maps-geo MCP Server
AI visibility monitoring with 25 MCP tools + 5 expert workflows. Check how 8 LLM platforms (ChatGPT, Gemini, Perplexity, Claude, Grok, DeepSeek, Meta AI, Copilot) see your brand. Free tier: 20 tools without API keys. Pro: history, trends, alerts. Hosted MCP at geo.studiomeyer.io
Discovered via github-topic:mcp-server and last synced 3mo ago.
1. Install the package
npx mcp-remote https://geo.studiomeyer.io/mcp
2. Add to claude_desktop_config.json
{
"mcpServers": {
"studiomeyer-geo": {
"command": "npx",
"args": [
"studiomeyer-geo"
]
}
}
}Config file location: ~/Library/Application Support/Claude/claude_desktop_config.json (macOS) / %APPDATA%\Claude\claude_desktop_config.json (Windows)
llms.txt + agents.json + robots.txt + JSON-LD + sitemap + FAQ schema
Pure scoring function from raw data
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Deep robots.txt analysis with 14-AI-bot matrix
Parse a single LLM response for brand mentions. Optional hallucination guard (`verifyUrls`, `extractClaims`, `claimsReference`) cross-checks LLM-cited URLs against the real web and tags numeric claims as verified / refuted / unverified.
Scan for brand name variants. Masks emails, URLs, and bare brand-domain refs before matching, so `[email protected]` is not counted as a variant. Fragmented entities = 2.8x fewer AI citations.
Bulk GEO check across all tracked brands
LLM platform readiness check (8 platforms)
Score-drop / new issues / resolved alerts
**8**
Preview prompts without making API calls
Estimate GEO score without API keys (~30s, free)
Generate actionable recommendations from scores
Citability score: authority links, stats, sameAs, quotes
Score trends: delta, direction, min/max/avg
Price
Description
Page-type-aware deep content audit. Detects homepage / blog post / product / local business / about / profile / service / category / contact via JSON-LD `@type` (with URL-pattern fallback) and applies a tailored weighting profile per type. Based on KDD 2024 GEO paper.
Automated checks (daily/weekly/monthly)
Validate llms.txt against llmstxt.org spec with link checking
Use Case
Extract and audit JSON-LD structured data
Side-by-side GEO comparison of two brands
Ahrefs Brand Radar
Generate missing JSON-LD blocks ready to paste
Past check results with score progression
Multi-brand management (list/add/remove/dashboard)
**StudioMeyer GEO**
Full GEO check pipeline across 8 LLM platforms. Optional `samples` (N>1) runs each prompt N times and collapses the draws into one statistically-defensible result + a reproducibility summary (a single LLM query is one stochastic draw, not a measurement).
Sitemap-first freshness audit. Reads robots.txt, walks sitemap_index, scores top-N URLs by lastmod + Last-Modified + og:modified_time + schema dateModified. Hardcoded i18n paths only as last-resort fallback.
Static crawler-readiness audit (no headless browser). Text-to-HTML ratio, visible-text length, JS-required markers (DE+EN), `<noscript>` fallback, meta refresh, canonical mismatch, redirect chain depth via HEAD probe. Score 0..100 + issues.
**AI-crawler access-log analysis.** Paste raw nginx/apache logs — reports which AI bots (GPTBot, OAI-SearchBot, ClaudeBot, PerplexityBot, Google-Extended, Bytespider, CCBot, …) fetched which pages, and crucially flags BLOCKED AI requests (401/403/429/5xx). The upstream check: if the bots that feed AI answers can't fetch your pages, no on-page work will ever get you cited.
Interactive visibility dashboard (MCP Apps): score wheel with confidence range, 8-LLM heatmap, citation drift, conversation sankey, recommendations. Renders existing check data.
**Citation-source provenance.** Aggregates the URLs the 8 LLMs actually cite about your brand into a classified breakdown (owned / Reddit / YouTube / Wikipedia / social / review sites / news / competitor / other) with an owned-vs-third-party split. ~97% of AI citations come from non-Tier-1 domains — this shows where to invest.
**Prompt-level competitor gap.** Finds the exact prompts where the LLMs name a competitor but not you — the conversations you're losing — plus per-competitor standings (who beats you in the most queries vs winnable head-to-heads).
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