Gainsight Customer Communities
Ask AI for community insights
- Category
- Customer Support
- Primary Subcategory
- Customer Success Platforms
Integration details
Description
The Gainsight Community MCP connects your Customer Community to ChatGPT. Surface unanswered questions, identify content gaps, and pull engagement trends through natural language. Review moderation queues, browse leaderboards, and audit community structure without waiting on a custom export. Purpose-built for community managers and CS teams managing Gainsight-powered communities at scale.
- Integration type
- Plugin
- Verification status
- Not applicable
- Platform
- ChatGPT
- Primary Subcategory
- Customer Success Platforms
- Secondary Subcategories
- None listed
- Brand
- Gainsight
- Access
- Account required
- First tracked
- 2026-08-27
- Tool count
- 13
- Geography
- US
The Primary Subcategory used for this profile’s headline score.
Other Subcategories where the Integration is listed.
ChatGPT Plugin Discovery Score
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What discovery looks like

Competing in ChatGPT Customer Success Platforms
View Category13 tools agents can invoke
Inspect community structure and content layout. Use 'get_category_tree' for a full nested category hierarchy, 'list_categories' to page through all categories, 'get_category' for a single category's details (requires category_id), 'list_content_in_category' to list topics within a category (requires category_id; filter by content_type), 'get_visible_topic_counts' for topic counts per visible section (supports modules and top_level_section_ids filters), or 'list_recent_topics' for the latest topics across the community. Requires mcp:admin scope.
Inspect community moderation queues. Use 'list_trashed_content' to page through deleted/trashed posts, or 'list_labeled_content' to list posts with specific moderation labels (filter by label name via moderation_labels). Requires mcp:admin scope.
Community recognition and gamification data. Use 'list_leaderboard' for top users by points, 'get_user_leaderboard_position' for a specific user's rank (requires user_id), 'list_badges' to enumerate available badges, or 'get_user_points_history' for a user's points timeline (requires user_id; supports period, from_date, to_date). Requires mcp:admin scope.
Look up community user details. Use 'get_user_by_id' to fetch a full user profile by user_id, 'get_user_by_field' to find a user by a specific profile field (e.g. field='email', value='[email protected]'), or 'list_user_roles' to enumerate all roles assigned to a user (requires user_id). Requires mcp:admin scope.
The ONLY tool for audience analytics, website traffic, pageviews, visitors, visitor segmentation, and visitor profiles. Admin-only tool. Requires authenticated access with administrator or community manager role. Use for ANY question about 'how many people visited', 'pageviews', 'traffic trends', 'unique visitors', 'registered vs guest visitors', 'audience size', 'daily traffic', 'visitor breakdown by section', 'who is visiting', 'audience segments', 'contributors vs viewers vs reactors', 'homepage traffic', 'visitor profiles', 'who visited and what did they do', or 'visitor engagement'. Answers: 'how many pageviews last month', 'what is the daily traffic trend', 'how many unique visitors this week', 'what percentage of visitors are registered', 'break down traffic by section', 'break down pageviews by content type', 'how many contributors vs viewers', 'show me audience segments', 'traffic to articles vs questions', 'homepage pageviews', 'show me visitor profiles for last quarter', 'which visitors created the most topics', 'who visited and earned the most points'. Use the 'view' parameter: 'summary' (default) for aggregate KPIs (total pageviews, unique visitors, registered/guest split, daily averages) with optional period-over-period comparison, 'daily_trends' for day-by-day pageview and visitor counts over time, 'pageviews_breakdown' for pageviews broken down by a chosen dimension (section, entity_type, content_type, or category_id), 'user_segments' for classifying active registered users into contributor/reactor/viewer tiers based on their activity, 'visitor_profiles' for registered visitor profiles with period-specific engagement stats (topics, replies, likes, logins) and gamification points — one row per visitor, sorted by activity. Do NOT use analytics_community_health for detailed audience or traffic questions — it only provides a high-level traffic summary. Do NOT use analytics_user_trends for visitor or pageview data — it handles user rankings and registration, not traffic. Do NOT use analytics_individual_user_profile for bulk visitor profiles — use visitor_profiles view instead. Do NOT use search tools for traffic or audience questions. Response notes: 'unique_visitors' = unique visitors by tracking cookie — different devices count as different visitors. 'registered_visitors' = unique registered users by user_id — different devices count as one user. 'guest_visitors' = visitors without a user account, cookie-based. 'pageviews' = total pages loaded or reloaded, not unique. 'registered_pageviews' / 'guest_pageviews' = pageviews split by visitor type. Guest pageviews are retroactively attributed to registered users when they later log in (matched by cookie). User segments: 'contributors' = users who created a topic or reply. 'reactors' = users who liked or voted but did not post. 'viewers' = users who only logged in. These are mutually exclusive tiers — a contributor is not also counted as a reactor.
