Welcome to MercurAI Workspace
Leverage our dual-engine architecture: The Data Engine for grounded semantic search, and the WebMCP Studio for autonomous agent actuation.
WebMCP Studio (Actuation)
Transform your frontend into a W3C-compliant agent execution layer, enabling Chrome Copilots to submit forms and trigger actions.
Data Engine (AI Search)
Feed global AI Search platforms and RAG pipelines with clean, vectorized semantic data via pgvector.
Authentication & Protocol Access
Your access is governed strictly by the x-api-key header linked to your active subscription tier.
API Gateway
Route all standard HTTP requests through the Uvicorn-powered tollbooth. Standard REST endpoints are available here.
FastMCP Stream (SSE)
Establish persistent connections for autonomous agents via Server-Sent Events (SSE) to bypass traditional REST limitations.
curl -N -H "x-api-key: YOUR_KEY" \
https://mercurai.online/v1/sse
WebMCP Studio (Agent Actuation)
Aligned with the W3C Web Machine Learning Community Group draft specification, this protocol enables autonomous agents to safely trigger deterministic functions on your site (bypassing brittle visual DOM scraping). This is explicitly for Agent Actuation, not passive AI Search indexing.
Domain Registration
Register your target URL in the WebMCP Portal and verify ownership.
Environment Profiling
The mercurai-scout.js script evaluates site complexity, detecting frameworks (React/Vue) and Shadow DOMs to determine agent execution readiness.
W3C Draft Schema Generation
Use the mercurai-discovery.js probe in your console to scan forms and output JSON Schema (Draft-07) compliant definitions required for W3C tool registration.
Browser Native Registration
The runtime bridge utilizes the proposed document.modelContext.registerTool() API to expose capabilities natively, triggering built-in browser permission dialogs for maximum security. A polyfill is provided for legacy clients.
Framework Integration
Select your frontend architecture below for practical, detailed instructions on embedding the WebMCP execution scripts seamlessly.
Vanilla HTML Installation
Paste the WebMCP script inside your <head> tag. Ensure it uses the defer attribute.
<!DOCTYPE html>
<html lang="en">
<head>
<meta charset="UTF-8">
<title>My Website</title>
<!-- WebMCP Execution Bridge -->
<script src="https://mercurai.online/mercurai-webmcp.js" data-domain="yourdomain.com" defer></script>
</head>
<body>
...
</body>
</html>
React (Vite / CRA)
You can add the script directly to your index.html, or load it dynamically in your root App.jsx using a useEffect hook.
import { useEffect } from 'react';
function App() {
useEffect(() => {
const script = document.createElement('script');
script.src = "https://mercurai.online/mercurai-webmcp.js";
script.setAttribute("data-domain", "yourdomain.com");
script.async = true;
document.head.appendChild(script);
return () => {
document.head.removeChild(script);
}
}, []);
return <div>My React App</div>;
}
export default App;
Next.js Integration
Use the native next/script component in your root layout (App Router) or _app.js (Pages Router) for optimal loading.
// app/layout.tsx (App Router)
import Script from 'next/script'
export default function RootLayout({ children }) {
return (
<html lang="en">
<body>
{children}
<Script
src="https://mercurai.online/mercurai-webmcp.js"
data-domain="yourdomain.com"
strategy="lazyOnload"
/>
</body>
</html>
)
}
Vue 3 & Nuxt
For Nuxt, configure it in your nuxt.config.ts. For standard Vue 3, inject it in the root component lifecycle.
// nuxt.config.ts
export default defineNuxtConfig({
app: {
head: {
script: [
{
src: 'https://mercurai.online/mercurai-webmcp.js',
defer: true,
'data-domain': 'yourdomain.com'
}
]
}
}
})
Angular
Append the script path directly into your angular.json scripts array, or inject it in index.html.
// angular.json
"architect": {
"build": {
"options": {
"scripts": [
"https://mercurai.online/mercurai-webmcp.js"
]
}
}
}
Data Engine & Vector Retrieval (AI Search)
This is the indexing and discovery layer. Access raw, structured market intelligence driven by FastEmbed (BAAI/bge-small-en-v1.5) and pgvector for AI Search engines and RAG pipelines.
Semantic Lookup
Execute sub-millisecond similarity queries directly via the /v1/dataset/export endpoint.
Bulk Export
Filter datasets by industry niche, city, or service, and export up to 5,000 records per request as JSON or CSV.
Market Ingestion
The ingestion engine cleans HTML/PDFs, generates fresh embeddings, and inserts them into pgvector.
AI Agent Configuration
Connect external AI models to your authenticated tools to execute live semantic searches and actuation protocols. Note: Native WebMCP agents (like Chrome 149+) discover tools automatically without this config file.
Claude Desktop Integration (Fallback Mode)
For external automation harnesses relying on the traditional MCP protocol rather than the W3C WebMCP bridge, add the SSE URL and your x-api-key header to your claude_desktop_config.json.
{
"mcpServers": {
"mercurai-workspace": {
"command": "curl",
"args": [
"-N",
"-H",
"x-api-key: YOUR_API_KEY",
"https://mercurai.online/v1/sse"
]
}
}
Universal Pipeline Test
Run the CLI script to verify your agent handshake and test tool execution against the database.