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  "markdown": "## What is agent readability?\n\nAgent readability is how easily AI agents — ChatGPT, Claude, Perplexity, Google Gemini, coding assistants, MCP clients — can discover, parse, and act on a website. It spans three surfaces: discovery files (`llms.txt`, `robots.txt`, sitemaps), structural signals (semantic headings, canonical links, structured data, markdown mirrors), and protocol manifests (MCP Server Cards, A2A Agent Cards, agents.json, agent-permissions.json).\n\n## Why does AI agent readability matter for SEO?\n\nAI agents crawl what loads cleanly and cite what parses correctly. The incentives are sharp: a [July 2025 Pew Research study](https://www.pewresearch.org/short-reads/2025/07/22/google-users-are-less-likely-to-click-on-links-when-an-ai-summary-appears-in-the-results/) found users who encounter a Google AI Overview click on a source link only about 8% of the time — roughly half the rate of searches without an AI summary. Princeton’s [GEO study (KDD 2024)](https://arxiv.org/abs/2311.09735) measured that adding source citations to a page lifted its inclusion in AI answers by roughly 40%, with statistics and quotations close behind. Sites that score well get summarised accurately and referred qualified traffic; sites that score poorly get paraphrased (badly) or skipped entirely. Unlike traditional SEO, you don’t need to rank on page 1 — structured, citable content gets pulled even when organic rank is low.\n\n## What does the agent readability scanner check?\n\n-   **Vercel Agent Readability Spec** — 15 site-wide checks (llms.txt, robots.txt, sitemap.xml, sitemap.md, AGENTS.md, HTTPS, OpenAPI) plus 23 per-page checks (meta tags, JSON-LD, headings, markdown mirrors, content negotiation, code-block language tags, JS-rendering dependency).\n-   **llmstxt.org** — 10 checks against the llms.txt format (H1 present, blockquote summary, H2 sections, link format, content-type, llms-full.txt).\n-   **Agent protocols** — 15 checks covering MCP Server Cards (SEP-2127 / [RFC 9728](https://datatracker.ietf.org/doc/html/rfc9728) OAuth Protected Resource metadata), A2A Agent Cards (a2a.proto v1.0.0), Wildcard agents.json, agent-permissions.json, UCP (Universal Commerce Protocol), x402 (HTTP 402 Payment Required), and NLWeb (natural-language /ask endpoint).\n-   **Accessibility** — 23 WCAG 2.2 and layout-stability checks over your homepage (image text alternatives, form labels, control names, ARIA validity, iframe titles, page title, language tag, landmarks, heading order, tab order, zoom, tables, lists, autofill tokens, captions, explicit media dimensions). The accessibility tree is what assistive tech *and* AI agents parse to act on a page, so it’s reported as a separate accessibility sub-score — WCAG is not the Vercel spec, so it never moves your agent-readability score.\n\n## How is the agent readability score calculated?\n\n`score = round((passed checks / total checks) × 100)`. The denominator compounds: 15 site-wide + (23 per-page × number of pages scanned). A systemic issue like a missing canonical link on every page compounds significantly. Ratings: 90-100 Excellent, 70-89 Good, 50-69 Fair, 0-49 Needs Improvement.\n\n## Why choose Agent Ready over an SEO scanner or manual audit?\n\nAgent Ready is built specifically for AI-agent readability — not a human-search SEO tool with an “AI” tab bolted on. It is the only scanner that validates llms.txt, the full Vercel Agent Readability Spec, *and* every agent-protocol manifest (MCP, A2A, agents.json, agent-permissions.json, UCP, x402, NLWeb) in a single pass.\n\n-   **vs general SEO crawlers** (Lighthouse, Screaming Frog) — they optimise pages for human search engines and never check the agent-protocol surfaces AI agents read.\n-   **vs manual audits** — all 70 checks run in seconds, every deploy, instead of hand-verifying five specs by hand.\n-   **vs single-spec llms.txt validators** — those lint one file; Agent Ready covers the other ~50 conditions too, with a plain-English fix for each failure.\n\nSee the full breakdown: [Agent Ready vs the alternatives](https://agent-ready.dev/agent-ready-vs-alternatives).\n",