Cross-domain community health snapshot with period-over-period comparison. Admin-only tool. Requires authenticated access with administrator or community manager role. Returns a HIGH-LEVEL summary across 6 domains: users (total, new, active), content (topics created, replies), traffic (pageviews, unique visitors), Q&A (answer rate), support deflection, and gamification (badges, points). Use ONLY for broad 'how is the community doing' questions or when the user wants a single combined overview across multiple domains. For DETAILED analysis of any single domain, use the specialized tool instead: analytics_content_performance for detailed Q&A metrics/content gaps/response times, analytics_user_trends for user rankings/registration/churn, analytics_audience for detailed traffic/visitor analysis, analytics_individual_user_profile for a specific person. This tool gives breadth, the others give depth. Response notes: 'topic' = original thread (question, article, idea, conversation/discussion, product_update). 'reply' = response to a topic or another reply (threaded). 'post' = topic + reply combined. 'content_type' values: question, article, idea, conversation (also called discussion), product_update. All metrics include both current and previous period values. '_current' suffix = current period value. '_previous' suffix = previous period value. Previous period = same number of days immediately before the selected period. 'total_registered' = lifetime registered users excluding banned/deleted/guest/super-admin/not-activated/requires-approval. 'active_users' = users with any activity (post, reply, like, login) in the period. 'active_contributors' = users who posted, replied, liked, or voted (excludes login-only). 'avg_dau' = average daily active users. 'new_topics' = original threads created, not replies. For articles and product_updates, date filtering uses published_at (when content went live). Unpublished drafts are excluded. 'new_replies' = responses created. 'new_questions' / 'new_questions_answered' = questions created and answered in the period. 'answered_pct' = all-time % of questions with a best answer. 'page_views' = total pages loaded or reloaded. 'badges_earned' = badges awarded in the period. 'rank_promotions' = users promoted to a higher rank. 'points_awarded' = gamification points given in the period. 'primary_role_name' is a system ID — present 'primary_role_label' for display.
The ONLY tool for analysing topics, replies, and content performance across the community. Admin-only tool. Requires authenticated access with administrator or community manager role. Also tracks likes trends — how many likes were added in a period and which topics received the most likes. Use for ANY question about content metrics, top performing topics, content distribution, content gaps, response times, helpfulness scores, Q&A performance, content subscriptions, content creation patterns, or likes trends. Answers: 'what are the most viewed topics', 'how is content distributed across categories', 'which questions are unanswered', 'what is the average response time', 'show me content gaps', 'top topics by replies', 'helpfulness scores by category', 'Q&A answer rate', 'how many questions were answered', 'average time to answer', 'who is asking and answering questions by role', 'which content gets the most subscriptions', 'content creation by role', 'what did moderators post', 'how many likes were added last month', 'most liked topics'. Can filter by content type, category, group, group type, product area, tags, moderator tags, and moderation labels. For Q&A questions (answer rate, unanswered questions, response time) — ALWAYS use this tool, not analytics_community_health. For 'which content gets subscriptions' — use this tool. For 'which users subscribed to what' — use analytics_user_trends instead. For content performance data (views, replies, likes, helpfulness, response times) — use this tool, not search_unified (it searches content text but cannot return metrics). Do NOT use analytics_product_ideas for general content questions — that tool is ONLY for ideas and feature requests with vote counts. Response notes: 'topic' = original thread (question, article, idea, conversation/discussion, product_update). 'reply' = response to a topic. 'post' = topic + reply combined. 'content_type' values: question, article, idea, conversation, product_update. Date filtering for articles and product_updates uses published_at (when the content went live) instead of created_at; unpublished drafts are excluded. Questions, ideas, and conversations continue to use created_at. Reply date filters always use the reply's created_at. 'total_replies_created' = actual reply count, not topics-with-replies. 'unanswered_rate' = % of questions without a best answer. 'avg_first_reply_time_minutes' = average minutes from topic creation to first reply. 'helpful_votes_percentage' = % positive helpfulness votes (0-100). NULL = no votes. 0 = all votes were not-helpful. 'like_count' on a topic = likes on the topic itself, not its replies. 'subscription_count' on a topic = all-time subscriber count, not time-windowed. 'net_subscriptions' = subscribed minus unsubscribed in the period. 'answer_rate_pct' = questions_answered / questions_asked × 100. 'avg_answer_time_minutes' = average minutes from question creation to when the answer was marked as best. 'questions_answered' = questions with a best answer, not just any reply. 'unanswered' = questions with no best answer marked. 'gap_type' severity: unanswered = no best answer, zero_reply = no replies at all, high_view_low_reply = many views but few replies. 'primary_role_name' is a system ID — present 'primary_role_label' for display. 'moderator_tag_names', 'moderation_label_name', 'public_tag_names', 'product_area_names' are comma-separated when multiple values exist. qa_by_role returns two groups: 'askers' (who asks questions by role) and 'answerers' (who provides best answers by role). by_role 'role_type' = 'primary' for system roles, 'custom' for custom roles. response_time view returns avg_minutes = average first-reply time in minutes. sample_size = number of topics used in the calculation.
