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ai.llmse/mcp

REMOTE · LLMSE.AI · SCANNED AUG 3

Public MCP server for the LLM Search Engine

Available components

+6 this week 62 Trust /100
Trust breakdown (6 categories)

How this component scores in each security and reliability category. Every signal is checked automatically against the live server, and we only credit what we can confirm. How we score →

Endpoint Security63
Transport & Reachability100
Schema Quality & AI Usability54
  • AI-judged instruction clarity (good).Pass
  • Context-footprint check failed: tool/resource definitions use about 2823 tokens (~282/item across 10 items; 10 tools + 0 resources), over budget; trim descriptions and params. See how to fix → Fail
  • Usage-examples check failed: none of the tools include examples. See how to fix → Fail
Stability & Change Management27
  • Stability observed for 8 of 30 days with no destabilising changes; credit accrues until the full window elapses.Partial
Tool Coverage71
  • 100% of tools have a non-trivial description (not blank, and not just the tool's name).Pass
  • 0% of tool parameters carry a description.Fail
  • Structured output schemas are declared (100% of tools); any adoption earns full credit.Pass
Capabilities100
  • Implements a supported MCP spec version (2025-11-25); the latest is 2026-07-28.Pass
Install

Add this component to your MCP client. Where a client-specific snippet is available, pick your client below and copy it straight into your config; otherwise use the connection detail shown.

remote · llmse.ai

# add to Claude Code
claude mcp add --transport http ai-llmse-mcp https://llmse.ai/mcp
# ~/.codex/config.toml
[mcp_servers.ai-llmse-mcp]
url = "https://llmse.ai/mcp"
// opencode.json
{
  "$schema": "https://opencode.ai/config.json",
  "mcp": {
    "ai-llmse-mcp": {
      "type": "remote",
      "url": "https://llmse.ai/mcp",
      "enabled": true
    }
  }
}
# add to OpenClaw
openclaw mcp add ai-llmse-mcp --url https://llmse.ai/mcp --transport streamable-http
# ~/.hermes/config.yaml
mcp_servers:
  ai-llmse-mcp:
    url: "https://llmse.ai/mcp"
// mcp.json
{
  "mcpServers": {
    "ai-llmse-mcp": {
      "type": "http",
      "url": "https://llmse.ai/mcp"
    }
  }
}

The mcpServers block is a cross-client convention. Remote transports vary, so check your client's docs.

Changelog

Every change we have recorded for this component, newest first. Security-relevant changes are always shown. ▲ marks a change for the better, ▼ a change for the worse; unmarked changes are neutral.

  • 2 Aug 26 +1

    No change was recorded against any check on this day. Stability & Change Management went from 20 to 23. That category is still filling its 30-day observation window: 6 days of observed history at the previous scan, 7 at this one. The score rises as the window fills, whether or not the server changes.

  • 31 Jul 26 +3
    • We updated how we score, so this day's move reflects our rubric, not a change to the server See what changed → functional
  • 30 Jul 26 +1
    • We updated how we score, so this day's move reflects our rubric, not a change to the server See what changed → functional
  • 29 Jul 26 +1

    No change was recorded against any check on this day. Stability & Change Management went from 7 to 10. That category is still filling its 30-day observation window: 2 days of observed history at the previous scan, 3 at this one. The score rises as the window fills, whether or not the server changes.

  • 27 Jul 26 +1
    • We updated how we score, so this day's move reflects our rubric, not a change to the server See what changed → functional
  • 26 Jul 26 55

    First indexed and scored.

Diagnostics

Diagnostic detail from the automated scan of this channel: what the scanner observed at each step, so you can see exactly where a check passed or failed. It is informational only and never changes the trust score.

Captured 3 Aug 2026 · Probed https://llmse.ai/mcp

TLS valid

Negotiated TLS 1.3 with TLS_AES_128_GCM_SHA256 .

Subject Issuer Valid from Valid until Key Signature Serial
CN=llmse.ai CN=WE1,O=Google Trust Services,C=US 12 Jul 2026 10 Oct 2026 ECDSA 256 ECDSA-SHA256 f65123a2976455540ece846e12d64d9b
SANs: llmse.ai, *.llmse.ai
CN=WE1,O=Google Trust Services,C=US (CA) CN=GTS Root R4,O=Google Trust Services LLC,C=US 13 Dec 2023 20 Feb 2029 ECDSA 256 ECDSA-SHA384 7ff31977972c224a76155d13b6d685e3
CN=GTS Root R4,O=Google Trust Services LLC,C=US (CA) CN=GlobalSign Root CA,OU=Root CA,O=GlobalSign nv-sa,C=BE 15 Nov 2023 28 Jan 2028 ECDSA 384 SHA256-RSA 7fe530bf331343bedd821610493d8a1b
DNSSEC insecure

Validation of llmse.ai. Not signed

Zone DS Keys Algorithms Outcome
. trust_anchor 20326, 38696 8, 8 Verified
ai. present 3799 8 Verified
llmse.ai. absent Unsigned (proven) parent-signed NSEC/NSEC3 proves an unsigned delegation
Authentication No authorisation required

The endpoint answered without asking for a token. Anyone who knows the URL can reach it.

Result No authorisation required
HTTP status 200
Header Value
strict-transport-security max-age=2592000
Transports 2 probes
Transport URL Outcome Status Location
streamable-http https://llmse.ai/mcp Verified 200
http (plaintext) http://llmse.ai/mcp HTTPS enforced 301 https://llmse.ai/mcp
MCP tools — 10 exposed · ~2,823 tokens

The tools this component advertises to a client, with an estimated token cost for each. Expand a tool to see its parameters and schema. The per-tool counts are indicative and are not scored directly; the schema's total context footprint is one signal in Schema Quality & AI Usability.

Tool Tokens
analyze_aeo ~383

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

NameTypeReqDescription
urlstringyes

Structured output declared, but exposes no named fields.

No examples provided.

analyze_eeat ~314

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

NameTypeReqDescription
urlstringyes

Structured output declared, but exposes no named fields.

No examples provided.

analyze_garm ~302

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

NameTypeReqDescription
category
sentiment
url

Structured output declared, but exposes no named fields.

No examples provided.

analyze_readability ~316

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

NameTypeReqDescription
urlstringyes

Structured output declared, but exposes no named fields.

No examples provided.

analyze_seo ~175

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

NameTypeReqDescription
urlstringyes

Structured output declared, but exposes no named fields.

No examples provided.

analyze_wcag ~254

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

NameTypeReqDescription
urlstringyes

Structured output declared, but exposes no named fields.

No examples provided.

audit ~334

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

NameTypeReqDescription
urlstringyes

Structured output declared, but exposes no named fields.

No examples provided.

classify_url ~181

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

NameTypeReqDescription
urlstringyes

Structured output declared, but exposes no named fields.

No examples provided.

find_similar_sites ~187

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

NameTypeReqDescription
limitinteger
urlstringyes

Structured output declared, but exposes no named fields.

No examples provided.

select_advertiser ~377

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)

NameTypeReqDescription
age
category
gender
limitinteger
max_cpm
min_cpm
sentiment
subcategory
url

Structured output declared, but exposes no named fields.

No examples provided.