StudioMeyer GEO exposes AI visibility research and crawler-readiness checks through a hosted MCP endpoint with tool-specific access requirements.
StudioMeyer GEO exposes AI visibility research and crawler-readiness checks through a hosted MCP endpoint with tool-specific access requirements.
The service includes robots, llms.txt and JSON-LD inspection alongside brand-visibility workflows that query model platforms. Several structural checks work without an LLM API key; live model checks need the corresponding access. A generated visibility score is a product measurement, not a guaranteed search position.
The registry manifest documents Streamable HTTP. The README also supplies an mcp-remote bridge for local-process clients. Background check tools return a job identifier that must be polled for the final result. Account tiers and provider keys affect which operations are available.
Start with the site's robots file, canonical pages, sitemap and structured data, then compare any reported issue with the actual page. For model visibility, retain the prompts and sampled responses and repeat the measurement when assessing a change. A single stochastic response should not be treated as complete market coverage. Review a suggested schema or content change before publishing it.
Check the linked publisher documentation and your connected client's tool list. Names and availability can vary with the server version and account permissions.
| Tool | What it does |
|---|---|
| geo_check | 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 stoc |
| geo_discovery_stack | llms.txt + agents.json + robots.txt + JSON-LD + sitemap + FAQ schema |
| geo_calculate_score | Pure scoring function from raw data |
| geo_platforms | LLM platform readiness check (8 platforms) |
| geo_preview_prompts | Preview prompts without making API calls |
| geo_analyze_response | 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 / u |
| geo_recommendations | Generate actionable recommendations from scores |
| geo_robots_audit | Deep robots.txt analysis with 14-AI-bot matrix |
| geo_llms_txt_validate | Validate llms.txt against llmstxt.org spec with link checking |
| geo_json_ld_audit | Extract and audit JSON-LD structured data |
| geo_entity_consistency | Scan for brand name variants. Masks emails, URLs, and bare brand-domain refs before matching, so ahoi@example.com is not counted as a variant. Fragmented entities = 2.8x fewer AI citations. |
| geo_content_freshness | 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. |
| geo_simulate | Estimate GEO score without API keys (~30s, free) |
| geo_schema_generator | Generate missing JSON-LD blocks ready to paste |
| geo_content_audit | Audit content according to its page type. |
| geo_check_start | Start a background visibility check. |
| geo_check_result | Retrieve a background check result. |
{
"mcpServers": {
"studiomeyer-geo": {
"url": "https://geo.studiomeyer.io/mcp"
}
}
}An HTTP MCP client, with provider keys or service access for the selected live-check and account-tier workflows.
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