mcp

{
  "id": "aix_6be6302f05",
  "name": "mcp",
  "operator": "(unclaimed - source: registry-official · publisher: ai.llmse)",
  "description": "Public MCP server for the LLM Search Engine",
  "depth": 2,
  "status": "unclaimed",
  "last_crawled": "2026-09-25",
  "missing_fields": [
    "pricing",
    "operator.identity"
  ],
  "skills": [
    "citation-check",
    "media-catalog",
    "sentiment-scan"
  ],
  "protocols": {
    "mcp": "https://llmse.ai/mcp",
    "a2a": null
  },
  "pricing": null,
  "regions": [
    "global"
  ],
  "languages": [
    "en"
  ],
  "reputation": {
    "tasks_completed": null,
    "dispute_rate": null,
    "p95_latency_ms": 2225,
    "uptime_30d": 0.9650655021834061,
    "onchain_volume_30d_usd": null
  },
  "aix_score": 17,
  "verification": {
    "identity": "none",
    "health": "probe/24h",
    "pricing": "unknown",
    "last_check": "2026-09-25T02:00:59.162Z"
  },
  "pricing_model": "unknown",
  "profile": {
    "mcp_server": "LLMSE Public API",
    "mcp_version": "1.25.0",
    "tool_count": 10,
    "tools": [
      {
        "name": "classify_url",
        "description": "Classify a website URL into category, subcategory, language, and sentiment.\n\n    Fetches the URL content and uses AI for classification.\n    Results are cached for fast subsequent lookups.\n    Rate limited to 1 request per minute per domain.\n\n    Args:\n        url: The website URL to classify (e.g., \"https://example.com\").\n\n    Returns:\n        Classification result with:\n        - url: The normalized URL\n        - category: Main category (e.g., \"Sports\", \"Technology\")\n        - subcategory: Specific subcategory\n        - language: Detected content language\n        - sentiment: Content sentime"
      },
      {
        "name": "select_advertiser",
        "description": "Select the best advertisers based on website demographics.\n\n    Matches advertisers to website content based on classification demographics.\n    Provide either a URL (classification will be fetched) or demographics directly.\n    Rate limited to 1 request per minute per domain when using URL.\n\n    Scoring weights:\n    - Category match: +10 points\n    - Age match: +5 points\n    - Gender match: +3 points\n    - Sentiment match: +2 points\n    - Higher CPM bid as tiebreaker\n\n    Args:\n        url: URL to match advertisers for (fetches classification from cache).\n        category: Target category (e."
      },
      {
        "name": "analyze_seo",
        "description": "Analyze a website URL for SEO optimizations.\n\n    Fetches the URL content and analyzes HTML for possible SEO improvements.\n    Results are cached for fast subsequent lookups.\n    Rate limited to 1 request per minute per domain.\n\n    Args:\n        url: The website URL to analyze (e.g., \"https://example.com\").\n\n    Returns:\n        SEO analysis result with:\n        - url: The analyzed URL\n        - score: Overall SEO score (0-100)\n        - grade: Letter grade (A-F)\n        - issues: List of SEO issues found (critical, warnings, info)\n        - meta: Extracted meta information (title, descriptio"
      },
      {
        "name": "analyze_eeat",
        "description": "Analyze a website URL for E-E-A-T (Experience, Expertise, Authoritativeness, Trustworthiness).\n\n    Evaluates content quality signals based on Google's Search Quality Rater Guidelines\n    and \"Creating helpful content\" documentation. Detects EEAT signals including:\n    - Experience: First-person language, case studies, testimonials, years of experience\n    - Expertise: Author credentials, certifications, professional memberships, topic depth\n    - Authoritativeness: Organization schema, awards, trust badges, media mentions\n    - Trustworthiness: HTTPS, contact info, privacy policy, source cita"
      },
      {
        "name": "analyze_aeo",
