ai. llmse/ mcp
by llmse.ai · remote · no sign-in to list tools · v1.3.12 · published by ai.llmse
Public MCP server for the LLM Search Engine
10 tools: 3 change things and 7 only read.
Scanned Oct 21, 2026
- Deletes or cancels0Claude Code: deny
- Can't be undone0Claude Code: ask
- Changes things3Claude Code: ask: see these tools
- Only reads7Claude Code: allow: see these tools
1 check matched something in the tool definitions. No finding is not a safety guarantee. How the checks work.
claude mcp add --transport http llmse https://llmse.ai/mcpFindings
Matches of fixed checks, with the text they matched.
- Infoanalyze_eeat
The description mentions "credentials".
What this check looks forMatched text
description: "...s of experience - Expertise: Author credentials, certifications, professional membershi..."
Tools
Open a tool for its reasons and full description. Descriptions are the publisher's own words, shown as they are.
10 tools
Changes things 3Claude Code: ask
auditPerform comprehensive audit of a website URL.No findings
Why it is in this group
- Nothing in its name or description says what it does, so it is counted as a write.
Description, as the server wrote it Perform comprehensive audit of a website URL. Fetches the URL content ONCE and provides a combined report with: - Classification: category, subcategory, language, sentiment, demographics - SEO Analysis: score, grade, issues, recommendations - EEAT Analysis: experience, expertise, authoritativeness, trustworthiness scores - AEO Analysis: AI answer engine optimization score, metrics, issues, signals (includes full Citation Readiness analysis in the nested 'citation' key) - Advertiser Matching: best-fit advertising networks with scores - Similar Sites: competitor/related sites from the same category This is more efficient than calling classify_url, analyze_seo, analyze_eeat, analyze_aeo, select_advertiser, and find_similar_sites separately as it only fetches the page once. Args: url: The website URL to audit (e.g., "https://example.com"). Returns: Comprehensive audit report with: - url: The analyzed URL - classification: Category, subcategory, language, sentiment, demographics - seo: Score, grade, issues, recommendations - eeat: EEAT score, grade, category scores, issues, signals - aeo: AEO score, grade, metrics, issues, signals (includes citation results) - advertisers: Matched advertising networks with scores - similar_sites: Related sites from the same category (up to 10) - cached: Whether result was from cache
classify_urlClassify a website URL into category, subcategory, language, and sentiment.No findings
Why it is in this group
- Nothing in its name or description says what it does, so it is counted as a write.
Description, as the server wrote it Classify a website URL into category, subcategory, language, and sentiment. Fetches the URL content and uses AI for classification. Results are cached for fast subsequent lookups. Rate limited to 1 request per minute per domain. Args: url: The website URL to classify (e.g., "https://example.com"). Returns: Classification result with: - url: The normalized URL - category: Main category (e.g., "Sports", "Technology") - subcategory: Specific subcategory - language: Detected content language - sentiment: Content sentiment (Good/Neutral/Bad) - age: Target age group (if available) - gender: Target gender (if available) - cached: Whether result was from cache
select_advertiserSelect the best advertisers based on website demographics.No findings
Why it is in this group
- The name "select_advertiser" says "select": a word for a change.
Description, as the server wrote it Select the best advertisers based on website demographics. Matches advertisers to website content based on classification demographics. Provide either a URL (classification will be fetched) or demographics directly. Rate limited to 1 request per minute per domain when using URL. Scoring weights: - Category match: +10 points - Age match: +5 points - Gender match: +3 points - Sentiment match: +2 points - Higher CPM bid as tiebreaker Args: url: URL to match advertisers for (fetches classification from cache). category: Target category (e.g., "Sports", "Automotive"). subcategory: Target subcategory. age: Target age group (e.g., "18-24", "25-34", "31-51"). gender: Target gender ("male", "female", or "all"). sentiment: Content sentiment ("Good", "Neutral", or "Bad"). limit: Number of advertisers to return (1-10, default 3). min_cpm: Minimum CPM cost filter (e.g., 5.0 for $5+ CPM). max_cpm: Maximum CPM cost filter (e.g., 10.0 for $10 or less CPM). Returns: Dictionary with: - matches: List of matched advertisers with scores - match_count: Number of matches found - classification: URL classification (if URL provided) - demographics: Provided demographics (if no URL)
Only reads 7Claude Code: allow
analyze_aeoAnalyze how well content is optimized for AI answer engines.No findings
Why it is in this group
- The name "analyze_aeo" says "analyze": a word for reading.
