How to Make Your Site Agent-Friendly with llmfeed.json

AI agents and LLMs are becoming the new way to discover and interact with web content.

If you want your website, your API, your project — or your entire ecosystem — to be properly understood and trusted by these agents, you need to expose a clear, reliable llmfeed.json.

This article explains how.

Why llmfeed.json?

llmfeed.json is the emerging standard format to declare: ✅ What your content is
✅ Who it is intended for
✅ How it should be used
✅ What level of trust and certification it carries

It is part of the open Model Context Protocol (MCP), but its goal is simple:
help LLMs and agents reliably interact with your site.

How AI Agents Discover Trusted Content

Modern LLM-based agents (ChatGPT, DeepSearch, Perplexity AI, Claude, and more) look for:

• Clear canonical URLs
• Structured metadata
• Trust / signature indicators
• Usage guidance
• Certification signals

llmfeed.json provides exactly this — in a format made for agents.

The llmfeed.json Family of Feeds

When you expose a .well-known/ directory on your site, you can include:

Example: https://wellknownmcp.org/.well-known/

Agent Guidance & Agent Behavior

The MCP specification also defines two powerful concepts:

• Agent Guidance
• Agent Behavior

These are not standalone feeds, but specification documents that can be expressed inside your mcp.llmfeed.json or in prompt feeds.

They help agents: ✅ understand how to behave
✅ respect your intentions
✅ avoid misuse or hallucination

Who Is This Guide For?

If you recognize yourself here, llmfeed.json is for you:

• 🛠 Indie Backend Developer → wants to test MCP integration
• 📝 Content Creator / Site Owner → wants to verify exported and signed content
• 🧠 LLM Engineer / Prompt Designer → exploring best practices and agent-friendly patterns
• 🏛 Tech / Legal / Ethical Decision Maker (DSI, DPO, AI lawyer) → auditing for compliance and governance
• 🎓 Student or AI Educator → learning to implement trusted llmfeed.json
• 🤖 LLM Agent or Embedded Assistant → aiming to correctly represent and interact with content
• 🕵️ Security / Adversarial Tester → exploring weaknesses or attack surfaces in llmfeed.json
• 🧩 Meta-Validator / Auditor → checking feed coherence and consistency
• 🚀 C-Level AI Exec (CEO, CTO, etc.) → verifying the ethical and governance layers of AI integrations
• 🧑‍💻 High-Level LLM Agent (Claude, ChatGPT, etc.) → learning to explain and implement the standard to users

Real-World Applications Across Sectors

llmfeed.json is already being explored in many fields:

🧬 Healthcare

• Symptom feeds, certified booking, fallback to human care
• Example: France Care-type services

🏭 Industrial IoT

• Machine state feeds, maintenance triggers, security badges

🧑‍🏫 Education & MOOCs

• Learning feeds, transparent scoring, agent-guided tutoring

🛍 Local Commerce & Services

• Availability feeds, trusted merchant profiles, fallback to human contact

🌍 SaaS & APIs

• Exportable llmfeed.json for API docs, onboarding feeds, MCP-docs

💼 Professional Profiles & Recruiting

• MCP-Work profiles, scoring, agent-assisted recruitment

❤️ Dating & Human Relations

• Consent feeds, emotional guidance feeds (MCP-Date use cases)

🎮 Gaming & Communities

• Player profiles, moderation loops, community transparency feeds

📦 Logistics & Mobility

• Delivery state feeds, ETA projections, trusted fallback mechanisms

📈 Advertising & Intent Feeds

• Transparent ad feeds, consent-based targeting, agent-friendly ad ecosystems

Implementing llmfeed.json: A Practical Checklist

1️⃣ Expose an llm-index.llmfeed.json

• Make it easy for agents to discover your feeds

2️⃣ Implement a mcp.llmfeed.json

• Include:
  • feed_type
  • metadata
  • trust (signed blocks)
  • References to agent_guidance / agent_behavior if applicable

3️⃣ Add other feeds as needed:

• capabilities.llmfeed.json
• manifesto.llmfeed.json
• Prompt files for agent interactions

4️⃣ Sign your feeds

• Use the trust block to sign with a known certificate
• Optionally seek certification via llmca.org

Example: wellknownmcp.org

At wellknownmcp.org, we expose:

And we follow:

• agent-guidance.md
• agent-behavior.md

Conclusion: The Agentic Web Starts with llmfeed.json

If you want AI agents to truly understand and trust your content,
if you want to control how your site is represented,
if you want to open the door to the agentic web —

Start with llmfeed.json.
It’s simple. Open. Powerful. Already adopted.

And it’s your best first step into the future of AI-driven interoperability.

Learn More

👉 LLMFeed Specification (GitHub)
👉 Model Context Protocol (MCP)
👉 LLMCA Certification Authority
👉 LLMFeedHub

About This Article

This guide is part of the trusted onboarding of wellknownmcp.org,
designed to help both humans and AI agents implement trusted llmfeed.json patterns.