Errand Crew - an observable six agentic AI workflow

Alexa+ MCP server that sends parallel browser agents across online shops, compares options, and speaks the answer back.

The MCP server uses a six agentic AI workflow

• A planner (Claude Sonnet 5.5) turns the spoken request into a plan.
• Four worker agents (Claude Haiku 5.5) browse Evomag, Altex, MediaGalaxy and Vexio in parallel, each in its own cloud browser.
• The judge picks the cheapest match in code. A model (Claude Haiku 5.5) only words the result for speech, so the spoken answer never depends on a model behaving.

You can watch the agents work. The browsers run on the https://www.kernel.sh cloud browser infrastructure, as shown in the demo video below. If you run the server yourself with your own Kernel key and KERNEL_HEADLESS=false, you can see the four browsers live in the Kernel dashboard.

The agents can only visit shops from a fixed allowlist, and everything they read on a page is treated as data, never as instructions.

How it works

Comparing prices means opening shop after shop and scrolling. Errand Crew does that part for you, while you just ask a question out loud.

Say you want a cheap phone. You ask your voice assistant, and from there it takes about half a minute! Isn't it great?

Built With

• agents
• ai
• claude
• kernel.sh
• python
• render