Description, as the server wrote it Analyze how well content is optimized for AI answer engines. Evaluates content for AI answer engines (ChatGPT, Perplexity, Gemini, Claude). Combines Q&A pattern detection, snippet extractability, and entity clarity analysis with a full Citation Readiness assessment. AEO Scoring Framework (100 points): - Answer Format Detection: 30 points (Q&A extractability patterns) - FAQ Schema Presence: 20 points (FAQPage schema markup) - HowTo Schema Presence: 15 points (HowTo schema markup) - Direct Answer Snippets: 20 points (short extractable blocks <50 words) - Entity Clarity Score: 15 points (clear entity definitions) Neutral Schema Scoring: If no FAQ/HowTo-style content detected, those schema metrics score full points rather than penalizing. Grade Scale: A (85-100), B (70-84), C (55-69), D (40-54), F (0-39) Results are cached for fast subsequent lookups. Rate limited to 1 request per minute per domain. Args: url: The website URL to analyze (e.g., "https://example.com"). Returns: AEO analysis with: - url: The analyzed URL - aeo_score: Overall AEO score (0-100) - aeo_grade: Letter grade (A-F) - aeo_metrics: Individual metric scores - citation: Full Citation Readiness analysis (score, grade, issues, signals) - issues: Problems detected (critical, warnings, info) - signals: Positive signals detected - recommendations: Prioritized improvements - cached: Whether result was from cache
analyze_eeatAnalyze a website URL for E-E-A-T (Experience, Expertise, Authoritativeness, Trustworthiness).1 finding
Why it is in this group
- The name "analyze_eeat" says "analyze": a word for reading.
Findings
- Info
The description mentions "credentials".
What this check looks forMatched text
description: "...s of experience - Expertise: Author credentials, certifications, professional membershi..."
Description, as the server wrote it Analyze a website URL for E-E-A-T (Experience, Expertise, Authoritativeness, Trustworthiness). Evaluates content quality signals based on Google's Search Quality Rater Guidelines and "Creating helpful content" documentation. Detects EEAT signals including: - Experience: First-person language, case studies, testimonials, years of experience - Expertise: Author credentials, certifications, professional memberships, topic depth - Authoritativeness: Organization schema, awards, trust badges, media mentions - Trustworthiness: HTTPS, contact info, privacy policy, source citations Also detects YMYL (Your Money or Your Life) content for health, financial, and legal topics. Results are cached for fast subsequent lookups. Rate limited to 1 request per minute per domain. Args: url: The website URL to analyze (e.g., "https://example.com"). Returns: EEAT analysis result with: - url: The analyzed URL - score: Overall EEAT score (0-100) - grade: Letter grade (A-F) - scores: Individual category scores (experience, expertise, authoritativeness, trustworthiness) - issues: Categorized issues (critical, warnings, info) - signals: Detected EEAT signals - meta: Extracted meta information - recommendations: Prioritized list of improvements - cached: Whether result was from cache
analyze_garmCompute GARM brand safety score for a website or category.No findings
Why it is in this group
- The name "analyze_garm" says "analyze": a word for reading.
Description, as the server wrote it Compute GARM brand safety score for a website or category. Based on the GARM (Global Alliance for Responsible Media) Brand Suitability Framework. Maps content categories to 11 GARM sensitive content categories with risk levels (Floor, High, Medium, Low). Can either: 1. Provide a URL - classification will be fetched and mapped to GARM 2. Provide category and sentiment directly for instant scoring Score interpretation: higher = safer for advertising. Floor categories (e.g., Adult) always score 0/F regardless of sentiment. Args: category: LLMSE category (e.g., "Adult", "Politics", "Sports"). sentiment: Content sentiment ("Bad", "Neutral", "Good"). url: Optional URL to analyze (fetches classification from cache). Returns: GARM brand safety analysis with: - score: Brand safety score (0-100, higher = safer) - grade: Letter grade (A-F) - garm_category: Matched GARM category name or None - risk_level: "floor"|"high"|"medium"|"low"|"none" - is_floor: True if not suitable for any advertising - issues: Categorized issues {critical, warnings, info} - recommendations: Improvement suggestions
analyze_readabilityAnalyze a website URL for content readability using Flesch Reading Ease.No findings
Why it is in this group
- The name "analyze_readability" says "analyze": a word for reading.
