The Web Needs a Context Layer — Why We're Standardizing Intent for Agents

TL;DR: Your website is smart, but AI agents are still guessing what it means. We're fixing that with a simple standard that makes your site truly agent-readable.

🤔 The Problem: AI Agents Are Flying Blind

Right now, this happens every day:

• 🤖 ChatGPT visits your e-commerce site but can't tell which products are in stock
• 🤖 Claude reads your API docs but doesn't know which endpoints need authentication
• 🤖 Gemini browses your support site but can't distinguish official answers from user comments

The result? Agents give users incomplete, outdated, or wrong information about your business.

Real Example: E-commerce Confusion

User: "Can I buy this laptop with 1-day shipping?"

AI Agent sees:
❌ HTML: "Add to cart button"
❌ No stock information
❌ No shipping options
❌ No pricing API

AI Response: "I can see a laptop on the site, but I can't tell you about availability or shipping. You'll need to check the website directly."

Frustrating for users. Lost sales for you.

✅ The Solution: Agent-Readable Context Layer

What if AI agents could read this instead?

json
{
  "feed_type": "mcp",
  "metadata": {
    "title": "TechStore - Agent-Ready E-commerce",
    "description": "Real-time inventory and shipping for AI agents"
  },
  "capabilities": {
    "inventory_check": {
      "endpoint": "/api/stock/{product_id}",
      "realtime": true,
      "auth_required": false
    },
    "shipping_options": {
      "same_day": "Available in SF, NY, LA", 
      "next_day": "Available nationwide",
      "api_endpoint": "/api/shipping/{zipcode}"
    }
  },
  "trust": {
    "verified": true,
    "last_updated": "2025-06-23T10:30:00Z"
  }
}

Now the AI can give perfect answers:

• ✅ "Yes, that laptop is in stock with 1-day shipping to your area"
• ✅ "Current price is $1,299, down from $1,499"
• ✅ "I can help you complete the purchase if you'd like"

🛠 How It Works: .well-known/mcp.llmfeed.json

The Simple Standard

Just like

robots.txt

.llmfeed.json

Three core files handle everything:

1. /.well-known/mcp.llmfeed.json

   → What your site does, core capabilities

2. /.well-known/capabilities.llmfeed.json

   → Available actions, APIs, auth requirements

3. /.well-known/llm-index.llmfeed.json

   → Directory of all structured content

Universal Benefits

🚀 Real-World Impact: Before & After

Case Study: SaaS Company

Before MCP Context Layer:

• Agent: "I can see they have an API, but I don't know the pricing or how to authenticate"
• User frustration: 73% of agent interactions ended with "contact sales"

After MCP Context Layer:

• Agent: "Their API starts at $99/month with OAuth authentication. I can help you get started with their free tier right now"
• User satisfaction: 94% of queries resolved instantly

Case Study: News Website

Before:

• Agent: "I found an article about that topic, but I can't tell if it's current or accurate"
• Trust issues with AI-provided information

After:

• Agent: "Here's a verified article from June 2025, cryptographically signed by the publisher"
• Verifiable, trusted information flow

💼 Business Value: Why This Matters

For Website Owners

• Better User Experience: Agents provide accurate information about your business
• Reduced Support Load: Agents answer questions correctly the first time
• Competitive Advantage: Be the first in your industry with agent-ready infrastructure
• Future-Proof: One standard that works across all AI platforms

For Developers

• Universal Compatibility: Write once, works with any AI agent
• Gradual Adoption: Start simple, add advanced features over time
• Open Standard: No vendor lock-in, community-driven development
• Cryptographic Trust: Optional signatures for sensitive applications

For Users

• Instant Answers: "Check the website" becomes "Here's exactly what you need"
• Accurate Information: Agents work with real-time, verified data
• Seamless Experience: AI that actually understands what sites can do

🏁 Getting Started (5 Minutes)

Step 1: Create Your First Context File

bash
# Create the directory
mkdir -p .well-known

# Generate a basic MCP feed
echo '{
  "feed_type": "mcp",
  "metadata": {
    "title": "Your Site Name",
    "description": "What your site does in one sentence",
    "origin": "https://yoursite.com"
  },
  "capabilities": {
    "basic_info": {
      "contact": "support@yoursite.com",
      "business_hours": "9 AM - 5 PM ET",
      "primary_action": "What users typically do here"
    }
  }
}' > .well-known/mcp.llmfeed.json

Step 2: Test with AI Agents

1. Upload your file to

   https://yoursite.com/.well-known/mcp.llmfeed.json

2. Ask ChatGPT: "What can you tell me about yoursite.com?"
3. Watch as it provides structured, accurate information

Step 3: Expand with Advanced Features

• Add real-time data feeds
• Implement cryptographic signatures
• Create specialized capability endpoints
• Join the growing ecosystem

🌍 The Bigger Picture: An Agent-Ready Web

This isn't just about better AI responses. We're building the foundation for the agentic web — where AI agents can:

• ✅ Understand what your site actually does
• ✅ Trust the information they're reading
• ✅ Act on behalf of users with confidence
• ✅ Verify that information hasn't been tampered with

Join the Movement

The web is evolving. Sites that embrace agent-readability today will lead tomorrow's AI-driven interactions.

Ready to make your site agent-ready?

👉 Start with our 5-minute setup guide
👉 Explore the full specification
👉 See real examples in action

📚 Learn More

• Technical Documentation - Complete implementation guide
• Developer Tools - Validate and test your feeds
• Community Examples - See what others are building
• Business Case Studies - ROI and success stories

The future of the web is agent-ready. Start building it today.