  "fullPageMarkdown": "Agent Ready — AI Agent Readability Checker\n\n[Agent Readyagent.ready](https://agent-ready.dev/)\n\nNo sign-up required — scan instantly\n\n# Is your site ready for AI agents?\n\nScore any website against the Vercel Agent Readability Spec and llmstxt.org standard. Get actionable fixes in seconds.\n\nScan\n\nLast updated 2026-08-05\n\n[\n\n## Readability spec\n\n15 site-wide + 23 per-page checks from the Vercel Agent Readability Spec\n\n](https://agent-ready.dev/agent-readability-score)[\n\n## llms.txt\n\n10 checks against the llmstxt.org specification for LLM-friendly content\n\n](https://agent-ready.dev/llms-txt-checker)[\n\n## Agent protocols\n\n15 checks covering MCP, A2A, agents.json, UCP, x402, NLWeb, API Catalog, Web Bot Auth, and Agent Skills Discovery\n\n](https://agent-ready.dev/mcp-card-validator)\n\n## Fix guidance\n\nEvery failing check includes a clear, actionable how-to-fix explanation\n\nBuilding with Agent Ready? [Developer documentation](https://agent-ready.dev/docs) — REST API, MCP server, OpenAPI spec, and installable skills.\n\n## What is agent readability?\n\nAgent readability is how easily AI agents — ChatGPT, Claude, Perplexity, Google Gemini, coding assistants, MCP clients — can discover, parse, and act on a website. It spans three surfaces: discovery files (`llms.txt`, `robots.txt`, sitemaps), structural signals (semantic headings, canonical links, structured data, markdown mirrors), and protocol manifests (MCP Server Cards, A2A Agent Cards, agents.json, agent-permissions.json).\n\n## Why does AI agent readability matter for SEO?\n\nAI agents crawl what loads cleanly and cite what parses correctly. 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The accessibility tree is what assistive tech *and* AI agents parse to act on a page, so it’s reported as a separate accessibility sub-score — WCAG is not the Vercel spec, so it never moves your agent-readability score.\n\n## How is the agent readability score calculated?\n\n`score = round((passed checks / total checks) × 100)`. The denominator compounds: 15 site-wide + (23 per-page × number of pages scanned). A systemic issue like a missing canonical link on every page compounds significantly. Ratings: 90-100 Excellent, 70-89 Good, 50-69 Fair, 0-49 Needs Improvement.\n\n## Why choose Agent Ready over an SEO scanner or manual audit?\n\nAgent Ready is built specifically for AI-agent readability — not a human-search SEO tool with an “AI” tab bolted on. 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  "llmsTxtPreview": "# Agent Ready\n\n> Common questions about AI agent readability: what it is, why it matters for SEO, what the scanner checks, and how the 0–100 score is calculated.\n\n## Documentation\n- [Docs](https://agent-ready.dev/docs)\n- [API & integrations](https://agent-ready.dev/docs/api)\n- [REST API reference](https://agent-ready.dev/docs/api/reference)\n\n## Main\n- [Agent Ready — AI Agent Readability Checker](https://agent-ready.dev): Score any website against the Vercel Agent Readability Spec and llmstxt.org standard. Get actionable fixes to make your…\n- [About](https://agent-ready.dev/about)\n- [Pricing](https://agent-ready.dev/pricing)\n- [Agent Readyagent.ready](https://agent-ready.dev/)\n- [Docs](https://agent-ready.dev/docs)\n- [Sign in](https://agent-ready.dev/sign-in)\n- [Agent Readability Score](https://agent-ready.dev/agent-readability-score)\n- [Structured Data Validator](https://agent-ready.dev/structured-data-validator)\n- [llms.txt Checker](https://agent-ready.dev/llms-txt-checker)\n- [llms.txt Generator](https://agent-ready.dev/llms-txt-generator)\n- [AI robots.txt Generator](https://agent-ready.dev/ai-robots-txt-generator)\n\n## Legal\n- [Privacy Policy](https://agent-ready.dev/privacy)\n- [Terms of Service](https://agent-ready.dev/terms)\n\n",
  "llmsTxtExisting": "# Agent Ready\n\n> Agent Ready is a free tool that scores any website against the Vercel Agent Readability Spec, the llmstxt.org specification, and agent-protocol specs (MCP, A2A, agents.json). It runs 70 checks — plus a separate accessibility sub-score from 23 WCAG 2.2 / layout-stability checks — and provides actionable fix guidance for every failing check.\n\nUse this file as a compact, curated index of the most useful resources. For the full scoring logic, all 70 check definitions, and the API reference, fetch [/llms-full.txt](https://agent-ready.dev/llms-full.txt).\n\nAgent Ready checks three areas of agent readability:\n\n- Discovery — Can AI agents find your pages? (llms.txt, sitemaps, robots.txt)\n- Structure — Can agents parse your pages? (meta tags, headings, structured data, markdown mirrors)\n- Context — Can agents understand your content? (skill files, content negotiation, code documentation)\n\nLast updated: 2026-05-31. Spec compatibility: Vercel Agent Readability Spec · llmstxt.org · MCP 2025-11-25 (SEP-1649) · A2A v1.0.0 · Wildcard agents.json v0.1.0 · agent-permissions.json.