The official remote MCP server for GEOly — AI brand visibility (GEO) for your agent. GEOly tracks how brands are mentioned and cited across AI engines (ChatGPT, Perplexity, Google AI Mode, Google AI…
geoly-mcp is an MCP project maintained in the geoly-ai/geoly-mcp repository. The maintainer describes its purpose as “The official remote MCP server for GEOly — AI brand visibility (GEO) for your agent. GEOly tracks how brands are mentioned and cited across AI…”. Read the project documentation for the complete scope.
The maintainer’s configuration uses https://app.geoly.ai/api/mcp. Check the project’s account and authentication instructions when adding the endpoint to your client.
Project documentation · Repository · Discovery listing. This profile records the public documentation checked on 2026-10-08.
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 |
|---|---|
| get_brand_overview | Headline KPIs: AIGVR score, mention/citation rates, per-platform stats — matches the in-app numbers |
| get_brand_citations_daily | Daily trend of AIGVR / mention rate / citation rate |
| query_analytics | Controlled aggregation (no SQL) over daily datasets — dimensions, metrics, filters, prompt-text subsets |
| resolve_my_brand_public | Bridge from your monitored brand to its public market-intelligence profile |
| get_prompt_list | Search/list monitored prompts with visibility stats |
| get_prompt_detail | One prompt in full: per-platform performance, AIGVR, Share of Model, competitor mentions |
| get_prompt_record_summaries | Latest monitoring record per platform for one prompt |
| list_prompt_records | Full execution history of one prompt over a time range, paginated — per-day trend work |
| get_prompt_record_detail | One monitored AI answer in full: text, citations, sentiment |
| get_prompt_citations | Citations for a prompt — raw or deduplicated URL list with share % |
| get_prompt_mention_rates | Per-prompt mention rate, ascending — blind-spot discovery |
| get_brand_search_queries | Query-fanout demand roots: the real web searches the AI ran while answering your prompts (ChatGPT, 90 days) |
| get_citation_overview | Citation domain distribution + ownership breakdown across the brand |
| get_domain_detail | One domain's citation profile: trend, pages, prompts, platforms, regions |
| get_page_detail | One page URL's citation detail: trend, prompt distribution, text snippets |
| get_url_reference_detail | A URL's references across citations and search sources |
| get_content_opportunities | Content-gap analysis: prompts where a domain has low or no citations |
| get_competitor_list | Tracked competitors for the brand |
| get_competitor_overview | Cross-prompt competitor comparison |
| get_competitor_cooccurrence | Brand + competitor co-occurrence, with optional answer text |
| get_competitor_polarity | AI Verdict: per-answer preference polarity vs each competitor (weLose / tie / weWin, net loss) |
| get_platform_matrix | Brand + competitors × platform matrix, or topics × platform |
| get_topic_analytics | Per-topic analysis: sentiment, competitors, response types, trends |
| get_sentiment_dashboard | Sentiment distribution, trends, platform comparison |
| get_risk_context_sources | AI Verdict: cited domains over-represented in negative / mixed answers, with lift (7-day window) |
| get_brand_mention_samples | Recent AI answers mentioning the brand: raw text + sentiment + context |
| get_audit_list | GEO site audits (AI-readiness diagnostics), paginated history |
| get_audit_detail | One audit in full: per-category scores, critical/warning/passed issues |
| get_ga4_traffic_data | GA4 integration: sessions, page views, distribution |
| get_ga4_page_data | GA4 page-level: views, sessions, bounce rate, traffic sources |
| search_public_entities | Free-text resolver: brand / category / topic / product name or domain → public IDs (products via include_products) |
| list_public_topics | Browse public topics, with status/search filters |
| list_public_locales | Valid {country, language} pairs for an entity |
| get_available_platforms | Which AI platforms have data for a scope, ordered by volume |
| get_public_topic_overview | Overview of one public topic |
| get_public_topic_brand_leaderboard | Brand leaderboard ranked by Share of Mention |
| get_public_topic_som_trend | Daily Share-of-Mention trend |
| get_public_topic_prompt_matrix | Prompt × brand heatmap (per-prompt SoM %) |
| list_public_topic_prompts | Every prompt under a topic, with leader brand & share |
| get_public_topic_prompt_detail | One prompt: per-brand breakdown, recent records, top citation domains |
| get_public_topic_record_detail | One public AI answer: snippeted text, citations, brands mentioned |
| get_public_topic_citation_domains | Citation-domain leaderboard for the topic |
| get_public_topic_commerce | Commerce aggregate: activation rate, price stats, retail channels |
| get_topic_competition_difficulty | AI-visibility difficulty 0–100, like SEO keyword difficulty |
| get_public_brand | One public brand across topics, faceted: visibility, footprint, competitors, citations, ranking |
| get_public_brand_rank_citation | Google AI Overview rankings × AI citations: coverage, four search-counting quadrants, displacers, and paginated per-search detail |
| get_public_brand_perception | AI perception profile: canonical aspects + polarity + evidence |
| get_public_brand_perception_aspect_mentions | Drill-down: source mentions behind one perception aspect |
| compare_public_brands | Side-by-side comparison of 2–4 brands on one facet |
| get_public_category | One product-space category, faceted: leaderboard, SoM trend, topics, citation domains |
| get_category_whitespace | Opportunity map: strengths (covered / leading / close / defend) vs opportunities (prioritize / gap / watch) |
| get_category_brand_momentum | Period-over-period Share-of-Mention change: risers vs fallers |
| get_public_search_queries | AI-search demand for a product space: queries, themes, brand landscape, demand territories |
| get_public_search_query_detail | Drill-down on one query or theme: brands, prompts, top sources |
| list_public_shopping_boards | The cross-category AI shelf leaderboard: hot / climbers / entrants with week-over-week rank moves |
| get_public_shopping_product_detail | One product's full AI analysis: shelves, weekly trend, rivals, channels |
| list_public_shopping_products | Shopping overview for a product-space slice: products, channels, price bands |
| get_public_shopping_card_detail | One product card preview: evidence, topics, prompts, retail offers |
| get_public_sources_overview | Most-cited source domains across all public topics, each with its AI DA score |
| get_public_source_domain_detail | One citation source domain: coverage, co-occurring brands, optional full AI DA scorecard |
| get_public_source_brand_conduit | The topics where one source domain funnels AI attention toward one brand |
| create_prompt | Create a new monitoring prompt |
| create_topic | Create a prompt topic |
| create_competitor | Add a competitor to track |
| trigger_prompt | Run monitoring for a prompt now (consumes credits) |
| get_agent_ready_scans | Agent Readiness scan history for the signed-in user |
| get_agent_ready_scan_detail | Full Agent Readiness scan result by ID |
| list_organizations | Workspaces the connection can access (multi-workspace mode) |
| list_brands | Brands in the workspace (multi-brand mode) |
| get_current_date | Server time, for date-range validation |
{
"mcpServers": {
"geoly": {
"url": "https://app.geoly.ai/api/mcp"
}
}
}From the project documentation. Replace placeholders and example paths before connecting.
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