ai.llmse/mcp

MCPcommunautéen ligne
v1.3.12ai.llmseUnknownMis à jour il y a 8 mois

Public MCP server for the LLM Search Engine

État de l’endpointen ligne
vérifié il y a 7 jours · 262 ms
100 % des dernières 5 vérifications ont atteint cet endpoint
Fonctionne dans
ClaudeCursorCopilotChatGPTGemini

Déduit des transports déclarés par cette annonce (streamable-http). Un client absent de cette liste n’est pas écarté pour autant — c’est simplement quelque chose que Forge ne peut pas confirmer.

Indexé automatiquement depuis des sources publiques. Pas encore vérifié par son développeur sur Forge.Revendiquer cette annonce →
il y a 8 moisDernière mise à jour
Paquet
Auteurai.llmse
LicenceUnknown
Version1.3.12
Sourcemcp-registry
Statut de confiance
B
60/100Bon
✓Listé dans l’index Forge+10/10
—Identité de l’éditeur vérifiée+0/30
→ Éditeur : aucune référence de dépôt n’est enregistrée pour cette annonce, `forge publish` ne peut donc pas vérifier la propriété automatiquement. Utilisez « Revendiquer cette annonce » ci-dessus — Forge les examine à la main.
—Vérification de domaine+0/10
→ Actuellement indisponible pour ce type d’annonce — la vérification de domaine ne s’exécute aujourd’hui que pour les paquets adossés à npm, cette ligne ne peut donc pas encore être obtenue ici, quel que soit le contenu hébergé sur le domaine.
✓Analyse d’injection de prompt · propre+30/30
✓Analyse d’obfuscation / exfiltration · propre+20/20
StatutIndexé par la communauté
ÉditeurNon vérifié
SignatureNon signé
Domaine—
Provenance—
DépendancesNon audité
Surface d’outils10 outils · aucun privilégié
Analyse de sécurité✓ Proprevlive · il y a 1 moisQuelle est l’efficacité de cette analyse ?
PROMPTtool:classify_urlLinks to undeclared domain: example.com
PROMPTtool:analyze_seoLinks to undeclared domain: example.com
PROMPTtool:analyze_eeatLinks to undeclared domain: example.com
PROMPTtool:analyze_aeoLinks to undeclared domain: example.com
PROMPTtool:analyze_wcagLinks to undeclared domain: example.com
PROMPTtool:analyze_readabilityLinks to undeclared domain: example.com
PROMPTtool:auditLinks to undeclared domain: example.com
ÉvaluationsAucune
Indexé13 juin 2026

La vérification confirme l’identité de l’éditeur (la propriété du dépôt), pas la sûreté du code. L’analyse de sécurité couvre les CVE connues et les scripts d’installation suspects.

Outils

10 outils · aucun privilégié
Observé en direct depuis l’endpoint du fournisseur1mo ago

Lu depuis un véritable échange MCP initialize → tools/list contre l’endpoint déclaré. Aucun outil n’a été invoqué — tools/list est l’appel d’introspection en lecture seule que le protocole prévoit pour cela. Cela reflète ce que le serveur annonçait à cet instant ; un endpoint hébergé n’est figé sur aucune version et peut changer sans préavis.

  • https://llmse.ai/mcp10 outils · 1334 ms
classify_urlClassify 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

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

Aucun schéma d’entrée n’a été publié pour cet outil.

select_advertiserSelect 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)

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)

Aucun schéma d’entrée n’a été publié pour cet outil.

analyze_seoAnalyze 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 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

Aucun schéma d’entrée n’a été publié pour cet outil.

analyze_eeatAnalyze 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 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

Aucun schéma d’entrée n’a été publié pour cet outil.

analyze_aeoAnalyze 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 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

Aucun schéma d’entrée n’a été publié pour cet outil.

analyze_wcagAnalyze 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

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

Aucun schéma d’entrée n’a été publié pour cet outil.

analyze_garmCompute 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

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

Aucun schéma d’entrée n’a été publié pour cet outil.

analyze_readabilityAnalyze 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 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

Aucun schéma d’entrée n’a été publié pour cet outil.

auditPerform 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

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

Aucun schéma d’entrée n’a été publié pour cet outil.

find_similar_sitesFind 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

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

Aucun schéma d’entrée n’a été publié pour cet outil.

10 outils sur 10 ont publié une description.

Les noms et descriptions d’outils sont écrits par l’éditeur et affichés tels quels, comme du texte inerte. Ce sont les chaînes qu’un client MCP transmet à un modèle, alors Forge y recherche des motifs d’injection de prompt — tout constat apparaît avec l’analyse de sécurité ci-dessus. « Privilégié » est une correspondance de mot-clé sur le nom de l’outil, pas un audit de ce qu’il fait : un nom anodin peut tout de même tout faire.

À propos

Public MCP server for the LLM Search Engine

Mots-clés
mcp
Alternatives
Comparaison des surfaces d’outils…

Aucune couverture des dépendances

Cette entrée ne publie aucun paquet npm : Forge n'a donc pas d'arbre de dépendances pour elle. C'est une lacune de couverture — pas une affirmation qu'elle n'a aucune dépendance.