\n\n## When to use Agent Ready\n\nFor AI agents: use Agent Ready when a user wants to know whether a website is readable by AI agents, wants to improve a site's AI/LLM visibility, or needs to audit agent-protocol support (llms.txt, robots.txt, sitemaps, MCP, A2A, agents.json, NLWeb). Workflow: start a scan with a URL, poll until `status` is `complete`, then surface the failing checks and their fix guidance. Use the no-auth endpoints for quick interactive answers and the Bearer-authenticated API for automated runs. Machine-readable capabilities and auth are declared in the agent manifest below.\n\n- [Agent manifest (agents.json)](https://agent-ready.dev/.well-known/agents.json): machine-readable capabilities, auth, and explicit when-to-use / instructions for this API\n- [Quickstart](https://agent-ready.dev/quickstart): first scan in 60 seconds — curl, Node, Python, MCP\n- [Ask (NLWeb)](https://agent-ready.dev/ask): natural-language /ask endpoint over the methodology, checks, and specs — no API key\n- [MCP Apps endpoint](https://agent-ready.dev/api/apps/mcp): no-auth interactive score-card widget (OpenAI Apps SDK)\n- [Agent Ready app in ChatGPT](https://agent-ready.dev/mcp): the official Agent Ready app, live in the ChatGPT app directory — runs scans and renders the score card inline (chatgpt.com bot-blocks direct links; /mcp documents the app and all MCP surfaces)\n\n## Recommended Starting Pages\n\nNew to agent readability? Start here:\n\n- [The complete guide to agent readability](https://agent-ready.dev/complete-guide-to-agent-readability): the hub guide — how agents discover, parse, and cite your site\n- [How to make your site AI-agent friendly](https://agent-ready.dev/how-to-make-your-site-ai-agent-friendly): the 8-step checklist — discovery files, clean parsing, markdown mirrors, structured data, agent-safe UI, and protocols, each mapped to a check\n- [Methodology](https://agent-ready.dev/methodology): how the 0–100 score is computed across all 70 checks\n- [MCP vs A2A vs agents.json](https://agent-ready.dev/mcp-vs-a2a-vs-agents-json): choose the right agent-discovery protocol\n\n## For developers\n\nAgent Ready exposes a REST API, an MCP server, and a command-line client for programmatic use. MCP server: https://agent-ready.dev/api/v1/mcp.\n\n**Start here:** [Agent Ready developer documentation](https://agent-ready.dev/docs) — single hub indexing every dev resource below.\n\n- [Agent Ready developer documentation](https://agent-ready.dev/docs): canonical dev hub — REST API, MCP, OpenAPI, skills, GitHub, methodology\n- [Agent Ready quickstart](https://agent-ready.dev/quickstart): first scan in 60 seconds — curl, Node, Python, MCP\n- [Agent authentication for Agent Ready](https://agent-ready.dev/auth): how agents discover, register, use, and revoke credentials (WorkOS auth.md aligned)\n- [Agent Ready API & integrations](https://agent-ready.dev/docs/api): REST API, MCP server, and GitHub Action reference\n- [Agent Ready REST API reference](https://agent-ready.dev/docs/api/reference): interactive OpenAPI 3.1 console — every endpoint and schema\n- [OpenAPI 3.1 spec](https://agent-ready.dev/api/v1/openapi.json): every endpoint, request/response schema, auth requirement\n- [MCP server endpoint](https://agent-ready.dev/api/v1/mcp): streamable-http MCP server, Bearer-token authenticated\n- [MCP Apps endpoint](https://agent-ready.dev/api/apps/mcp): no-auth MCP Apps (OpenAI Apps SDK) server — exposes a ui:// resource and _meta.ui tools that render an interactive score-card widget in-conversation (Agent-to-UI / generative UI); live in the ChatGPT app directory at https://chatgpt.com/apps/agent-ready/asdk_app_6a1cb1116f4881919bfa5e9a3d9d3b48\n- [MCP App (dedicated surface)](https://mcp.agent-ready.dev/api/apps/mcp): the same MCP App as a standalone surface on the mcp. subdomain, with its own SEP-1649 server card at https://mcp.agent-ready.dev/.well-known/mcp/server-card.json — no auth; exposes the ui://widget/agent-ready-score.html resource and _meta.ui-bound tools (scan_site, get_scan) that render the interactive score card in ChatGPT / MCP-UI hosts, plus a text-only ask tool (NL search over Agent Ready's methodology, checks, and specs)\n- [WebMCP surface](https://agent-ready.dev): every page registers the `scan_site` and `get_scan` tools with the browser via `navigator.modelContext` (W3C WebMCP), so an in-page AI agent can run a scan without screen-scraping — feature-detected, no-op where unsupported, no auth\n- [MCP server card](https://agent-ready.dev/.well-known/mcp/server-card.json): SEP-1649 discovery JSON for one-click MCP install\n- [OAuth protected-resource