Description, as the server wrote it Analyze a website URL for content readability using Flesch Reading Ease. Extracts plain text from HTML and computes readability metrics including Flesch Reading Ease score, Flesch-Kincaid grade level, reading time, and word/sentence statistics. Grade Scale (web-optimized): - A (60-100): Easy, 6th-8th grade — ideal for web content - B (50-59): Fairly easy, some high school - C (30-49): Standard, college level - D (10-29): Difficult, graduate level - F (0-9): Very difficult, professional/academic Results are cached for fast subsequent lookups. Rate limited to 1 request per minute per domain. Args: url: The website URL to analyze (e.g., "https://example.com"). Returns: Readability analysis with: - url: The analyzed URL - score: Flesch Reading Ease score (0-100, higher = easier) - grade: Letter grade (A-F) - flesch_kincaid_grade_level: US school grade level equivalent - reading_time_minutes: Estimated reading time in minutes - word_count: Total word count - sentence_count: Total sentence count - difficult_words: Count of difficult/uncommon words - cached: Whether result was from cache
analyze_seoAnalyze a website URL for SEO optimizations.No findings
Why it is in this group
- The name "analyze_seo" says "analyze": a word for reading.
Description, as the server wrote it Analyze a website URL for SEO optimizations. Fetches the URL content and analyzes HTML for possible SEO improvements. Results are cached for fast subsequent lookups. Rate limited to 1 request per minute per domain. Args: url: The website URL to analyze (e.g., "https://example.com"). Returns: SEO analysis result with: - url: The analyzed URL - score: Overall SEO score (0-100) - grade: Letter grade (A-F) - issues: List of SEO issues found (critical, warnings, info) - meta: Extracted meta information (title, description, headings, etc.) - recommendations: Prioritized list of improvements - cached: Whether result was from cache
analyze_wcagAnalyze a website URL for WCAG 2.1 Level A accessibility issues.No findings
Why it is in this group
- The name "analyze_wcag" says "analyze": a word for reading.
Description, as the server wrote it Analyze a website URL for WCAG 2.1 Level A accessibility issues. Automated static HTML analysis covering approximately 30-40% of WCAG 2.1 Level A criteria. Checks include: image alt text, form labels, heading hierarchy, page title, html lang, empty links/buttons, ARIA labels, duplicate IDs, skip navigation, table headers, landmarks, viewport zoom, autoplay media, and tabindex ordering. Manual testing is required for full WCAG compliance assessment. Results are cached for fast subsequent lookups. Rate limited to 1 request per minute per domain. Args: url: The website URL to analyze (e.g., "https://example.com"). Returns: WCAG analysis with: - url: The analyzed URL - score: Accessibility score (0-100) - grade: Letter grade (A-F) - issues: Categorized issues (critical, warnings, info) - meta: Extracted accessibility metadata - recommendations: Prioritized improvements - coverage_note: Disclaimer about automated coverage - cached: Whether result was from cache
find_similar_sitesFind similar or competitor websites based on classification.No findings
Why it is in this group
- The name "find_similar_sites" says "find": a word for reading.
Description, as the server wrote it Find similar or competitor websites based on classification. Takes a URL, classifies it (or uses cached classification), and returns other websites from the same category and subcategory. Useful for competitive analysis and discovering related content. Rate limited to 1 request per minute per domain. Args: url: The website URL to find similar sites for. limit: Maximum number of similar sites to return (1-50, default 10). Returns: Dictionary with: - url: The input URL (normalized) - classification: The URL's category and subcategory - similar_sites: List of similar URLs from the same category - total_in_category: Total sites in this category/subcategory - cached: Whether the classification was from cache
This is not a safety rating, and no finding is not a safety guarantee. The groups and findings come from fixed checks of the tool definitions the server returned on the date shown, not from its code or what it does when called. How the checks work.
Install
Pinned to version 1.3.12. Values in angle brackets are yours to fill in.
claude mcp add --transport http llmse https://llmse.ai/mcpRun in a terminal.
Claude Code permissions
Allow the reads, ask before a change, deny the deletes. Paste into .claude/settings.json.
{
"permissions": {
"allow": [
"mcp__llmse__analyze_seo",
"mcp__llmse__analyze_eeat",
"mcp__llmse__analyze_aeo",
"mcp__llmse__analyze_wcag",
"mcp__llmse__analyze_garm",
"mcp__llmse__analyze_readability",
"mcp__llmse__find_similar_sites"
],
"ask": [
"mcp__llmse__classify_url",
"mcp__llmse__select_advertiser",
"mcp__llmse__audit"
],
"deny": []
}
}Tools that only read are allowed, tools that change things ask first, tools that delete or cancel are denied. It assumes the server is installed as llmse. Review it before you use it.