Genezio MCP Tools: Full Reference of Tools

The Genezio MCP server has 153 tools and 2 prompts. 112 tools read data and need the mcp:read scope. 41 tools change data and need the mcp:write scope. An AI assistant selects the tools by itself, thus you do not call them by name. Ask a question in your own words, and the assistant calls the tools that answer it. A tool shows only the brands that your Genezio user can open. A client with only the mcp:read scope does not see the write tools. Refer to Authentication and scopes.

Prompts

A prompt is a ready workflow. In most clients, you start it with a slash command, for example /genezio_exec_brief.

Prompt	Arguments	What it does
`genezio_exec_brief`	`brand`, `focus`, `window_hours`	Single safe executive MCP brief. One-tool diagnostics for a brand with evidence and deterministic next-step call.
`genezio_build_business_goal`	`brand_id`, `goal`	Build one Business Scorecard goal for a brand, in a conversation with the agent that writes one. The agent settles the number, reads the real data, and saves the card.

Business Scorecard

Tool	Scope	What it does
`archive_scorecard_goal`	write	Take one goal off the board.
`build_scorecard_goal`	write	Make a goal of the Business Scorecard of a brand, in a conversation with the agent that builds one.
`get_scorecard_authoring_guide`	read	The rules that a Business Scorecard controller must keep, the reads of the API that it can call, and the contract of each view type that the board draws.
`get_scorecard_goal`	read	One goal of the Business Scorecard, with its datapoints and the history of its runs.
`list_archived_scorecard_goals`	read	The goals of the Business Scorecard of one brand that a person archived, last archived first.
`list_scorecard_goals`	read	The goals of the Business Scorecard of one brand, each with the datapoints of its last 90 days.
`probe_scorecard_data`	write	Run a short Python script against the real data of one brand, in a sandbox, and read what it printed.
`restore_scorecard_goal`	write	Put an archived goal back on the board.
`revise_scorecard_goal`	write	Write a new version of the controller of a goal that exists, with the sentences that moved with it.
`run_scorecard_goal`	write	Compute the last date again for one goal, in the same way as the night does.
`update_scorecard_goal`	write	Change the title, the category, or the dimensions of one goal.

CDN logs

Tool	Scope	What it does
`analyze_cdn_vs_citations`	read	Compare pages public-LLM crawlers fetched (from a CDN log) against pages cited in the brand’s simulated scenarios, matched by URL.
`cluster_cdn_logs_by_keywords`	write	Cluster a brand’s CDN log of public-LLM crawler traffic into keyword-defined buckets and get back per-bucket traffic volumes.
`get_cdn_crawler_breakdown`	read	Per-crawler traffic totals for one CDN log file: row counts and occurrence sums for each AI-assistant crawler (ChatGPT, Claude, Perplexity, Google, Bing, etc.), sorted by volume.
`get_saved_cdn_log_clusters`	read	Fetch ONE named clustering snapshot for a brand+period.
`list_cdn_log_clusterings`	read	List every named clustering snapshot saved for a brand+period.
`list_cdn_log_inventory`	read	Catalog of CDN log files available for a brand in S3: period folders, CSV filenames, file sizes, and saved clustering counts.
`list_cdn_log_paths`	read	Return every unique URL path that public-LLM crawlers requested from the brand during the given period.

E-commerce audit

Tool	Scope	What it does
`get_competitor_ucp_readiness`	read	Get latest crawled UCP readiness scores for tracked competitors.
`get_ecommerce_audit`	read	Get the latest UCP readiness audit for a brand, including rule results.
`get_ecommerce_audit_history`	read	Get UCP readiness score history for drift tracking.
`run_ecommerce_audit`	write	Queue a UCP readiness audit for a brand and its tracked competitors.