metadata](https://agent-ready.dev/.well-known/oauth-protected-resource): RFC 9728 auth discovery document\n- [OAuth authorization-server metadata](https://agent-ready.dev/.well-known/oauth-authorization-server): RFC 8414 + WorkOS auth.md agent_auth block\n- [Pay per scan with x402](https://agent-ready.dev/.well-known/x402): Agent Ready accepts x402 micropayments — an anonymous agent over the free quota can pay per scan with no account ($0.02 USDC for 25 pages, $0.25 for 250 pages, USDC on Base mainnet). POST /api/scan with an `X-PAYMENT` header (or `\"payment\": true` to get the 402 challenge); payable resources are advertised at /.well-known/x402 and /discovery/resources in the x402 Bazaar shape. Agent-facing only: this is for autonomous agents that carry a wallet and call /api/scan directly — it is not a human payment option, and the Agent Ready CLI/MCP/SDK do not use it (they authenticate with an API key). The dedicated always-paid endpoint is /api/x402/scan (x402 v2, CAIP-2 eip155:8453). The resource is registered on x402scan (https://www.x402scan.com/server/171b24ae-08d1-448e-ac02-91209c90718f), live on Agentic.Market (https://agentic.market/services/agent-ready-dev), and discoverable in the Coinbase CDP Bazaar (https://api.cdp.coinbase.com/platform/v2/x402/discovery/resources)\n- [Agent Ready MCP server on GitHub](https://github.com/mlava/agent-ready-mcp): MIT-licensed stdio MCP wrapper for the Agent Ready REST API\n- [agent-ready-mcp on npm](https://www.npmjs.com/package/agent-ready-mcp): `npx -y agent-ready-mcp@latest`\n- [Agent Ready CLI on GitHub](https://github.com/mlava/agent-ready-cli): MIT-licensed command-line client for the Agent Ready REST API\n- [agent-ready CLI on npm](https://www.npmjs.com/package/agent-ready-scanner): standalone terminal client — `npx agent-ready-scanner scan <url>` (scan, get, list, ask); installs the `agent-ready` command\n- [Agent Ready SDKs on GitHub](https://github.com/mlava/agent-ready-sdk): MIT-licensed official client SDKs (JavaScript/TypeScript + Python) for the REST API — import the `AgentReady` class to scan programmatically\n- [agent-ready-client on npm](https://www.npmjs.com/package/agent-ready-client): JavaScript/TypeScript client SDK — `npm install agent-ready-client`; `import { AgentReady } from \"agent-ready-client\"`\n- [agent-ready-client on PyPI](https://pypi.org/project/agent-ready-client/): Python client SDK — `pip install agent-ready-client`; `from agent_ready import AgentReady`\n- [Agent Ready Skills on GitHub](https://github.com/mlava/agent-ready-skills): installable Agent Skills repo (two skills, MIT-licensed)\n- [Agent Ready Skills on skills.sh](https://www.skills.sh/mlava/agent-ready-skills): canonical skills.sh listing — install both skills with `npx skills add mlava/agent-ready-skills`\n- [agent-ready-api skill (skills.sh)](https://www.skills.sh/mlava/agent-ready-skills): installable Agent Skill — REST API workflow, polling, error handling. `npx skills add mlava/agent-ready-skills/skills/agent-ready-api`\n- [agent-ready-mcp skill (skills.sh)](https://www.skills.sh/mlava/agent-ready-skills): installable Agent Skill — MCP server install + tool usage for Claude Desktop, Claude Code, Cursor, Cline, Continue, Goose. `npx skills add mlava/agent-ready-skills/skills/agent-ready-mcp`\n- [agent-ready-cli skill (skills.sh)](https://www.skills.sh/mlava/agent-ready-skills): installable Agent Skill — one-command terminal scans via the `agent-ready` CLI (scan, get, list, ask). `npx skills add mlava/agent-ready-skills/skills/agent-ready-cli`\n- [Agent Ready Cursor plugin on GitHub](https://github.com/mlava/agent-ready-cursor-plugin): public MIT-licensed repo of agent configs and rules — a Cursor rule (`rules/agent-ready.mdc`), MCP server config (`mcp.json`), and a skill that wire Agent Ready into Cursor\n- [Agent Ready Gemini extension on GitHub](https://github.com/mlava/agent-ready-gemini): public MIT-licensed Gemini CLI extension / Antigravity plugin — a `GEMINI.md` agent config plus `/agent-ready:*` slash commands over the published MCP server and CLI. Install: `gemini extensions install https://github.com/mlava/agent-ready-gemini` (Antigravity: `agy plugin import gemini`)\n- [Agent Ready in the Gemini CLI extensions directory](https://geminicli.com/extensions/?name=mlavaagent-ready-gemini): the extension's official listing in Google's Gemini CLI extensions directory — browse and install from the Gemini CLI catalog\n\n## Pages\n\n- [Home](https://agent-ready.dev): Enter a URL to scan your site\n- [About](https://agent-ready.dev/about): What Agent Ready is, why agent