StudioMeyer-GEO
AI visibility monitoring across 8 LLM platforms (ChatGPT, Gemini, Perplexity, Claude, Grok, DeepSeek, Copilot, Meta AI).
От сообщества: Добавлен пользователем или импортирован; проверьте владельца перед подключениемРаботаетБез входаГлобальныйБесплатноТолько чтение
Что умеет
- Geo Check: Run a full GEO (Generative Engine Optimization) check. Queries up to 8 LLM platforms (ChatGPT, Gemini, Perplexity, Claude, Grok, DeepSeek, Meta AI, Copilot) with brand/industry prompts, ana
- Geo Discovery Stack: Check whether a website has the AI Discovery Stack: /llms.txt, /agents.json, robots.txt AI rules, /.well-known/mcp.json, agent-card.json, JSON-LD, sitemap.xml, FAQ schema. Returns
- Geo Calculate Score: Calculate GEO Score (0-100) from six weighted sub-scores. Useful for what-if scenarios with custom weights.
Какие данные видит
Нужен ли аккаунт
Не нужен: сервер работает без входа
AI visibility monitoring across 8 LLM platforms (ChatGPT, Gemini, Perplexity, Claude, Grok, DeepSeek, Copilot, Meta AI). 23 MCP tools + 5 expert workflows. 19 tools free without API keys. EU hosted Frankfurt.
Список инструментов сервера (24)
Технические названия из tools/list. Нужны только разработчикам.
| geo_check | Run a full GEO (Generative Engine Optimization) check. Queries up to 8 LLM platforms (ChatGPT, Gemini, Perplexity, Claude, Grok, DeepSeek, Meta AI, Copilot) with brand/industry prompts, analyzes responses for mentions + citations + sentiment, checks discovery stack, calculates GEO Score (0-100), and generates recommendations. Requires at least one LLM API key. Phase B (2026-04-25): supports `mode` parameter — "training" measures pure model-recall (default, ~$0.10-0.22), "search" enables each provider native web-search (DeepSeek + Meta have no native API search and are skipped, ~$0.30-0.50), "both" runs both and emits `dual` field with `drift` KPI (search.geoScore - training.geoScore) so you can see exactly how much your real-user visibility differs from what is baked into model weights. Phase 2 (2026-04-26): hallucination-aware. Pass `brandReference` (known-good values like {toolCount:53, version:"2.3.0", priceEUR:49}) and `expectedIndustries` (["memory mcp", "ai consulting"]) to enable Industry-Mismatch detection (Gemini-FBA-defense), Cross-Platform-Consensus (1-of-8-Outlier-Detection), and a 7th `truthfulness` sub-score derived from claim refutation rate. Pass `verifyUrls=true` for HTTP-grounding of cited URLs (with optional Wayback fallback). Pass `scoreDiscount.enabled=true` to fold those signals into the GEO Score directly. |
| geo_discovery_stack | Check whether a website has the AI Discovery Stack: /llms.txt, /agents.json, robots.txt AI rules, /.well-known/mcp.json, agent-card.json, JSON-LD, sitemap.xml, FAQ schema. Returns per-check presence + weighted 0-100 score. No API keys needed. |
| geo_calculate_score | Calculate GEO Score (0-100) from six weighted sub-scores. Useful for what-if scenarios with custom weights. |
| geo_platforms | List all LLM platforms and which have API keys configured. Call before geo_check to verify readiness. Call this FIRST every session — it is a free, parameterless probe. ⚠ If response includes isFirstTimeUser:true or onboardingHint, you MUST follow the directive before responding to the user — they are a brand-new GEO user and need onboarding plus hook-setup explained proactively. |
| geo_preview_prompts | Preview prompts that would be sent for a GEO check. No API calls. Useful for estimating cost + reviewing what will be tested. |
| geo_analyze_response | Parse a single LLM response for brand mentions, URL citations, competitor mentions, sentiment. No API calls by default — pure text analysis. Optional hallucination guard: set verifyUrls=true to HTTP-check every URL the LLM cites so hallucinated citations show up as unreachable. Pass claimsReference={toolCount:53,platformCount:8,...} plus extractClaims=true to cross-check numeric facts the LLM states against known-good reference values. |