Shopping and products

Tool	Scope	What it does
`get_brand_product`	read	Catalog details for a single product (title, category, line, manufacturer, label, image).
`get_conversation_shopping_percent`	read	Percentage of conversations that include a shopping carousel for a brand, optionally filtered by status, date range, topic, and model.
`get_merchant`	read	Merchant details plus products this merchant offered in shopping conversations.
`get_merchant_conversations`	read	The distinct shopping conversations in which a merchant offered a product, newest first.
`get_product_co_mentions`	read	Paginated products co-mentioned with a focus product in the same shopping carousels, ordered by the chosen metric (visibility or recommendation) in the latest period, descending.
`get_product_conversations`	read	The conversations a product appeared in.
`get_product_ownership_totals`	read	Distinct products with at least one appearance in the window, split into our brand products, competitor products, and the grand total.
`get_product_perception`	read	How the AI perceives a product, split into three sentiment columns (positive/negative/neutral), each ordered by how often the perception was repeated (occurrence_count desc) and paginated independently.
`get_product_query_conversations`	read	The distinct shopping conversations in which a product-search query was run, newest first.
`get_product_query_products`	read	Products returned for a product-search query.
`get_product_retailer_offers`	read	Paginated product offers for one retailer at one product level.
`get_product_series`	read	Per-period visibility and recommendation (each with share-of-voice) for one product and its co-mentioned products, for the product drawer chart.
`get_product_sku_retailers`	read	Paginated retailers for one level of a product: a specific SKU when sku_id is given, otherwise the general (variant-less) level.
`get_product_sku_visibility`	read	A single product’s aggregate shopping visibility plus a per-SKU (variant) breakdown over the range.
`get_product_sources`	read	Paginated citation sources (URL, answer engine, ownership type, sentiment, occurrences, percent_cited) from the conversations a product appeared in, with first-party stats.
`get_product_visibility_metrics`	read	Per-product shopping time series for a brand.
`get_retailer_share`	read	Merchants ranked by their share of the brand’s shopping conversations.
`list_actual_competitor_products`	read	Actual competitors for a brand that have at least one product appearing in the filtered shopping conversations, each with a product_count (distinct products that appeared in the topic/model/date window).
`list_brand_product_categories`	read	Distinct product categories for a brand, sorted alphabetically.
`list_brand_product_queries`	read	Paginated LLM-generated product-search queries for a brand (deduplicated per brand), sorted by occurrence count descending.
`list_brand_product_query_fanouts`	read	Paginated query fanouts from conversations where brand products appeared (via product_appearances).
`list_brand_products`	read	Paginated list of the brand’s products that appeared in shopping conversations matching the filters, sorted by visibility descending.
`rank_brand_products`	read	Paginated ranking of the brand’s products by a single metric, for the top/worst products widget.

Brand groups

Tool	Scope	What it does
`get_alias_group_by_id`	read	Fetch detailed configuration and membership for a specific alias group by its ID.
`list_all_alias_groups`	read	Retrieve configured brand groups for a specific brand.

Search Console and integrations

Tool	Scope	What it does
`get_search_console_queries`	read	Read the top Google Search Console queries of the property that a brand reads, with the clicks, the impressions, the CTR, and the position of each one.
`list_brand_integrations`	read	List the external providers of a brand and whether each one is connected: Google Search Console and Google Analytics 4.
`list_search_console_properties`	read	List the Google Search Console properties of the account that a brand connected, and name the one that the brand reads.
`select_search_console_property`	write	Store the Google Search Console property that a brand reads.

Tracked URLs

Tool	Scope	What it does
`assign_tracked_url_group`	write	Move tracked URLs into one custom group.
`create_tracked_url_group`	write	Create a custom group that collects the tracked URLs of a brand.
`delete_tracked_url_group`	write	Delete a custom group of tracked URLs.
`list_brand_tracked_urls`	read	Fetch a paginated list of all URLs being actively tracked for brand citations, with optional filtering by date, topic, model, and search term.
`list_tracked_url_groups`	read	List the custom groups that collect the tracked URLs of a brand, each one with the number of its members.
`update_tracked_url_group`	write	Rename a custom group of tracked URLs.

Articles and briefs

Tool	Scope	What it does
`get_article_details`	read	Fetch the full content and metadata of a specific article by its ID.
`get_brief_details`	read	Fetch details and content of a specific brief by ID.
`update_article_schema_markup`	write	Replace the schema.org markup (JSON-LD) of an article with a full edited JSON-LD object.

Competitors and SWOT

Tool	Scope	What it does
`create_competitor`	write	Create a new competitor for a brand.
`delete_competitor`	write	Soft-delete a competitor by ID.
`demote_competitor`	write	Demote an actual competitor back to suggested.
`get_brand_competitor_presence_by_model`	read	Presence or recommendation percentages per AI model for the brand and its competitors.
`get_competitor_details`	read	Retrieve detailed information about a specific competitor by its ID.
`get_competitor_swot_detail`	read	Get full detail for a single SWOT entry, including paginated child statements.
`get_competitor_swot_overview`	read	Get the AI-generated head-to-head SWOT overview comparing the brand against a specific competitor.
`get_competitor_swots`	read	Get clustered SWOT statements for a brand, grouped by competitor.
`list_competitors_by_brand`	read	List confirmed competitor names and websites for a brand.
`update_competitor`	write	Update competitor details by competitor ID.