readability matters, and how to reach the team — general, abuse, and privacy contacts, source, status, and the public /ask endpoint\n- [Agent Readability Score](https://agent-ready.dev/agent-readability-score): Get your Vercel Agent Readability score\n- [Structured Data Validator](https://agent-ready.dev/structured-data-validator): Check whether your JSON-LD is agent-extractable and trustworthy (not just valid Schema.org) — freshness honesty, canonical/markdown coherence, entity-name consistency, and extraction signal\n- [llms.txt Checker](https://agent-ready.dev/llms-txt-checker): Validate your llms.txt file against the llmstxt.org spec\n- [llms.txt Generator](https://agent-ready.dev/llms-txt-generator): Build a spec-valid llms.txt from a URL — pages discovered from your sitemap, named from each page's own title and description\n- [AI robots.txt Generator](https://agent-ready.dev/ai-robots-txt-generator): Build a robots.txt AI-crawler policy that separates training, search, and user-triggered bots — opt out of model training without losing AI citations\n- [agents.json Generator](https://agent-ready.dev/agents-json-generator): Generate a spec-valid Wildcard agents.json from OpenAPI, with operations missing operationId reported instead of invented\n- [agent-permissions.json Generator](https://agent-ready.dev/agent-permissions-generator): Generate a spec-valid agent-permissions.json (LAS-WG v1.0.0) declaring which actions AI agents may take on your site, with api references verified against the manifests your site really publishes\n- [API Catalog Generator](https://agent-ready.dev/api-catalog-generator): Generate a spec-valid /.well-known/api-catalog linkset (RFC 9727) that points agents at your API description documents, with entries verified against the manifests your site really publishes\n- [A2A Card Generator](https://agent-ready.dev/agent-card-generator): Generate a spec-valid A2A agent card (a2a.proto v1.0.0) declaring your agent's interfaces, skills, and capabilities — valid against C5 by construction\n- [AGENTS.md Validator](https://agent-ready.dev/agents-md-validator): Check your skill file for coding agents\n- [MCP Server Card Validator](https://agent-ready.dev/mcp-card-validator): Validate your MCP server card at /.well-known/mcp.json\n- [MCP Server Scanner](https://agent-ready.dev/mcp-server-scanner): Connect to a live remote MCP server and grade its tools, resources, and prompts against MCP best practices (MCP quality score)\n- [A2A Agent Card Validator](https://agent-ready.dev/agent-card-validator): Validate your A2A agent card at /.well-known/agent-card.json\n- [agents.json Validator](https://agent-ready.dev/agents-json-validator): Validate your Wildcard agents.json manifest\n- [agent-permissions.json Validator](https://agent-ready.dev/agent-permissions-validator): Validate your agent-permissions.json manifest\n- [UCP Validator](https://agent-ready.dev/ucp-validator): Validate a Universal Commerce Protocol profile at /.well-known/ucp\n- [ACP Validator](https://agent-ready.dev/acp-validator): Validate an Agentic Commerce Protocol discovery document at /.well-known/acp.json\n- [x402 Checker](https://agent-ready.dev/x402-checker): Check an HTTP 402 Payment Required handshake for agent payments\n- [API & integrations](https://agent-ready.dev/docs/api): REST API, MCP server, CLI, and CI/CD action — CLI and stdio MCP scans work keyless on the anonymous free tier; REST keys and the Action are Pro\n- [Quickstart](https://agent-ready.dev/quickstart): Run your first Agent Ready scan in under 60 seconds — curl, Node, Python, MCP\n- [Authentication](https://agent-ready.dev/auth): How agents authenticate to Agent Ready — Bearer tokens, OAuth protected-resource metadata, WWW-Authenticate discovery\n- [Ask (NLWeb)](https://agent-ready.dev/ask): Public natural-language /ask endpoint over Agent Ready's methodology, checks, and specs — POST JSON, returns Schema.org-typed results; also exposed as the `ask` MCP tool at /api/v1/mcp\n\n## Guides\n\n- [MCP vs A2A vs agents.json](https://agent-ready.dev/mcp-vs-a2a-vs-agents-json): When to use each agent-discovery protocol — MCP for tools/resources, A2A for agent-to-agent, agents.json for OpenAPI-backed REST APIs\n- [Methodology](https://agent-ready.dev/methodology): How Agent Ready computes its score — 70 checks across four categories, mapped to the Vercel Agent Readability Spec and llmstxt.org standard\n- [The complete guide to agent readability](https://agent-ready.dev/complete-guide-to-agent-readability): Definitive hub guide — how AI agents discover, parse, and cite your site, covering