Why llmfeed.json is the Right Level for Multi-Agent AI
An update from the LLMFeed ecosystem
π 5 Advanced Use Cases for MCP / llmfeed.json
Why agents need a signed, interoperable, behavior-aware feed standard
β multi agent, multi maturity ready
1οΈβ£ Smart Navigation
Why JSON / llmfeed.json?
- HTML is ambiguous for LLM parsing β fragile DOM
- RSS is limited to news flow β no site capabilities
- schema.org is partial and often outdated
llmfeed.json provides:
β
a machine-readable site capabilities block
β
an intent router to guide agent requests
β
a universal
.well-known
Relevant feed_type
: mcp
feed_type
mcp
Benefits of signing / certifying:
- Agents can verify authenticity of the feed β trust the capabilities
- Prevent spoofing (fake feed hosted on compromised domains)
- Feed signed = can be cached and reused by agents safely
Agent Behavior:
- Should respect declared
intent_router
- Should respect disclaimers on capabilities
trust
Agent Guidance:
json{ "preferred_interaction": "capabilities-guided-navigation", "fallback_behavior": "no invasive crawling" }
Why this works for multiple agent types
-
Claude / ChatGPT / Gemini β native
discovery.well-known/mcp.llmfeed.json
-
Custom LLaMA agent β uses
for structured feed discoveryllm-index
-
Classical crawler β can parse
or.well-known/index.html
to optimize paths.llm-index.llmfeed.json
-
IoT device β can use MCP to know which paths are relevant
-
Human β MCP index is human-readable
2οΈβ£ Automatic Documentation Summarization
Why JSON / llmfeed.json?
-
HTML docs are unstructured
-
schema.org doesnβt expose documentation hierarchy
-
llmfeed.json allows explicit data block declarations:
json
CopierModifier
{ "feed_type": "export", "data": { "files": [ "README.md", "API.md", "CONTRIBUTING.md" ] } }
Relevant feed_type
: export
feed_type
export
Benefits of signing / certifying:
-
Avoid hallucinating content not part of the export
-
Traceability β agent can reference "source: signed export feed XYZ"
Agent Behavior:
- Should respect β e.g. "summarize only", "do not redistribute"
trust.usage_policies
Agent Guidance:
json
CopierModifier
{ "preferred_interaction": "targeted summarization", "respect_trust_blocks": true }
Why this works for multiple agent types
-
Claude / ChatGPT β fetches
β uses signed content for summarization.spec.llmfeed.json
-
Gemini β same, can propose verified summaries
-
Custom LLaMA β only ingests declared
data.files
-
IoT device β can fetch minimal
feed with only what it can processexport
-
Human β can verify which documents are included
3οΈβ£ FAQ Generation / AI Support
Why JSON / llmfeed.json?
-
FAQ generation requires intent and semantic grouping
-
RSS / HTML β no clear signals
-
llmfeed.json can explicitly expose FAQ-ready blocks:
json
CopierModifier
{ "feed_type": "export", "intent": ["faq_generation"], "data": { ... } }
Relevant feed_type
: export
+ intent: faq_generation
feed_type
export
intent: faq_generation
Benefits of signing / certifying:
-
Agent can provide a signed provenance for generated answers
-
Enterprise compliance: auditability of AI-generated support
Agent Behavior:
-
Should use only signed FAQ feeds if available
-
Should respect intent scope (FAQ only, no open Q&A beyond scope)
Agent Guidance:
json
CopierModifier
{ "preferred_interaction": "faq_generation", "fallback_behavior": "none if no signed feed" }
Why this works for multiple agent types
-
ChatGPT Plugins / Claude β uses
to scope summarizationintent: faq_generation
-
Custom LLaMA β fetches FAQ feed regularly
-
IoT bot β uses it to generate spoken answers
-
Crawler β can index signed FAQ blocks
-
Human β can verify source of FAQ answers
4οΈβ£ Trusted Source Selection
Why JSON / llmfeed.json?
-
Agents need to rank and filter sources
-
RSS / HTML lacks signed provenance
-
llmfeed.json allows:
β
signature
β
trust
β
certifications
β enabling a source reputation layer.
Relevant feed_type
: any β trust
applies to all feed_types.
feed_type
trust
Benefits of signing / certifying:
-
Agents can filter for "gold certified feeds"
-
Prevent malicious source injection
-
Transparency for the end user ("this info comes from feed X certified by Y")
Agent Behavior:
-
Should privilege certified sources
-
Should expose feed provenance to user / supervisor agent
Agent Guidance:
json
CopierModifier
{ "preferred_interaction": "trust-ranked content selection", "required_certifications": ["llmca.org/gold"] }
Why this works for multiple agent types
-
Claude / ChatGPT / Gemini β uses
andtrust
blocks to rank sourcescertifications
-
Custom LLaMA β can hard-require signed feeds
-
Crawler β can record feed provenance in its knowledge graph
-
IoT device β uses trust level to decide which data to ingest
-
Human β can manually check signature and issuer
5οΈβ£ Cross-Site Agent Exploration
Why JSON / llmfeed.json?