Perceptions, sentiment and fact check

Tool	Scope	What it does
`continue_perception_monitoring`	read	Read the next page of a run that start_perception_monitoring began.
`get_brand_perception_confirmation_analytics`	read	Confirmed, contradicted, and unconfirmed perception occurrence counts for pie charts (weighted by cluster size).
`get_brand_perception_summaries`	read	Get cached or freshly generated perception summaries for a brand.
`get_brand_statement_sentiment_analytics`	read	Get sentiment analytics for a brand’s statements over time, including positive/neutral/negative percentages and latest snapshot.
`get_statement_details`	read	Retrieve detailed information about a specific statement by its ID, including all its mentions across different conversations.
`get_topic_fact_check_stats`	read	Retrieve fact-check pass/fail counts for fact_checker topics under a brand, grouped by topic and scenario.
`get_topic_fact_check_stats_by_model`	read	Retrieve claimed-rate percentages grouped by LLM model for fact_checker topics.
`get_topic_fact_check_stats_over_time`	read	Retrieve claimed vs not-claimed counts over time for fact_checker topics.
`get_topic_sentiment_stats`	read	Retrieve sentiment statistics (positive, negative, neutral) for introspector topics under a specific brand.
`list_brand_perceptions`	read	Fetch a paginated list of brand perceptions for a specific brand ID.
`list_citation_sources_by_statement`	read	Paginated citation sources linked to a specific statement ID via statement-source associations.
`list_monitored_perceptions`	read	List the perceptions that the brand monitored, from the last run to the oldest.
`list_statements_by_citation_domain`	read	Paginated statements linked to citation sources from a specific domain via statement-source associations.
`list_statements_by_citation_source`	read	Paginated statements linked to a specific citation source ID via statement-source associations.
`start_perception_monitoring`	read	Count how many answers of the models agree with a perception, and how many disagree.

Query fanouts

Tool	Scope	What it does
`get_fanout_by_id`	read	Metadata and total occurrence count for a query fanout by ID: keyword, llm_model, and replay_index.
`get_fanouts_by_citation`	read	Retrieve query fanouts extracted from a specific citation source (by ID or URL).
`get_fanouts_for_phrase`	read	Return a paginated list of full fanout queries linked to the exact given sub-query phrase.
`get_sub_query_fanouts_for_brand`	read	Return a paginated list of sub-query phrases for a brand.
`list_brand_query_fanouts`	read	Fetch a paginated list of query fanouts associated with a brand, with filters for date, topics, and models.
`list_citation_sources_by_fanout`	read	Paginated citation sources that contain a specific query fanout.
`list_conversations_by_fanout`	read	Paginated conversations where a query fanout was mentioned.

Citations

Tool	Scope	What it does
`get_brand_citations_analytics`	read	Aggregated citation analytics across a brand: domain ranking, occurrence trends over time for selected root_domains, period totals, and source-ownership distribution.
`get_citation_metrics_by_domain`	read	Citation occurrence counts for a single domain: total count, daily time series, breakdowns by topic, scenario, and LLM model, and how many citations name a channel or an author (channel_occurrences, author_occurrences).
`get_source_citation_insights`	read	Fetch qualitative and quantitative insights for a specific citation source ID.
`get_top_citation_sources`	read	Retrieve the most frequently cited sources for a brand, ordered by occurrence count.
`get_total_brand_citations`	read	Fetch the total number of citations/references identified for a specific brand, with optional filters for topics, date range, and models.
`list_brand_citation_channels_and_authors`	read	Which communities and people the answer engines cite for a brand.
`list_brand_citation_domains`	read	Retrieve citation sources grouped by domain, with total_occurrences and cited_occurrences per domain and per source.
`list_brand_citation_sources`	read	Fetch a detailed, paginated list of all citation sources for a brand, including URL, sentiment, total_occurrences, and cited_occurrences (sources with matched_texts in the LLM response).
`list_domain_citation_channels_and_authors`	read	The channels or the authors behind the cited URLs of one domain, most cited first, with citation counts.
`list_recent_conversations_by_citation`	read	Fetch the most recent conversation for a specific normalized URL citation, with optional date, topic, and model filters.
`list_scenario_sources`	read	List all citation sources (websites/platforms) identified in conversations for a specific scenario.
`list_source_url_occurrences`	read	Retrieve a list of citation URLs with total_occurrences and cited_occurrences across all conversations for a brand.

Insights

Tool	Scope	What it does
`get_insight_details`	read	Fetch the full content and metadata of a specific data-driven insight by its ID.
`list_brand_insights`	read	Retrieve all insights generated for a specific brand ID, with optional date range and frequency filters.
`list_insights_by_status`	read	Fetch insights filtered by status (todo, done, declined), optionally scoped to a specific brand ID.

