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Alternatives to geo-inspector-mcp

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    • A
      license
      A
      quality
      B
      maintenance
      Enables AI agents to check whether a public website is crawlable, understandable, and ready for AI search workflows through local-only audits of robots.txt, sitemaps, metadata, and llms.txt.
      3
      71 npm
      1
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      license
      A
      quality
      D
      maintenance
      An MCP server that gives AI agents tools to inspect a website's visibility to AI answer engines, including crawler permissions, llms.txt, structured data, on-page signals, and a full 29-check AI-readiness audit.
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    • A
      license
      A
      quality
      B
      maintenance
      Enables MCP clients to check whether AI answer engines such as ChatGPT, Claude and Perplexity can read and cite a given site, reporting robots.txt rules, edge-level bot blocks, llms.txt, structured data, JS-only content and other citation blockers with a score and fixes. It can also draft a starter llms.txt file from a site's homepage.
      2
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    • A
      license
      A
      quality
      A
      maintenance
      Checks what GPTBot, ClaudeBot, PerplexityBot and 50+ other AI crawlers can read on a site and what its access policy allows, checks whether a page permits search, answers, training or agent use (with a signed receipt), generates llms.txt, robots.txt and JSON-LD, and reads your Answer Analysis. Nine tools for Claude Desktop, Cursor and other MCP clients.
      9
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    • A
      license
      Not graded
      quality
      C
      maintenance
      Enables 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.
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    TDQS

    A4/5.0

    Scored across 4 tools

    Disambiguation5/5

    Each tool targets a distinct aspect of website metadata for AI discoverability: robots.txt, llms.txt, schema markup, and meta directives. No functional overlap.

    Naming Consistency5/5

    All tool names follow a clear verb_noun pattern: check_robots_txt, fetch_llms_txt, detect_schema_markup, check_meta_directives, with consistent snake_case.

    Tool Count5/5

    4 tools is an ideal size for this focused domain—each tool addresses a necessary and distinct inspection task without redundancy or clutter.

    Completeness4/5

    The set covers the key AI-related metadata surfaces: robots.txt, llms.txt, schema.org markup, and meta robots directives. A minor gap is direct sitemap inspection, though sitemaps are referenced in robots.txt.

    Maintenance

    ActivitySlowing
    ResponsivenessNo issues