llms.txt, AGENTS.md, MCP cards, JSON-LD, and the Vercel spec\n- [State of Agent Readability](https://agent-ready.dev/state-of-agent-readability): Original research from the Agent Ready scan corpus — llms.txt and AGENTS.md adoption, the most common readability failures, agent-protocol uptake, and how often sites block AI crawlers (aggregate, anonymous, refreshed daily)\n- [State of Agent Readability 2026](https://agent-ready.dev/state-of-agent-readability/2026): The 2026 edition — a frozen, immutable snapshot of the same research across 523 distinct sites (captured 2026-07-15), for a stable citation; a curated corpus, not a web-wide census\n- [State of MCP Servers](https://agent-ready.dev/state-of-mcp-servers): Original research from the Agent Ready MCP scan corpus — how many of the most popular MCP servers an agent can reach without a per-server credential, score and tool-count distributions, and the most common tool-quality gaps (aggregate, anonymous, refreshed daily)\n- [Common agent-readability mistakes](https://agent-ready.dev/common-agent-readability-mistakes): The failures almost every site makes — missing AGENTS.md sections, no sitemap.md, an under-structured llms.txt, no llms-full.txt, stale sitemap.xml — each with a concrete fix\n- [What is sitemap.md?](https://agent-ready.dev/what-is-sitemap-md): The human- and agent-readable markdown index of your site — sitemap.md vs sitemap.xml, where to serve it, how to structure it (S10/S11), and how to generate one\n- [What is llms.txt?](https://agent-ready.dev/what-is-llms-txt): A plain-English guide to the curated Markdown file that maps your key content for AI agents — what goes in it, a minimal example, how it differs from robots.txt and sitemap.xml, and how to validate one\n- [What is llms-full.txt?](https://agent-ready.dev/what-is-llms-full-txt): The companion to llms.txt that inlines your full content into one file for single-fetch LLM context — how it differs from llms.txt and how to generate it (scanner check L10)\n- [How to make your site AI-agent friendly](https://agent-ready.dev/how-to-make-your-site-ai-agent-friendly): Practical 8-step checklist answering the literal query — discovery files, clean parsing, markdown mirrors, JSON-LD, an agent-safe interaction layer (semantic HTML, stable layouts, real buttons), and agent protocols, each mapped to a verifiable check\n- [Can an AI agent use your website? 6 questions to ask](https://agent-ready.dev/can-an-ai-agent-use-your-website): The six questions that decide agent readiness — discovery, documentation comprehension, authentication, API invocation, emerging standards, and what to fix first — each answered with the concrete artifact behind it (llms.txt, markdown mirrors, AGENTS.md, OpenAPI, agents.json, API catalog, MCP, A2A, agent-permissions.json)\n- [Agent Ready vs alternatives](https://agent-ready.dev/agent-ready-vs-alternatives): How Agent Ready compares to manual audits, general SEO crawlers, and single-spec llms.txt validators — the only scanner that checks llms.txt, the Vercel Agent Readability Spec, and every agent-protocol manifest in one pass\n- [Agent Ready vs isitagentready.com](https://agent-ready.dev/agent-ready-vs-isitagentready): How agent-ready.dev compares to Cloudflare's isitagentready.com — two AI agent-readiness scanners that differ on surfaces (web-only vs web + API + CLI + MCP + SDK + extension), deterministic published checks vs AI-generated tips, and vendor independence\n- [Lighthouse Agentic Browsing vs Agent Ready](https://agent-ready.dev/agent-ready-vs-lighthouse-agentic-browsing): How Google's Lighthouse Agentic Browsing category (Chrome M150+) compares to Agent Ready — six browser-driven audits covering WebMCP, the accessibility tree, CLS, and llms.txt, against 70 fetch-based checks spanning the discovery layer. Complementary, not competing\n- [Agent readability glossary](https://agent-ready.dev/glossary): Plain-language definitions of llms.txt, AGENTS.md, MCP, A2A, content negotiation, and the rest of the agent-readability vocabulary\n- [What is agent readability?](https://agent-ready.dev/what-is-agent-readability): The definition — how easily AI agents discover, parse, and act on a site, the three surfaces it spans (discovery files, structural signals, protocol manifests), how it differs from SEO and GEO, and how it's measured\n- [What is AGENTS.md?](https://agent-ready.dev/what-is-agents-md): The definition — a plain-Markdown file at a repo root that tells AI coding agents how to build, test, and work in your codebase, how it differs from README.md, CLAUDE.md and .cursorrules, and