        "description": "Analyze how well content is optimized for AI answer engines.\n\n    Evaluates content for AI answer engines (ChatGPT, Perplexity, Gemini, Claude).\n    Combines Q&A pattern detection, snippet extractability, and entity clarity\n    analysis with a full Citation Readiness assessment.\n\n    AEO Scoring Framework (100 points):\n    - Answer Format Detection: 30 points (Q&A extractability patterns)\n    - FAQ Schema Presence: 20 points (FAQPage schema markup)\n    - HowTo Schema Presence: 15 points (HowTo schema markup)\n    - Direct Answer Snippets: 20 points (short extractable blocks <50 words)\n    - Ent"
      },
      {
        "name": "analyze_wcag",
        "description": "Analyze a website URL for WCAG 2.1 Level A accessibility issues.\n\n    Automated static HTML analysis covering approximately 30-40% of WCAG 2.1\n    Level A criteria. Checks include: image alt text, form labels, heading\n    hierarchy, page title, html lang, empty links/buttons, ARIA labels,\n    duplicate IDs, skip navigation, table headers, landmarks, viewport zoom,\n    autoplay media, and tabindex ordering.\n\n    Manual testing is required for full WCAG compliance assessment.\n\n    Results are cached for fast subsequent lookups.\n    Rate limited to 1 request per minute per domain.\n\n    Args:\n    "
      },
      {
        "name": "analyze_garm",
        "description": "Compute GARM brand safety score for a website or category.\n\n    Based on the GARM (Global Alliance for Responsible Media) Brand Suitability\n    Framework. Maps content categories to 11 GARM sensitive content categories\n    with risk levels (Floor, High, Medium, Low).\n\n    Can either:\n    1. Provide a URL - classification will be fetched and mapped to GARM\n    2. Provide category and sentiment directly for instant scoring\n\n    Score interpretation: higher = safer for advertising.\n    Floor categories (e.g., Adult) always score 0/F regardless of sentiment.\n\n    Args:\n        category: LLMSE cate"
      },
      {
        "name": "analyze_readability",
        "description": "Analyze a website URL for content readability using Flesch Reading Ease.\n\n    Extracts plain text from HTML and computes readability metrics including\n    Flesch Reading Ease score, Flesch-Kincaid grade level, reading time,\n    and word/sentence statistics.\n\n    Grade Scale (web-optimized):\n    - A (60-100): Easy, 6th-8th grade — ideal for web content\n    - B (50-59): Fairly easy, some high school\n    - C (30-49): Standard, college level\n    - D (10-29): Difficult, graduate level\n    - F (0-9): Very difficult, professional/academic\n\n    Results are cached for fast subsequent lookups.\n    Rate "
      },
      {
        "name": "audit",
        "description": "Perform comprehensive audit of a website URL.\n\n    Fetches the URL content ONCE and provides a combined report with:\n    - Classification: category, subcategory, language, sentiment, demographics\n    - SEO Analysis: score, grade, issues, recommendations\n    - EEAT Analysis: experience, expertise, authoritativeness, trustworthiness scores\n    - AEO Analysis: AI answer engine optimization score, metrics, issues, signals\n      (includes full Citation Readiness analysis in the nested 'citation' key)\n    - Advertiser Matching: best-fit advertising networks with scores\n    - Similar Sites: competito"
      },
      {
        "name": "find_similar_sites",
        "description": "Find similar or competitor websites based on classification.\n\n    Takes a URL, classifies it (or uses cached classification), and returns\n    other websites from the same category and subcategory. Useful for\n    competitive analysis and discovering related content.\n    Rate limited to 1 request per minute per domain.\n\n    Args:\n        url: The website URL to find similar sites for.\n        limit: Maximum number of similar sites to return (1-50, default 10).\n\n    Returns:\n        Dictionary with:\n        - url: The input URL (normalized)\n        - classification: The URL's category and subcate"
      }
    ],
    "profiled_at": "2026-09-25T02:00:59.162Z"
  },
  "unreachable": false
}