I've been building https://routing24.com for a while, a free route optimization and planning app for businesses.
One of the things that bothered me for quite a time is inability of browser agents to work with Routing24.
We have tons of natural tasks for AI:
- data ingestion, to figure out data coming from user's side (csv and Excel);
- geocoding quality validation (to explain user what they need to correct and their addresses and how);
- steep learning curve for business users (who have sense of what they want from route optimization, but setting up the model takes significant time and effort);
- explainability of route optimization decisions (which constraints conflict with each other, why orders are sequenced in a certain way, etc)
- ...
These and many others are very natural tasks for agentic AI in general as well as for desktop business AI assistants (Claude Cowork in particular).
We came up to the realisation when were doing frontend testing from prompts, that used Chrome CDP, where AI instruments and controls the browser.
Our build of Routing24 for integration testing has its state and action model fully exposed to AI tests via `window`, and driving complex test cases from prompts was nice and easy.
Surprisingly, similar reduced state object exposed via `window` to Claude Cowork equipped with `javascript_tool` and browser extension made it possible to drive import, geocoding, optimization and explanation from agent like a charm, the whole app became one large tool+state.
Further it turned our this approach is getting standartized as W3C WebMCP (already in preview in Chrome).
Long story short: Routing24.com free route optimization now works in Claude Cowork and and future WebMCP agent!