Deep-dive into ONE specific named community user. Admin-only tool. Requires authenticated access with administrator or community manager role. ONLY use when the question names or identifies a specific person (e.g. 'tell me about John Smith', 'show me Sarah's profile', 'what has jsmith posted'). Look up by name or email to view their full profile (identity, roles, rank, company, groups, badges, lifetime stats, subscriptions), recent activity feed, gamification history, content performance, or group membership timeline. Use the 'view' parameter to select: 'profile' (default) for full profile, 'activity' for recent actions in a time window, 'gamification' for badge/rank/points history, 'content' for topics, replies, and content performance metrics, 'groups' for group membership timeline including joins, leaves, and role changes. IMPORTANT: For questions about whether a user was active, how engaged they were, or any complete activity summary, call this tool TWICE — once with view='activity' (for posts, likes, logins) and once with view='gamification' (for points earned, badges, rank changes). Activity view does NOT include points data. Do NOT use this tool for ranking, comparing, or listing multiple users — use analytics_user_trends instead. Do NOT use this tool for 'who has the most points', 'top contributors', 'most active users' — those are ranking questions that belong to analytics_user_trends. Response notes: 'topic' = original thread (question, article, idea, conversation/discussion, product_update). 'reply' = response to a topic. 'post' = topic + reply combined. 'content_type' values: question, article, idea, conversation, product_update. Date filtering in the content view for articles and product_updates uses published_at (when the content went live) instead of created_at; unpublished drafts are excluded. Questions, ideas, and conversations continue to use created_at. Reply date filters always use the reply's created_at. 'primary_role_name' is a system ID like 'roles.member' — present 'primary_role_label' instead (e.g. 'Member'). 'custom_role_names' is comma-separated. 'solved_count' = replies accepted as best answer, not closed topics. 'likes_given_count' = likes this user gave to others. 'likes_received_count' = likes this user received from others. 'vote_count' = net idea votes (upvotes minus unvotes), only for ideas. 'helpful_votes_percentage' = % positive helpfulness votes (0-100). NULL = no votes cast. 0 = all votes were not-helpful. 'like_count' on a topic = likes on the topic itself, not its replies. 'idea_status_type' values: open, closed, delivered, null (no status set). Activity view 'activity_type' values: topic_created, reply_created, topic_liked, reply_liked, topic_voted, enduser_login, sso_login, role_change. 'trigger_activity' in points breakdown shows the earning action (e.g. 'Created.topic', 'Created.reply').