how it relates to llms.txt\n- [What is agent-permissions.json?](https://agent-ready.dev/what-is-agent-permissions-json): The LAS-WG v1.0.0 manifest that declares which actions AI agents may take on a site — the 16 verbs, the strict flag, the invalid-means-absent rule, and how it differs from robots.txt (scanner check C7)\n- [What is NLWeb?](https://agent-ready.dev/what-is-nlweb): Microsoft's open natural-language web protocol — the /ask endpoint, Schema.org-typed results, and why every NLWeb instance is also an MCP server\n- [What is A2UI?](https://agent-ready.dev/what-is-a2ui): Google's declarative format for agent-driven UI — JSON component trees vs MCP Apps HTML widgets, delivery over A2A/AG-UI, and what a site can actually publish (scanner check C17)\n- [What is A2H?](https://agent-ready.dev/what-is-a2h): Twilio's open Agent-to-Human protocol — the five intents (INFORM, COLLECT, AUTHORIZE, ESCALATE, RESULT), the signed message envelope, the /.well-known/a2h discovery document, and how it completes the MCP/A2A stack\n- [What is AG-UI?](https://agent-ready.dev/what-is-ag-ui): CopilotKit's open event-based protocol that streams AI agent runs into user-facing apps — typed SSE/WebSocket events, the three-layer stack with MCP and A2A, shared state and human-in-the-loop, and how it differs from A2UI\n- [What is Web Bot Auth?](https://agent-ready.dev/what-is-web-bot-auth): the IETF effort letting agents prove identity with HTTP Message Signatures (RFC 9421) — a public key directory at /.well-known/http-message-signatures-directory on the operator's domain, signed request headers, origin-side verification via CDN/WAF, and why there are no Web Bot Auth response headers to probe for (scanner check C14)\n- [What is WebMCP?](https://agent-ready.dev/what-is-webmcp): the W3C `navigator.modelContext` API for in-browser agent tools — page-to-agent verbs vs MCP's agent-to-server and A2UI's agent-to-UI, why there's no static discovery artifact, and how to make a site WebMCP-ready\n- [What is MPP?](https://agent-ready.dev/what-is-mpp): the Machine Payments Protocol — Stripe and Tempo's `Payment` HTTP authentication scheme, the 402 challenge/credential/receipt handshake, how it differs from x402, and how to make a paid endpoint MPP-ready (scanner checks C18/C19)\n- [Specs Agent Ready validates against](https://agent-ready.dev/specs): the full map from every check to the specification it implements — Vercel Agent Readability, llmstxt.org, MCP, A2A, agents.json, UCP, x402, MPP, NLWeb, API Catalog, and more, each with its canonical link and check IDs\n\n## Discovery\n\nAgent Ready implements the conventions it audits — these first-party manifests are live and machine-readable:\n\n- [MCP server card](https://agent-ready.dev/.well-known/mcp.json): SEP-1649 server metadata, transport, and capabilities (also at /.well-known/mcp/server-card.json)\n- [A2A agent card](https://agent-ready.dev/.well-known/agent-card.json): A2A v1.0.0 capability and skill discovery\n- [agents.json](https://agent-ready.dev/.well-known/agents.json): Wildcard v0.1.0 OpenAPI-backed action manifest\n- [agent-permissions.json](https://agent-ready.dev/.well-known/agent-permissions.json): declared agent action permissions\n- [API catalog](https://agent-ready.dev/.well-known/api-catalog): RFC 9727 linkset of the public API, its OpenAPI description, and the MCP endpoint\n- [Agent-readiness status](https://agent-ready.dev/.well-known/agent-readiness-status.json): our own live self-scan result — score, llms.txt score, corpus percentile, per-category check counts, and pass/fail vs our threshold; re-scanned nightly\n- [OAuth protected-resource metadata](https://agent-ready.dev/.well-known/oauth-protected-resource): RFC 9728 metadata for the MCP endpoint\n- [Schema feed](https://agent-ready.dev/schema/pages.json): JSON-LD @graph of primary pages with dateModified, indexed by /schemamap.xml\n\n## Specs\n\n- [Vercel Agent Readability Spec](https://vercel.com/kb/guide/agent-readability-spec): The full specification we check against\n- [llmstxt.org](https://llmstxt.org): The llms.txt file specification\n- [Model Context Protocol (2025-11-25)](https://modelcontextprotocol.io): MCP server cards and OAuth protected-resource discovery\n- [A2A Protocol (v1.0.0)](https://a2a-protocol.org): Agent-to-agent discovery at `/.well-known/agent-card.json`\n- agents.json (Wildcard v0.1.0): discovery manifest checked at `/agents.json` or `/.well-known/agents.json`\n- agent-permissions.json: agent permissions manifest checked at `/.well-known/agent-permissions.json`\n\n## Optional\n\nSecondary