Direct Answer (Experimental Field Note): In Q1 2026, InfinitusNow deployed an experimental WebMCP implementation (exposing /.well-known/mcp.json and lightweight JSON tool endpoints) alongside /llms.txt on our production domain. What Worked: MCP-compatible autonomous AI agents retrieved structured service catalogs and contact endpoints in under 120ms with 100% attribute extraction accuracy and zero HTML scraping overhead. What Didn't: Mainstream consumer search crawlers currently ignore WebMCP files, and consumer AI interfaces do not query web MCP endpoints during casual conversational sessions without active agent tooling. Conclusion: WebMCP is a high-potential emerging standard for autonomous agentic commerce, but should be deployed as a forward-looking infrastructure layer on top of—never instead of—standard SEO and JSON-LD schema.
The Technical Architecture on infinitusnow.com
- Discovery Manifest:
/.well-known/mcp.jsondefining available tool methods (get_services,get_contact_info). - JSON Endpoints: Lightweight API routes returning clean, deterministic JSON without styling or scripts.
- Cross-Referencing: Linking the discovery endpoint directly within our
/llms.txtfile.
Empirical Observations
| Metric | Standard HTML Page Scrape | WebMCP Endpoint Query | Improvement |
|---|---|---|---|
| Payload Size | ~45 KB | ~1.2 KB | 97.3% reduction |
| Token Consumption | ~12,000 tokens | ~280 tokens | 97.6% savings |
| Agent Retrieval Latency | 850ms – 1,400ms | 110ms – 140ms | 88% faster |
| Attribute Accuracy | 88% (parsing noise) | 100% (deterministic) | Zero hallucination |