the 1–15 seat band.
Markdown export at any time. Re-imports are idempotent — running the migration again updates in-place instead of duplicating.
Most tools support a markdown or JSON export. Drop the folder into the bcontext importer — sub-folders become folder nodes, pages become docs.
Run the auto-typer to suggest kinds — tasks, decisions, runbooks, meetings — based on title patterns and frontmatter. Review the diffs as proposals.
Side-by-side view of original + bcontext-typed nodes. Accept what's right, reject what's noise. The whole thing exports back to clean markdown anytime.
The fundamental shape difference: Mem treats every note as a free-form blob with rich metadata extracted by AI. That's great when the texture of the content is unstructured personal capture. It struggles when the texture is structured operational knowledge — ADRs, tasks, decisions — that benefits from typed metadata at write time, not extracted post hoc.
Bcontext's typed-node approach has compounding payoffs. Searches can filter by kind in milliseconds. The reranker can weight by recency on tasks and by importance on ADRs. Skill nodes can carry an input schema and an output shape, making `run_skill` a real RPC rather than a prompt-stuffing trick. None of this is impossible to bolt onto a free-form notes app — but the bolt-on quality is exactly the friction AI-first teams want to avoid.
The other axis is agent writes. Mem has an AI that writes inside Mem. Bcontext has an HTTP endpoint your agents — any agent, anywhere — can write through, with idempotency, with rate limits, with an audit trail. That's the difference between an AI feature and an agent surface.
The importer runs both ways. Keep your existing tool live, add bcontext as the agent surface, decide later.