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Export Feed Type

💊 The Information Capsule Concept​

Universal Application Sources​

Export feeds transform any information into structured capsules that LLMs can understand:

Desktop App → Export Feed → LLM understands context
Database Query → Export Feed → Agent processes results
User Conversation → Export Feed → Transfer to another agent
System Logs → Export Feed → AI analyzes patterns

What Makes a Good Information Capsule​

  1. Context: Not just data, but where it came from and why
  2. Structure: Organized for machine processing
  3. Metadata: Creation time, origin, purpose, tags
  4. Trust Information: Signature status, verification hints
  5. Usage Hints: How the LLM should interpret or use the data

Beyond Web Exports​

While export buttons on websites are common, the format works for any application:

  • Electron apps can export user projects as .llmfeed.json
  • Mobile apps can share user data with proper consent
  • CLI tools can output structured reports for agent analysis
  • Desktop software can create portable context for AI assistants
  • IoT devices can export sensor data with metadata

The key is packaging information with intent so any LLM receiving the capsule understands its purpose and provenance.


🔏 Signature and Trust​

Why Sign Export Feeds?​

Signatures provide three critical guarantees:

  1. Ownership: Proves who created the export
  2. Integrity: Ensures content hasn't been tampered with
  3. Trust: Allows LLMs and agents to assess reliability

When to Sign​

Data TypeSignatureReason
Public documentationOptionalFor authenticity and discoverability
Personal exportsRecommendedFor integrity and provenance
Sensitive dataRequiredFor trust and compliance
Enterprise exportsRequiredFor audit and governance
API credentialsAlwaysFor security and verification

Trust Levels​

{
"trust": {
"trust_level": "self-declared", // or "certified"
"scope": "partial", // or "complete"
"signed_blocks": ["metadata", "content"],
"certifier": "https://example.com/.well-known/public.pem"
}
}

Note: Unsigned exports are still valid but may be treated with lower trust by security-conscious agents and enterprise systems.


📄 Basic metadata

title: "Feed Type: export.llmfeed.json" description: "MCP documentation on Feed Type: export.llmfeed.json - Universal information capsules for LLM consumption" date: "2025-06-17T10:00:00.000Z" lang: "en"

🏷️ Tags and classification

tags:

  • "mcp"
  • "ai-agents"
  • "security"
  • "data-classification"
  • "information-capsules" format: "documentation" category: "technical" contentType: "documentation"

🧠 Intent and audience

intent: "inform" llmIntent: "browse-spec" llmTopic: "specification" audience:

  • "llm"
  • "developer"
  • "security-engineer"
  • "enterprise-architect"

📊 Page properties

pageType: "documentation" interactionComplexity: "simple" priority: "normal" riskLevel: "low" updateFrequency: "static"

🔗 URLs

slug: "llmfeed_feedtype_export" canonical_url: "https://wellknownmcp.org/spec/02_llmfeed_feedtype/llmfeed_feedtype_export" githubUrl: "https://github.com/wellknownmcp/llmfeed-spec/blob/main/02_llmfeed_feedtype/llmfeed_feedtype_export.md" mcpFeedUrl: "/.well-known/mcp.llmfeed.json"

🤖 Agent optimization

autoDiscoverFeeds: true agentReadiness: true llmBehaviorHints: "suggest-only"

📋 Capabilities

capabilities:

  • "verification"
  • "export"
  • "feed-generation"
  • "security-classification"
  • "information-capsules"

Feed Type: export.llmfeed.json

Purpose​

This feed creates information capsules from any application or data source — ready for LLM consumption, agent processing, or secure transfer.

Export feeds can originate from:

  • Web applications: dashboards, documentation, user interfaces
  • Desktop software: documents, databases, project files
  • Mobile apps: user data, settings, conversations
  • Command-line tools: logs, reports, system information
  • APIs and services: structured data, responses, metadata

The core concept is packaging information with context so LLMs can understand not just the data, but its origin, purpose, and trustworthiness.

Security Extension: Supports automatic data classification and secure export workflows for enterprise environments.


Location​

Typical path:

/exports/faq.llmfeed.json

Can be linked from:

  • llm-index.llmfeed.json
  • buttons on site (ExportToLLM)
  • internal agent menus

Basic Structure​

{
"feed_type": "export",
"metadata": {
"title": "FAQ",
"origin": "https://example.org",
"description": "Frequently asked questions",
"generated_at": "2025-06-17T10:30:00Z"
},
"summary": "This FAQ explains the trust system and how to verify signed feeds.",
"tags": ["faq", "documentation", "trust"],
"trust": { ... }
}

🔐 Security-Enhanced Export Structure​

For exports containing potentially sensitive data, the format extends with security metadata:

{
"feed_type": "export",
"metadata": {
"title": "Page Export with Security",
"origin": "https://example.com/secure-page",
"generated_at": "2025-06-17T10:30:00Z"
},
"data_classification": {
"security_scan_performed": true,
"sensitive_data_handling": "user_consented",
"redacted_fields": ["api_keys", "internal_urls"],
"warning_shown": true,
"user_consent": {
"timestamp": "2025-06-17T10:29:45Z",
"items_approved": ["email_addresses", "user_preferences"],
"items_rejected": ["internal_system_ids"]
}
},
"content": {
"processed_html": "...",
"metadata_extracted": "...",
"sensitive_placeholders": {
"[API_KEY_REDACTED]": "Original contained an API key",
"[INTERNAL_URL_REDACTED]": "Internal URL masked for security"
}
},
"trust": {
"data_integrity": "verified",
"sanitization_performed": true,
"risk_level": "low"
}
}