Conversations

Tool	Scope	What it does
`get_conversation_aggregates`	read	Fetch aggregate counts of conversations for a brand, optionally filtered by status, date range, topic, and model.
`get_conversation_details`	read	Fetch a complete log of a specific conversation by its ID, including AI messages, brand rankings, and citation sources.
`get_conversation_progress`	read	Get conversation status counts for a brand (total, success, in_progress, error).
`list_recent_conversations_for_brand`	read	Fetch the most recent conversations (max 5) for a specific brand.
`list_scenario_conversations`	read	Fetch detailed conversation logs and metadata for a specific scenario.
`list_topic_conversations`	read	Paginated topic conversations: filter by date, llm_models (Answer Engine ids as stored, e.g.
`search_conversations`	read	Find what the answers of the models say about a subject, such as ‘Vercel pricing’ or ‘credit for young people’.

Scenarios

Tool	Scope	What it does
`create_scenario`	write	Create a single scenario for a topic.
`delete_scenario`	write	Delete a scenario by ID.
`get_scenario_details`	read	Retrieve detailed information about a specific scenario by its ID.
`get_scenario_performance_metrics`	read	Fetch quantitative metrics (mentions/recommendations) for a specific scenario over time.
`list_all_scenarios_by_brand`	read	Fetch all scenarios for a specific brand ID.
`list_recently_deleted_scenarios_by_topic`	read	Fetch scenarios soft-deleted within the last N days for a topic.
`list_scenarios_for_topic`	read	Retrieve all scenarios associated with a given topic ID.
`restore_scenario`	write	Restore a soft-deleted scenario by ID.
`start_scenario`	write	Start scenario runs for a specific scenario ID.
`update_scenario`	write	Update a single scenario by ID.

Topics and tags

Tool	Scope	What it does
`change_topics_status`	write	Bulk update status for multiple topics.
`create_topic`	write	Create a new topic for a brand.
`create_topic_custom_tag`	write	Create a new custom tag for organizing topics within a brand.
`delete_topic`	write	Soft-delete a topic by ID.
`delete_topic_custom_tag`	write	Soft-delete a custom topic tag for a brand and remove it from all topics.
`get_topic_details`	read	Fetch detailed information about a specific topic by its ID.
`get_topic_performance_metrics`	read	Top competitors by visibility or recommendation (dashboard Top 10 widget).
`list_recently_deleted_topics_by_brand`	read	Fetch topics soft-deleted within the last N days for a brand, including their scenarios and custom tags.
`list_topic_custom_tags`	read	List brand-scoped custom topic tag definitions (names and ids) for filtering and assignment.
`list_topics_by_brand`	read	List all topics for a brand, including nested scenarios and brand-scoped custom_tags (tag ids and names).
`replace_topic_custom_tags`	write	Replace the full set of custom tags assigned to a topic (body: tag_ids).
`restore_topic`	write	Restore a soft-deleted topic by ID.
`start_topics`	write	Start one or more topics for execution.
`update_topic`	write	Update topic metadata by topic ID.
`update_topic_custom_tag`	write	Update a custom topic tag of a brand: its name, its color, or the personas of a master filter.

Personas

Tool	Scope	What it does
`create_persona`	write	Create a new persona for a brand.
`delete_persona`	write	Delete an existing persona by ID.
`get_persona_details`	read	Fetch full details for a specific persona, including demographics, interests, and behavior profile.
`list_personas`	read	Retrieve the research personas of one brand.
`update_persona`	write	Update an existing persona by ID.

Brands and visibility

Tool	Scope	What it does
`create_brand`	write	Create a new brand in a specific account.
`delete_brand`	write	Soft-delete a brand by ID.
`get_brand_overview`	read	Read-only: get a brand by ID with nested competitors, topics, and scenarios in one response.
`get_brand_visibility_metrics`	read	Brand visibility/recommendation time series.
`list_all_available_brands`	read	Fetch a paginated list of all brands the user has access to with optional filtering.
`set_brand_llm_models`	write	Set which LLM/AI models (answer engines) a brand monitors.
`update_brand_websites`	write	Replace or toggle websites for a specific brand.

Web research

Tool	Scope	What it does
`crawl_website`	read	Crawls a single given URL using Firecrawl and returns the extracted content.
`google_search_ui`	read	Searches Google using Firecrawl and returns a list of search results (URLs, titles, and descriptions).

​Prompts

​Business Scorecard

​CDN logs

​E-commerce audit

​Shopping and products

​Brand groups

​Search Console and integrations

​Tracked URLs

​Articles and briefs

​Competitors and SWOT

​Perceptions, sentiment and fact check

​Query fanouts

​Citations

​Insights

​Conversations

​Scenarios

​Topics and tags

​Personas

​Brands and visibility

​Web research