# move to germany, lol — the arrival planner for you + your AI agent

Because the paperwork is enough drama. Human and AI agent build the everyday
essentials for a new German address together: the agent searches 80+ business
categories in parallel, the human curates the shared shortlist and writes notes,
the agent reads them back and refines the plan.

## WebMCP tools on this page
list_categories, set_home_plz, find_nearby, generate_starter_plan,
add_to_shortlist, remove_from_shortlist, get_shortlist, set_note, export_plan —
registered via document.modelContext, typed JSON schemas, readOnlyHint where honest.

## HTTP API
- GET /api/categories — all categories of the network
- GET /api/search?cat=<slug>&plz=<plz>&limit=5 — one category, distance-sorted
- GET /api/essentials?plz=<plz>&cats=a,b,c — many categories in parallel

Categories include: Elektriker, Immobilienmakler, Autoglas, Autowerkstatt, Autohaus, Möbelhaus, Bäcker, Supermarkt, Friseur, Tankstelle, Bank, Hotel, Kino, Krankenhaus, Baumarkt … (81 categories total)

Data: the 'in meiner Naehe' network — 80+ agent-readable German directories
(OpenStreetMap ODbL 1.0, Overture Maps CDLA-Permissive-2.0). Open source (MIT):
https://github.com/shufflethis/neu-hier