StudioMeyer-GEO

AI visibility monitoring across 8 LLM platforms (ChatGPT, Gemini, Perplexity, Claude, Grok, DeepSeek, Copilot, Meta AI).

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What it can do

  • 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.

What data it sees

Do you need an account

No: the server works without sign-in

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.

How to connect

How to connect StudioMeyer-GEO to Claude

The server address to paste into Claude settings:

https://studiomeyer-geo--cod-gb2l.run.tools

  1. Open Claude (claude.ai or the desktop app).
  2. Go to Settings → Connectors.
  3. Click Add custom connector.
  4. Paste the server address copied below into Remote MCP server URL and click Add.
  5. In a chat, click + → Connectors and switch the new connector on.

Custom connectors are available on Free, Pro, Max, Team and Enterprise plans (Free is limited to one). On Team and Enterprise an organization Owner adds the connector first under Organization settings → Connectors.

Authorization

After you click Add, a sign-in window for the service opens. Sign in with your own account and approve access. Claude never sees your password.

How to connect StudioMeyer-GEO to ChatGPT

The server address to paste into ChatGPT settings:

https://studiomeyer-geo--cod-gb2l.run.tools

  1. Open ChatGPT in a browser (chatgpt.com). A Plus, Pro, Business, Enterprise or Edu plan is required.
  2. Turn on developer mode once: Settings → Apps → Advanced settings → Developer mode.
  3. Open Settings → Connectors and click Create.
  4. Fill in the form: Name (anything), Description (one line about what the service does), MCP server URL (copy it below).
  5. Under Authentication choose OAuth if the service requires sign-in, otherwise None. Click Create.
  6. In a new chat open + → Apps/Connectors and enable the connector.

OpenAI has renamed this section before (Connectors → Apps/Plugins). If the label differs, search settings for "developer mode". On Business/Enterprise workspaces an admin must allow custom connectors first.

Authorization

On first use ChatGPT opens the service's sign-in window. Sign in and approve access.

How to connect StudioMeyer-GEO to Cursor

The server address to paste into Cursor settings:

https://studiomeyer-geo--cod-gb2l.run.tools

Fastest: click Open in Cursor below and confirm the prompt.

Manually:

  1. In Cursor open Settings → Cursor Settings → MCP and click Add new global MCP server.
  2. Paste the JSON copied below into ~/.cursor/mcp.json (per project: .cursor/mcp.json in the repo root).
  3. Save the file. The server appears in the MCP list; authorize it there if asked.

Authorization

If the service needs sign-in, an authorize button appears next to the server in the MCP list.

Server tool list (24)

Raw names from tools/list. Only developers need these.

geo_checkRun 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_stackCheck 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_scoreCalculate GEO Score (0-100) from six weighted sub-scores. Useful for what-if scenarios with custom weights.
geo_platformsList 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_promptsPreview prompts that would be sent for a GEO check. No API calls. Useful for estimating cost + reviewing what will be tested.
geo_analyze_responseParse 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_recommendationsGenerate prioritized recommendations from sub-scores + discovery stack. No API calls — pure rule-based generation.
geo_robots_auditDeep-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_validateFetch /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_auditExtract 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_consistencyScan 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_freshnessCheck 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_simulateEstimate 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_generatorGenerate 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_sourcesAnalyze citation signals: outbound authority links, statistics, sameAs profiles. Higher citability = more AI citations. No API keys needed.
geo_content_auditDeep 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_qualityStatic 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_brandsList, 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_compareSide-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_checkRun 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_historyView past GEO check results for a brand. Returns score history with timestamps. Requires Supabase (Pro tier).
geo_trendsCalculate GEO score trends over time. Shows delta, direction (improving/declining/stable), min/max/avg. Requires Supabase (Pro tier).
geo_scheduleSet up scheduled GEO checks for a brand. Checks run automatically and alert on score drops. Requires Supabase (Pro tier).
geo_alertsView alerts (score drops, new issues, resolved issues) for a brand. Requires Supabase (Pro tier).