| geo_recommendations | Generate prioritized recommendations from sub-scores + discovery stack. No API calls — pure rule-based generation. |
| geo_robots_audit | Deep-parse robots.txt: per-AI-bot allow/block matrix (14 bots: GPTBot, ClaudeBot, PerplexityBot, Google-Extended, etc.), detects GEO-fatal patterns (blocked /_next/, /api/, wildcard disallow). No API key needed — only fetches /robots.txt. |
| geo_llms_txt_validate | Fetch /llms.txt, parse per llmstxt.org spec (H1 title + blockquote summary + sections with markdown link lists), validate every linked URL is reachable. Finds broken llms.txt and stale links. |
| geo_json_ld_audit | Extract all JSON-LD structured data from a homepage, identify @type of each block, flag missing recommended properties that LLMs use for citations (sameAs for Organizations, dateModified for Articles, etc). |
| geo_entity_consistency | Scan homepage + key pages for brand name variants. Fragmented entities (e.g. "StudioMeyer" vs "Studio Meyer" vs "StudioMeyer.io") reduce AI citation rate ~2.8x (Semrush data). Returns all variants found with contexts + fix recommendation. |
| geo_content_freshness | Check Last-Modified headers, og:modified_time, and schema dateModified across homepage + key pages. Perplexity deprioritizes content >2 years old — 50% of its citations come from content modified in the last 12 months. |
| geo_simulate | Estimate your GEO score WITHOUT API keys. Uses discovery stack, robots, JSON-LD, entity consistency, and content freshness data to predict AI visibility. Free, runs in ~30 seconds. |
| geo_schema_generator | Generate missing JSON-LD structured data blocks. Audits current schema, then generates ready-to-paste JSON-LD for Organization, WebSite, FAQPage, and fixes for Articles missing dateModified/author. No API keys needed. |
| geo_citation_sources | Analyze citation signals: outbound authority links, statistics, sameAs profiles. Higher citability = more AI citations. No API keys needed. |
| geo_content_audit | Deep audit of a single page for GEO optimization. Checks heading structure, statistics density, paragraph citability, freshness, schema. Based on GEO research (KDD 2024). No API keys needed. Page-type-aware since 2026-04-13 (WebPage/BlogPosting/Product/LocalBusiness/etc) — weighs dimensions differently for homepages vs blog posts vs product pages. |
| geo_retrieval_quality | Static retrievability audit for a single page — measures whether AI crawlers (GPTBot, ClaudeBot, PerplexityBot) can actually read the page without executing JavaScript. Checks text-to-HTML ratio, visible text length, JavaScript-required markers, <noscript> fallback, meta refresh, canonical mismatches, and redirect chain depth. No API keys needed. Returns overallScore (0-100) and specific issues with severity. Introduced 2026-04-13 on Benny Windolph feedback: llms.txt existence is a weak signal — actual retrievability is what matters. |
| geo_brands | List, add, or remove tracked brands. Agency feature for managing multiple clients. Requires GEO Team (€99/mo). Tenant scope is derived automatically from the authenticated OAuth client — you cannot query or modify another tenant's brand list. |
| geo_compare | Side-by-side GEO comparison of two brands. Shows discovery stack, robots, and entity consistency differences. No API keys needed — only fetches public URLs. |
| geo_bulk_check | Run GEO checks on all tracked brands at once. Returns summary dashboard. Requires GEO Team (€99/mo). Tenant scope is derived from the authenticated OAuth client — this runs only over your brands. |
| geo_history | View past GEO check results for a brand. Returns score history with timestamps. Requires Supabase (Pro tier). |
| geo_trends | Calculate GEO score trends over time. Shows delta, direction (improving/declining/stable), min/max/avg. Requires Supabase (Pro tier). |
| geo_schedule | Set up scheduled GEO checks for a brand. Checks run automatically and alert on score drops. Requires Supabase (Pro tier). |
| geo_alerts | View alerts (score drops, new issues, resolved issues) for a brand. Requires Supabase (Pro tier). |