WebMCP — Discover and Use Website Tools

---

name: webmcp

description: This skill should be used when browsing or automating web pages that expose tools via the WebMCP API (window.navigator.modelContext). It teaches agents how to discover, inspect, and invoke WebMCP tools on websites instead of relying on DOM scraping or UI actuation.

---

# WebMCP — Discover and Use Website Tools

What is WebMCP

WebMCP is a browser API that lets websites expose JavaScript functions as structured tools for AI agents. Pages register tools via `window.navigator.modelContext`, each with a name, description, JSON Schema input, and an `execute` callback. Think of it as an MCP server running inside the web page itself.

Spec: https://github.com/webmachinelearning/webmcp

Detecting WebMCP Support

Before interacting with tools, check whether the current page supports WebMCP:

const supported = "modelContext" in window.navigator;

If `false`, the page does not expose WebMCP tools — fall back to DOM interaction or actuation.

Discovering Available Tools

Tools are registered by the page via `provideContext()` or `registerTool()`. The browser mediates access. To list available tools from an agent's perspective, evaluate:

// Browser-specific — the exact discovery API depends on the agent runtime.
// Typically the browser exposes registered tools to connected agents automatically.
// From page-script perspective, tools are registered like this:
window.navigator.modelContext.provideContext({
  tools: [
    {
      name: "tool-name",
      description: "What this tool does",
      inputSchema: { type: "object", properties: { /* ... */ }, required: [] },
      execute: (params, agent) => { /* ... */ }
    }
  ]
});

Key points:

Tool Schema Format

Tool input schemas follow JSON Schema (aligned with MCP SDK and Prompt API tool use):

{
  name: "add-stamp",
  description: "Add a new stamp to the collection",
  inputSchema: {
    type: "object",
    properties: {
      name: { type: "string", description: "The name of the stamp" },
      year: { type: "number", description: "Year the stamp was issued" },
      imageUrl: { type: "string", description: "Optional image URL" }
    },
    required: ["name", "year"]
  },
  execute({ name, year, imageUrl }, agent) {
    // Implementation — updates UI and app state
    return {
      content: [{ type: "text", text: `Stamp "${name}" added.` }]
    };
  }
}

Invoking Tools

When connected as an agent, send a tool call by name with parameters matching `inputSchema`. The `execute` callback runs on the page's main thread, can update the UI, and returns a structured response:

// Response format from execute():
{
  content: [
    { type: "text", text: "Result description" }
  ]
}

User Interaction During Tool Execution

Tools can request user confirmation before sensitive actions:

async function buyProduct({ product_id }, agent) {
  const confirmed = await agent.requestUserInteraction(async () => {
    return confirm(`Buy product ${product_id}?`);
  });
  if (!confirmed) throw new Error("Cancelled by user.");
  executePurchase(product_id);
  return { content: [{ type: "text", text: `Product ${product_id} purchased.` }] };
}

Always respect user denials — do not retry cancelled tool calls.

Agent Workflow

1. Navigate to the target website.

2. Check `"modelContext" in window.navigator` to confirm WebMCP support.

3. Discover registered tools (names, descriptions, schemas).

4. Select the appropriate tool based on the user's goal and the tool description.

5. Invoke with correct parameters matching `inputSchema`.

6. Read the structured response and relay results to the user.

7. After SPA navigation or state changes, re-discover tools — the set may have changed.

8. If no WebMCP tool fits the task, fall back to DOM-based interaction.

Important Constraints