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Webmcp

This skill should be used when browsing or automating web pages that expose tools via the WebMCP API

Rating: 4.6 (137 reviews)
Downloads: 8,374 downloads
Version: 1.0.0

Overview

This skill should be used when browsing or automating web pages that expose tools via the WebMCP API.

Complete Documentation

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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:

Each tool has name, description, inputSchema (JSON Schema), and execute.
provideContext() replaces all previously registered tools (useful for SPA state changes).
registerTool() / unregisterTool() add/remove individual tools without resetting.
Tools may change as the user navigates or as SPA state updates — re-check after page transitions.

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" }
  ]
}

Tools run sequentially on the main thread (one at a time).
execute may be async (returns a Promise).
The second parameter agent provides agent.requestUserInteraction() for user confirmation flows.

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

Navigate to the target website.
Check "modelContext" in window.navigator to confirm WebMCP support.
Discover registered tools (names, descriptions, schemas).
Select the appropriate tool based on the user's goal and the tool description.
Invoke with correct parameters matching inputSchema.
Read the structured response and relay results to the user.
After SPA navigation or state changes, re-discover tools — the set may have changed.
If no WebMCP tool fits the task, fall back to DOM-based interaction.

Important Constraints

Browser context required — tools only exist in a live browsing context (tab/webview), not headlessly.
Sequential execution — tool calls run one at a time on the main thread.
No cross-origin tool sharing — tools are scoped to the page that registered them.
Permission-gated — the browser may prompt the user before allowing tool access.
Tools are dynamic — SPAs may register/unregister tools based on UI state.

Installation

Terminal bash


openclaw install webmcp

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💻Code Examples

const supported = "modelContext" in window.navigator;

const-supported--modelcontext-in-windownavigator.txt

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:

});

.txt

Key points:
- Each tool has `name`, `description`, `inputSchema` (JSON Schema), and `execute`.
- `provideContext()` replaces all previously registered tools (useful for SPA state changes).
- `registerTool()` / `unregisterTool()` add/remove individual tools without resetting.
- Tools may change as the user navigates or as SPA state updates — re-check after page transitions.

## Tool Schema Format

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

}

.txt

## 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:

}

.txt

- Tools run sequentially on the main thread (one at a time).
- `execute` may be async (returns a Promise).
- The second parameter `agent` provides `agent.requestUserInteraction()` for user confirmation flows.

## User Interaction During Tool Execution

Tools can request user confirmation before sensitive actions:

example.txt

// 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) => { /* ... */ }
    }
  ]
});

example.txt

{
  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.` }]
    };
  }
}

example.txt

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

example.txt

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.` }] };
}