-
Only MCP provides intentional cross-site agent navigation
-
RSS / schema.org β no cross-domain coherence
-
llmfeed.json allows:
β shared
intent_router
β shared
agent_behavior
β clear multi-feed relationships via
llm-index.llmfeed.json
Relevant feed_type
: mcp
+ llm-index
+ linked export
or capabilities
.
feed_type
mcp
llm-index
export
capabilities
Benefits of signing / certifying:
-
Agents can validate cross-site handoffs
-
Prevent fake inter-site relationships
-
Maintain agent context across domains
Agent Behavior:
-
Should track provenance across site hops
-
Should comply with each domainβs declared
agent_behavior
Agent Guidance:
json
CopierModifier
{ "preferred_interaction": "context-aware cross-site exploration", "provenance_tracking": true, "fallback_behavior": "stop on untrusted domains" }
Why this works for multiple agent types
-
Claude / Gemini / Meta AI β uses
to safely follow cross-site linksintent_router
-
Custom LLaMA β maintains cross-domain context via signed feed trails
-
IoT mesh β uses MCP to orchestrate service-to-service navigation
-
Crawler β can document MCP-declared relationships between domains
-
Human β can review intent_router in MCP feed β understand agent hops
π Final Conclusion: A Meta-Protocol for Agents
β llmfeed.json + MCP:
β
Provides unified discovery
β
Provides signed content structure
β
Provides intent and behavior guidance
β
Serves:
Type | Examples |
---|---|
Major LLM | Claude, ChatGPT, Gemini |
Custom LLM | LLaMA fine-tuned |
IoT Agents | Embedded service bots |
Crawlers | SEO bots, knowledge graph indexers |
Humans | Transparent, signed, verifiable feeds |
π Itβs Not the Battle of the Most Powerful AI That Matters β Itβs the Usages Enabled Today
Every day, headlines scream about which Large Language Model is now the most powerful:
"1000B parameters!" β "1.5M context window!" β "Smarter than GPT-4o!"
But this race is a distraction.
What matters is not the raw power of the models β itβs what they can actually do for users, today.
And for this, there is a critical missing piece: standardized, trusted, interoperable data feeds.
The Real Battle: Usability, Trust, Interoperability
Without trustable feeds, even the most powerful AI is flying blind.
-
It scrapes ambiguous web content.
-
It hallucinates relationships.
-
It cannot verify its sources.
-
It cannot act safely in agent mode.
Meanwhile, even a "small" LLaMA fine-tuned agent,
if it consumes signed, certified, behavior-guided llmfeed.json,
can outperform a giant model in reliability, explainability, and safe automation.
The Web Is Becoming an Agent Space β But It Needs Protocols
We are entering the age of:
β
AI crawlers
β
Autonomous agents
β
AI-driven applications
β
IoT interacting with cloud models
β
Search becoming agentic
But the web is still served as⦠HTML spaghetti.
It is not ready.
MCP and llmfeed.json bring:
β
explicit feed types
β
signature / provenance
β
agent behavior
β
cross-site navigation guidance
β
human-readable AND agent-consumable feeds
Itβs a Race to Useful, Trusted Interactions β Not Raw Power
A world where:
-
Developers can easily declare trustworthy feeds
-
Sites can express what they want agents to do
-
Agents can select reliable sources and respect behaviors
-
Users can know why an answer was given, and from where
β THIS is the world that scales.
Thatβs Why MCP Is Needed Now β Not in 5 Years
We should not wait for an "AGI future".
Agents are here. Agents act now.
And today:
β
llmfeed.json works
β
MCP works
β
Sites can adopt it today
β
All agents, big and small, can benefit
β
Humans can verify
β
Ecosystems can emerge around trust.
Final Words: "The Real AI Revolution Will Be Signed"
In this race, the question is not:
"Who has the biggest model?"
But:
"Whose data is trusted?"
"Which agent actions are safe?"
"Which answers can be verified?"
And for this β we need MCP. We need llmfeed.json.
π This is why we are building wellknownmcp.org.
π This is why LLMCA exists.
π This is why this ecosystem matters.
Not for the battle of superpowerful AIs.
But to enable a trusted, useful, multi-agent web β today.
Unlock the Complete LLMFeed Ecosystem
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π Next Steps for Agents
β’ Export this content: Available formats
β’ Explore capabilities: API endpoints
β’ Join ecosystem: Contribute to LLMFeed
β’ Download tools: Get MCP resources
β’ Learn prompts: Prompting for agents