Data Classification Levels​

LevelPattern ExamplesHandling
🔴 CRITICALsk_, password, -----BEGIN PRIVATE KEY-----Automatically redacted
🟡 SENSITIVEEmail addresses, phone numbers, internal URLsUser consent required
🟢 PUBLICDocumentation, marketing content, public APIsNormal export

Security Workflow​

  1. Automatic Scan: Content is scanned for sensitive patterns
  2. Classification: Data is categorized by sensitivity level
  3. User Consent: For sensitive data, user chooses what to include
  4. Secure Export: Generate feed with appropriate redaction and metadata

Modes of Generation​

ModeDescriptionSecurity FeaturesSource Examples
StaticPre-generated file stored anywherePre-screened contentDocumentation, manuals, templates
DynamicGenerated on-demand via API or applicationReal-time classificationUser dashboards, personalized exports
LiveExtracted in real-time from running applicationInteractive consentWeb pages, active documents, live data

Universal Application: These modes work for any type of application — web, desktop, mobile, or command-line. The export mechanism adapts to the platform while maintaining the same feed structure.

⚠️ Security Note: Signature is recommended for static exports, and required for dynamic exports containing sensitive data.


🧳 Structured Bundles (data.files[])​

An export feed may describe the contents of an archive (ZIP) via a data.files[] block.

Minimal example (structure only):​

{
"feed_type": "export",
"metadata": { "title": "Bundle Index" },
"data": {
"files": [
{ "path": "README.md" },
{ "path": "src/index.js" },
{ "path": "images/logo.png" }
]
}
}

Security-enhanced bundle:​

{
"data": {
"files": [
{
"path": "src/config.js",
"tags": ["code", "configuration"],
"description": "Application configuration",
"security_classification": "sensitive",
"redaction_applied": "credentials_masked"
},
{
"path": "README.md",
"tags": ["documentation", "public"],
"description": "Project documentation",
"security_classification": "public"
}
],
"security_summary": {
"total_files": 2,
"public_files": 1,
"sensitive_files": 1,
"critical_files": 0
}
}
}

🎯 Export Use Cases​

Simple Documentation Export​

{
"feed_type": "export",
"metadata": {
"title": "API Documentation",
"origin": "https://api.example.com/docs"
},
"content": {
"documentation": "Complete API reference...",
"endpoints": [...],
"examples": [...]
}
}

Secure Credential Export​

{
"feed_type": "export",
"metadata": {
"title": "API Access Package",
"origin": "https://dashboard.example.com"
},
"data_classification": {
"security_scan_performed": true,
"sensitive_data_handling": "admin_approved",
"classification_level": "restricted"
},
"content": {
"api_endpoint": "https://api.example.com",
"key_hint": "sk_live_abc***",
"permissions": ["read", "write"],
"rate_limits": "1000/hour"
},
"trust": {
"signed_blocks": ["content", "metadata"],
"certifier": "https://example.com/.well-known/public.pem"
}
}

Page Context Export with Privacy​

{
"feed_type": "export",
"metadata": {
"title": "Dashboard Export",
"origin": "https://app.example.com/dashboard"
},
"data_classification": {
"security_scan_performed": true,
"sensitive_data_handling": "user_consented",
"user_consent": {
"email_addresses": true,
"user_preferences": true,
"internal_ids": false
}
},
"content": {
"dashboard_data": "User preferences and settings...",
"user_email": "user@example.com",
"internal_user_id": "[USER_ID_REDACTED]"
}
}

🛡️ Enterprise Security Features​

Automatic Pattern Detection​

const CRITICAL_PATTERNS = {
api_keys: /^(sk_|pk_|key_|token_|secret_)/i,
passwords: /password|pwd|pass/i,
private_keys: /-----BEGIN.*PRIVATE KEY-----/,
session_tokens: /sess_|session_/i
};

const SENSITIVE_PATTERNS = {
emails: /\b[A-Za-z0-9._%+-]+@[A-Za-z0-9.-]+\.[A-Z|a-z]{2,}\b/g,
phone_numbers: /\b\d{3}[-.]?\d{3}[-.]?\d{4}\b/g,
internal_urls: /https?:\/\/internal\.|localhost/g
};

Compliance Integration​

  • GDPR: Automatic consent management for PII
  • SOX: Audit trail for financial data exports
  • HIPAA: PHI detection and handling
  • Corporate Policies: Custom pattern detection

Best Practices​

Security​

  • ✅ Always scan for sensitive data before export
  • ✅ Implement user consent for personal information
  • ✅ Use placeholders for redacted content
  • ✅ Sign exports containing any sensitive data
  • ✅ Log all export activities for audit

Performance​

  • ✅ Use tags to describe content type
  • ✅ Inline small content, reference large files
  • ✅ Include file metadata for bundles
  • ✅ Reference via llm-index for discoverability

User Experience​

  • ✅ Clear consent interfaces for sensitive data
  • ✅ Preview what will be exported
  • ✅ Explain why data is being redacted
  • ✅ Provide export without sensitive data option

🚀 Future: Progressive Integration Levels​

Export feeds are the foundation of a progressive integration strategy:

  • Level 1-2: Inline + file exports with security (✅ implemented)
  • Level 3: Universal export buttons with consent UX
  • Level 4-5: Browser & OS integration (See Vision →)

For enterprise security considerations, see our Enterprise Roadmap.