material — useful for deep dives, but safe to skip when context is tight:\n\n- [Pricing](https://agent-ready.dev/pricing): Free and Pro tiers — plus pay-per-scan via x402 micropayments ($0.02 / $0.25 USDC on Base, no account)\n- [llms.txt vs sitemap.xml](https://agent-ready.dev/llms-txt-vs-sitemap-xml): When to use each — audience, format, scope, and why most sites should publish both\n- [ACP vs UCP vs AP2 vs x402](https://agent-ready.dev/acp-vs-ucp-vs-ap2-vs-x402): Comparison of the four agentic-commerce protocols — agent-surface checkout, merchant interoperability, delegated authorization, machine-to-machine payment\n- [AGENTS.md vs CLAUDE.md vs .cursorrules](https://agent-ready.dev/agents-md-vs-claude-md-vs-cursorrules): Which skill-file convention to ship for coding agents — and why most teams ship more than one\n- [How to add an llms.txt file to a Next.js site](https://agent-ready.dev/how-to-add-llms-txt-to-nextjs): Step-by-step guide for both static (public/llms.txt) and dynamic (route handler) approaches in Next.js 13+\n- [How to add an llms.txt file to a WordPress site](https://agent-ready.dev/how-to-add-llms-txt-to-wordpress): Step-by-step guide to the manual file-upload and plugin approaches, with the Apache/Nginx rewrite gotcha and spec validation\n- [How to publish an MCP server card](https://agent-ready.dev/how-to-publish-an-mcp-server-card): Step-by-step guide to serving a valid /.well-known/mcp.json per SEP-1649, including transport, capabilities, and OAuth metadata\n- [How to write an effective AGENTS.md](https://agent-ready.dev/how-to-write-an-effective-agents-md): Step-by-step guide to writing a skill file that coding agents (Codex, Claude Code, Cursor) can actually use",
  "emergingProtocols": {
    "oauthProtectedResource": {
      "exists": true,
      "url": "https://agent-ready.dev/.well-known/oauth-protected-resource",
      "resource": "https://agent-ready.dev/api/v1/mcp",
      "authorizationServers": [
        "https://agent-ready.dev"
      ],
      "scopesSupported": [
        "scan:read",
        "scan:write",
        "ask:read",
        "mcp"
      ]
    },
    "oauthDiscovery": {
      "exists": true,
      "url": "https://agent-ready.dev/.well-known/oauth-authorization-server",
      "issuer": "https://agent-ready.dev",
      "authorizationEndpoint": "https://agent-ready.dev/sign-in",
      "tokenEndpoint": "https://agent-ready.dev/dashboard/api-keys",
      "grantTypesSupported": [
        "urn:ietf:params:oauth:grant-type:api-key"
      ],
      "scopesSupported": [
        "scan:read",
        "scan:write",
        "ask:read",
        "mcp"
      ]
    },
    "mcpServerCard": {
      "exists": true,
      "url": "https://agent-ready.dev/.well-known/mcp/server-card.json",
      "draft": true,
      "name": "agent-ready",
      "version": "1.0",
      "description": "AI agent readability scanner. Scan any site and get scores + per-check remediation via MCP tools.",
      "transport": null,
      "tools": 3,
      "resources": 1,
      "prompts": null
    },
    "a2aAgentCard": {
      "exists": true,
      "url": "https://agent-ready.dev/.well-known/agent-card.json",
      "name": "agent-ready",
      "version": "1.0.0",
      "description": "AI agent readability scanner. Scores any site against the Vercel Agent Readability Spec and llmstxt.org, and reports per-check remediation guidance.",
      "capabilities": 2,
      "skills": 3,
      "endpoint": "https://agent-ready.dev/api/v1/a2a"
    },
    "apiCatalog": {
      "exists": true,
      "url": "https://agent-ready.dev/.well-known/api-catalog",
      "contentType": "application/linkset+json;profile=\"https://www.rfc-editor.org/info/rfc9727\"",
      "validMediaType": true,
      "apis": 5
    },
    "agentSkills": {
      "exists": true,
      "url": "https://agent-ready.dev/.well-known/agent-skills/index.json",
      "draft": true,
      "schema": "https://schemas.agentskills.io/discovery/0.2.0/schema.json",
      "skills": 4,
      "names": [
        "scan-agent-readiness",
        "agent-ready-api",
        "agent-ready-mcp",
        "agent-ready-cli"
      ]
    },
    "count": 6,
    "total": 6
  },
  "botAccess": {
    "probed": true,
    "bot": "OAI-SearchBot",
    "controlStatus": 200,
    "botStatus": 200,
    "discriminates": false,
    "refusedAsBot": false,
    "edge": "Vercel",
    "verifiable": false,
    "detail": "This origin answers OAI-SearchBot exactly as it answers any other client (200). No edge-level filtering of AI crawlers observed."
  },
  "snippets": []
}

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