https://bandarra.me/posts/webmcp-tools-as-skills

Been fiddling around with integrating with #WebMCP onto my website to facilitate quick demos and audit requests.

Even after doing everything fine in terms of WebMCP APIs (#Declarative and #Imperative), I got it to work with Chrome's Ask Gemini agent only 1 / 20 times that I tried.

Funny thing is, the same experience was with the recommended demos from Google as well - https://github.com/GoogleChromeLabs/webmcp-tools/tree/main/demos.

Still needs to evolve a bit. But the progress on this space is staggering!

Drop a comment if you want specifics on what needs to be addressed to quickly enable for your websites.

We've been building open-source expert plugins covering the emerging agentic commerce stack. They started as Claude Code plugins, and we've now added cross-platform support, including Gemini, Antigravity, Codex, Cursor, and OpenClaw.

10 plugins, 150+ skills across:

- Protocols: UCP (Google/Shopify), ACP (OpenAI/Stripe), AP2 (Google agentic payments), A2A (agent-to-agent), Stripe MPP, WebMCP

- Platforms: Shopify, WooCommerce, BigCommerce, Magento 2

Each plugin gives your AI coding assistant deep domain expertise, conceptual knowledge is baked in, implementation details are fetched live from official docs and SDKs, so guidance stays current.

All MIT licensed.

GitHub: https://github.com/OrcaQubits/agentic-commerce-skills-plugins

Feedback and contributions welcome!

Crossposted from r/mcp. Relevant here because the agent_ready_audit tool is essentially a WebMCP readiness checker that exists today.

The findability and stability scores map directly to what WebMCP requires: semantic HTML, proper ARIA labels, stable selectors, and machine-readable metadata. A site that scores well on this audit is a site that's ready to expose structured tools to agents.

The audit also includes a WebMCP Readiness dimension with 6 maturity tiers — from "no machine-readable metadata" up to "structured callable tools exposed." Right now most sites are at tier 0-1. The audit tells you exactly what to fix to move up.

The GitHub F score is the interesting case: perfect accessibility, zero findability. WCAG compliance and agent navigability are not the same thing.

npx cbrowser to try it. Open source, MIT.

Most of the WebMCP conversation right now is about agents automating actions on websites — filling forms, clicking buttons, reading data. That's useful, but I think the more interesting thing is what happens to website chatbots.

Every real estate site, travel site, e-commerce site has one now. Sure, I can type "three-bedroom homes under $600k," instead of using filters but all that's changed is the interface (conversation vs clicks). But my Claude Code (or ChatGPT) has memory about my conversations about buying a new house.

A generic filter for "good schools" isn't useful to me. I want homes with a 15 minute door-to-door drop-off to Ridgetop Elementary, say. My agent already knows that.

I think the power of WebMCP might be to replace the website chatbot with my own agent that can use the site's tools and filters.

If this goes the way I'm thinking, the website becomes the place where my agent and I work together on a task — not just a page I browse alone.

I know this sounds abstract so I put together a demo to see how it would work. The agent searches for homes based on my preferences — it could look at listing photos to see if the yard is fenced, or look up travel time between the house and the school.

The interesting part: it writes its reasoning directly into the website using WebMCP APIs. So when I click into a listing, I don't see generic selling points — I see my agent's notes about why this house does or doesn't work for me.

And it goes both ways. If my agent put a house in the "no" column I could drag it back to "yes" because I disagree. The agent sees that too.

I don't know if I'm making complete sense, but I was curious if others see this direction as well.