CVin.Bio / AI Infrastructure
Built for
AI agents
Every CVin.Bio profile is engineered for machine-readability. Structured metadata, standardized schemas, and protocol-level integrations make your professional data natively consumable by AI assistants, search agents, and automated hiring infrastructure.
How AI agents find you
PDFs are invisible to AI
PDF is a print-era format operating in a machine-learning era. When an AI agent encounters a PDF, it must run OCR, infer document structure, resolve formatting ambiguities, and handle layout engine inconsistencies. Most systems deprioritize or skip them entirely.
A CVin.Bio profile is a structured webpage with machine-readable metadata baked into the HTML. An AI agent reads it the same way it reads any web page, except every data point is explicitly labeled and categorized.
Skills, job titles, companies, dates, degrees, credentials. All structured as JSON-LD with explicit type annotations. Zero parsing overhead. Zero extraction loss.
PDF vs Live link readability
ATS read PDFs. AI agents read links. If your CV is still a file, the next wave of hiring tools cannot see you.
Four layers of AI discoverability
CVin.Bio implements a multi-layer discovery architecture. Every profile is accessible through four independent systems, each optimized for a different class of AI consumer.
Architecture
Schema.org / JSON-LD
Every profile embeds a complete Person schema with hasOccupation, hasCredential, alumniOf, knowsAbout, and sameAs. Work history includes employer, title, dates, and location. Education includes degree type and institution. This is the universal standard that Google, Bing, and AI assistants already understand.
llms.txt
A dynamically generated index at /llms.txt catalogs every public profile with name, skills, and summary. Regenerated hourly. Functions as a sitemap.xml equivalent optimized for LLM consumption. A single HTTP request returns the complete profile directory.
Model Context Protocol
The CVin.Bio MCP server implements two callable tools. search_candidates queries the profile database by skill, location, or job title. get_profile retrieves a complete structured profile by username. Compatible with any MCP-enabled AI assistant.
Explicit crawler access
Most platforms restrict AI crawlers. We implement an open-access policy. Over 100 user agents are recognized in robots.txt across AI, search, social, SEO, academic, and content categories. Full max-snippet:-1 meta directives enable unrestricted content indexing for compliant agents.
What this means for you
AI agents surface your profile autonomously. Your professional data is continuously indexed and matchable without manual applications.
AI agents parse structured JSON-LD in milliseconds. No OCR pipeline. No regex extraction. No keyword heuristics. Direct schema-to-model data transfer.
Update your profile once. Every connected AI system receives the latest version on its next query. Single source of truth. Always synchronized.
Your profile is not a static file sitting in a folder. It is a live endpoint that AI systems query in real time.
For developers and AI agents
Integration endpoints
CVin.Bio exposes structured professional data through standardized integration points. Read-only access to public profile endpoints follows web standards. MCP-level integration is available for qualified partners.
Profile index for LLMs
GET https://cvin.bio/llms.txt
Returns all public profiles with name, skills, and summary. Plain text. Updated hourly. Cache: 1h with stale-while-revalidate.
Structured profile data (JSON-LD)
GET https://cvin.bio/{username}Every profile page contains a JSON-LD script tag. Extract the schema.org/Person object from the HTML.
<script type="application/ld+json">
{
"@context": "https://schema.org",
"@type": "Person",
"name": "Jane Smith",
"url": "https://cvin.bio/jane",
"jobTitle": "Senior Engineer",
"worksFor": {
"@type": "Organization",
"name": "Stripe"
},
"knowsAbout": ["React", "TypeScript", "Node.js"],
"hasOccupation": [...],
"hasCredential": [...],
"alumniOf": [...],
"sameAs": [...]
}
</script>MCP tools (Model Context Protocol)
search_candidates(query, limit)
Search by skill, location, job title, or keyword. Returns up to 20 matching profiles with full work history and education.
get_profile(username)
Fetch a complete profile by slug. Returns structured data including custom sections and credentials.
Available via stdio transport. Contact hi@cvin.bio for MCP server access and configuration.
XML Sitemap
GET https://cvin.bio/sitemap.xml
All profile URLs with lastmod timestamps. Includes static pages, blog posts, and dynamic user profiles. Updated on every build.
Robots.txt
GET https://cvin.bio/robots.txt
100+ user agents explicitly allowed. Public profiles, blog, and reports are fully crawlable. Editor, API, and admin routes are disallowed.
Response headers
Content-Type: text/html; charset=utf-8 X-Robots-Tag: index, follow, max-snippet:-1, max-image-preview:large, max-video-preview:-1 Cache-Control: public, s-maxage=3600
No content restrictions. AI systems can use unlimited text snippets and full-size image previews.
Recognized user agents
AI Agents
Search Engines
Social & Preview
Apple & Amazon
SEO & Analytics
Archive & Research
Feed & Content
Standards-compliant access to public profile endpoints. Respects robots.txt directives.