Inlay
- 1 repo stars
- Updated May 7, 2026
- cartoonitunes/inlay-skills
Inlay is a MCP server that makes your website discoverable to AI agents via per-site MCP, llms.txt, and structured data.
About
Inlay MCP helps founders make an existing website machine-readable for AI agents and answer engines. Instead of only tuning meta tags for traditional SEO, you connect a site-specific MCP remote (using your Inlay site key) alongside llms.txt and structured data so external agents can retrieve authoritative summaries and facts about your product. Skillselion catalogs it under Launch → GEO because the value appears when you are shipping pages and want citations, referrals, and accurate AI answers—not during raw idea research. It complements human-facing launch work: distribution posts, landing copy, and analytics still matter, but Inlay reduces the gap where bots ignore your site because there is no agent-oriented surface. Setup is dashboard-driven; you are not installing a heavy local server unless you also adopt their broader Inlay stack from the linked repository.
- Per-site MCP remotes at inlay.dev/api/mcp/{site_key} with streamable-http and SSE transports
- Publishes llms.txt and structured data so AI agents can find and summarize your pages
- Site key from inlay.dev/dashboard—required URL variable in the MCP manifest
- Version 1.0.1 from cartoonitunes/inlay-skills on GitHub
- Targets builders who care about Perplexity, ChatGPT Search, and agent-driven discovery—not only classic Google SEO
Inlay by the numbers
- Data as of Jul 7, 2026 (Skillselion catalog sync)
claude mcp add --transport http inlay https://inlay.dev/api/mcp/%7Bsite_key%7DAdd your badge
Show developers this MCP server is listed on Skillselion. Paste this into your README.
| repo stars | ★ 1 |
|---|---|
| Transport | HTTP, SSE |
| Auth | None |
| Last updated | May 7, 2026 |
| Repository | cartoonitunes/inlay-skills ↗ |
What it does
Expose your site to AI crawlers and answer engines with Inlay’s MCP endpoint, llms.txt, and structured data so agents can cite your product accurately.
Who is it for?
Best when you have a live marketing site or docs and want AEO/GEO coverage and MCP exposure without building a custom agent API.
Skip if: Pre-launch ideas with no URL yet, or teams that only need on-page SEO plugins with no AI-agent channel.
What you get
After you configure your Inlay site key and MCP remote, agents can pull governed site context instead of guessing from noisy HTML snippets.
- Per-site MCP endpoint wired with your site_key
- llms.txt and structured data surfacing for agent consumption
- Clearer AI-agent and answer-engine discovery path for your brand
By the numbers
- Manifest version 1.0.1
- Two remote transports: streamable-http and sse at the same URL pattern
- Required path variable: site_key (from inlay.dev/dashboard)
README.md
Inlay Skills
AI Agent Skills for Website AI Readiness
Agent skills to audit and optimize any website for AI readiness — llms.txt, MCP servers, structured data, semantic HTML, and more.
Install
npx skills add cartoonitunes/inlay-skills
Works with Claude Code, Cursor, Codex, OpenCode, and 35+ other agents.
Skills
🔍 ai-readiness-audit
Audit any website for AI agent readiness using the Inlay API. Get a score out of 100, letter grade, per-category breakdown, and actionable recommendations.
> Audit https://example.com for AI readiness
What it checks:
- llms.txt presence and quality
- MCP server availability
- Structured data (JSON-LD / schema.org)
- Meta tags and Open Graph
- Semantic HTML structure
- AI bot permissions in robots.txt
- Performance, security, accessibility
- Content quality and AI signals
📄 setup-llms-txt
Create and configure llms.txt for your website. Analyzes your project, generates the file, and places it in the right location for your framework.
> Set up llms.txt for this project
🔌 setup-mcp-server
Set up an MCP (Model Context Protocol) server for your website via Inlay. Enables AI agents to search and interact with your site.
> Set up an MCP server for my website
Example Audit Output
📊 AI Readiness Score: 62/100 (C)
Category Score Status
llms.txt 0 ❌
MCP Server 0 ❌
Structured Data 45 ⚠️
Meta Quality 78 ✅
Semantic HTML 85 ✅
Robots & Crawling 60 ⚠️
Performance 72 ✅
🔧 Top Recommendations:
1. Create llms.txt (+15 points)
2. Set up MCP server via Inlay (+12 points)
3. Unblock AI bots in robots.txt (+8 points)
Why AI Readiness Matters
AI agents and AI search engines (ChatGPT, Perplexity, Claude, Gemini) are becoming primary ways people discover and interact with websites. Sites that are optimized for AI agents get:
- Cited more often in AI search results
- Better tool integration with AI assistants
- Higher visibility as AI-first browsing grows
Inlay helps you measure and improve your AI readiness score.
Contributing
Contributions welcome! Open an issue or PR.
License
MIT
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AI discoverability and llms.txt MCP layer, not a code generator or vehicle-data integration.
FAQ
Who is Inlay MCP for?
Developers and small teams with a deployed site who want AI agents and answer engines to discover accurate product information through MCP and structured exports.
When should I use Inlay MCP?
Use it at Launch when pages are live and you are optimizing for AI search visibility, citations, and agent-readable site metadata—not before you have a site key and public URLs.
How do I add Inlay MCP to my agent?
Create a site at inlay.dev, copy your site_key from the dashboard, and add the remote URL https://inlay.dev/api/mcp/{site_key} (streamable-http or SSE) to your MCP client configuration.