MercurAI | Intelligence Dashboard

Your Active Services

Data Engine (Search)

Plan 1: Single Query

Sub-millisecond similarity lookups across vectorized datasets.

Service / Query *

Target City

Plan 2: VIP MCP Stream

Autonomous AI Agent vector database execution over the protocol stream.

Tool Argument (Service Query)

Max Price Cap (\$)

Plan 3: Database Engine

Download full datasets or filter segments for RAG or CRM ingestion.

City (Optional)

Area (Optional)

Service Filter (Optional)

Workspace Canvas

Zero-hallucination agent actuation and W3C draft site integration environment.

Ready

Your WebMCP Studio is Ready

Your account is activated. Use WebMCP Studio to map your frontend actions into W3C Draft-compliant JSON schemas. This enables autonomous agents (like Claude and Chrome Copilots) to execute real-time actions on your site, entirely distinct from passive AI search indexing.

Step 1

Register Hostname

Link and verify your domain in the Studio portal.

Step 2

Run 4-Layer Probe

Scan forms, APIs, and JS functions to generate native tool registries.

Open WebMCP Studio Portal Read Documentation

Initialize Semantic Indexing

Enter your target domain below. Our backend will trigger the Gemini semantic pipeline to scrape your site, clean the HTML, and output a structured `/llms.txt` and W3C JSON-LD markup.

domain.com

Last Synced: N/A

CDN:

Manual Semantic Ingestion

Force a manual semantic pipeline crawl of your target URL to instantly regenerate your llms.txt and JSON-LD schemas.

Pipeline Executing...

The Gemini AI model is currently parsing your website and generating semantic markdown and JSON-LD schema. This takes about 30-45 seconds. Please refresh this page momentarily.

/llms.txt Markdown

JSON-LD Schema

Configure your query filters on the left to inspect structured records.

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Confirm Action

Universal WebMCP Pass is Active