Crawl Readiness MCP Server
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- AlicenseNot gradedqualityAmaintenanceEnables AI agents to crawl live websites, audit AEO readiness, generate Schema.org @graph JSON-LD, llms.txt, ai.txt, and robots.txt, inject structured data into HTML, validate optimizations, and retrieve framework-specific code snippets.MIT
- AlicenseNot gradedqualityDmaintenanceMCP server exposing Generative Engine Optimization tools to any AI agent, enabling checking of llms.txt, auditing robots.txt for AI crawlers, and validating JSON-LD schema.MIT

agentbuiltofficial
AlicenseNot gradedqualityCmaintenanceEnables AI agents to run a free AI-readiness audit of any URL, checking AI crawler rules, JavaScript-free page text, JSON-LD, llms.txt, sitemap, meta description, FAQ schema, and returning a score with findings and fixes. Also exposes the same capability via an A2A agent endpoint.MIT- AlicenseNot gradedqualityBmaintenanceEnables AI agents to perform live Google SERP searches, run on-page and full-site SEO audits with prioritized fixes, and check brand visibility in AI answer engines via four MCP tools.MIT
- AlicenseAqualityBmaintenanceEnables chatting with your site's SEO using real data, including crawling, on-page auditing, Google Search Console performance, Core Web Vitals, and competitor comparison from MCP clients like Claude or Cursor.144 npm1MIT
- AlicenseAqualityBmaintenanceEnables running SEO and AI/GEO visibility audits on websites, reading audit results, competitor analyses and expert reports, and importing or retrieving editorial calendars, all from any MCP client such as Claude Desktop, Claude Code or Cursor.11591 npmMIT
TDQS
Scored across 8 tools
Each tool targets a distinct phase or concern: readiness scoring, schema validation, robots auditing, content parity, file generation, and trend monitoring. The only mild ambiguity is check_ai_readiness, which overlaps at a high level with the more specialized validators, but its first-step audit role is clearly described.
All tools follow a lowercase snake_case verb_noun pattern. The mix of check_, validate_, generate_, and get_ verbs is mostly predictable, though check and validate are close synonyms that create a minor stylistic inconsistency.
Eight tools is a well-scoped size for an AI crawl readiness server. Each tool covers a meaningful capability without redundancy, and the count supports both auditing and fixing workflows.
The set covers the main audit workflow (readiness, schema, robots, content parity), generation fixes (llms.txt, robots.txt, schema), and a monitoring view. Minor gaps exist—such as no validator for generated llms.txt and no detailed meta-tag inspection—but agents can complete core tasks without dead ends.