The ONLY tool that can list, rank, sort, or count ideas by votes, views, or replies. Admin-only tool. Requires authenticated access with administrator or community manager role. Also tracks voting trends — how many votes were added in a period and which ideas gained the most votes. Use for any question about ideas, feature requests, product feedback, or the idea pipeline. Answers: 'which ideas have the most votes', 'top voted ideas', 'how many ideas were delivered', 'what feature requests are open', 'show me delivered ideas', 'idea pipeline stats', 'ideas by product area', 'how many votes were added last month', 'voting trends', 'which ideas gained votes', 'what percentage of votes are on delivered ideas', 'votes on delivered ideas this quarter'. Can filter by idea status (open/closed/delivered), product area, category, and minimum votes. Can sort by votes, replies, views, likes, or recency. Supports period-over-period comparison. For idea voting data, rankings, or vote counts — use this tool, not search_unified or search_discussions (they search idea text but cannot sort or rank by votes). Response notes: 'idea' = a feature request or suggestion submitted by a community user, always content_type='idea'. 'vote_count' = net idea votes (upvotes minus unvotes/merges/resets) — can be zero or negative. 'idea_status_type' values: open, closed, delivered, or null (no status assigned). 'ideas_no_status' = ideas with no status set. ideas_delivered + ideas_open + ideas_closed + ideas_no_status = ideas_count. 'idea_status_changed_at' = when status was last changed, null if never changed. 'date_filter_by' controls which date is filtered: 'created' = idea creation date, 'status_changed' = when status last changed. Delivered view defaults to 'status_changed'. 'avg_votes_per_idea' includes ideas with zero votes. 'product_area_names' is comma-separated when an idea belongs to multiple product areas. 'primary_role_name' is a system ID — present 'primary_role_label' for display. 'votes_delivered' = total votes on delivered ideas. 'votes_open' = total votes on open ideas. 'pct_votes_delivered' = votes on delivered ideas as % of delivered + open votes (excludes closed).
The ONLY tool for ranking, comparing, or counting users across the community. Admin-only tool. Requires authenticated access with administrator or community manager role. Use for ANY question about 'who has the most', 'top users by', 'which users', 'how many users', 'user growth', or 'user trends'. Answers: 'who got the most points in Q1', 'top contributors this month', 'most active users', 'who has the most solved answers', 'how many users registered last week', 'which users churned', 'users by role', 'which users subscribed to topics/categories/groups'. Use the 'view' parameter: 'summary' (default) for aggregate counts with period-over-period comparison, 'leaderboard' for top users ranked by any metric (points, topics, replies, likes, solved answers, badges, votes), 'registration_trends' for signups over time, 'role_breakdown' for user counts per role with optional gamification stats, 'active_users' for users meeting activity thresholds (posts, replies, likes, logins), 'churned_users' for previously active users who dropped off, 'subscriptions' for which users subscribed or unsubscribed from topics/categories/groups. For 'which content gets subscriptions' — use analytics_content_performance instead (it ranks content by subscription count). Do NOT use analytics_individual_user_profile for ranking or comparing users — it only handles one named person at a time. Response notes: 'total_registered' = all valid users to date, excludes banned/deleted/guest/super-admin/not-activated/requires-approval. 'active_users' = users who performed any activity (post, reply, like, login) in the period. 'topics_created' = original threads created, not replies. 'replies_created' = responses to topics. 'likes_given' = likes this user gave to others. 'likes_received_count' = likes others gave to this user. 'solved_count' = replies accepted as best answer, not closed topics. 'total_points' = lifetime accumulated points. 'user_votes_count' = idea votes cast by this user. 'primary_role_name' is a system ID like 'roles.member' — present 'primary_role_label' for display. 'churned_users' = users whose last activity was in the queried period with no subsequent activity. Leaderboard without dates uses lifetime stats; with dates it calculates within that period.
Get search analytics data for the community. Provides insights into how users search: top queries, no-result searches, click-through rates, and more. Calls the syncsearch analytics API. Admin-only tool. Requires authenticated access with administrator or community manager role. Args: metric: Analytics metric. Valid values: top_searches, search_count, no_result_rate, click_through_rate, conversion_rate, frequent_searches_without_result, top_search_results, searches_without_clicks, no_click_rate, user_count, top_countries. Default: top_searches. date_from: Start date (YYYY-MM-DD, e.g. "2025-01-01"). date_to: End date (YYYY-MM-DD, e.g. "2025-12-31"). limit: Maximum results (default 10, max 100).
Find active community discussions on a topic. Returns questions and discussions with status, reply counts, and engagement metrics.
Search across all content sources via the Algolia unified index. Searches community posts, knowledge base articles, Zendesk tickets, Salesforce articles, Freshdesk articles, and Skilljar courses in one query.
How do I improve a ChatGPT Plugin's discoverability?
The levers are the listing surface agents actually read: names, descriptions, keywords, tool metadata, and registry health. Which lever matters depends on where discovery breaks, which is what continuous measurement shows.
What are Gainsight Customer Communities alternatives on ChatGPT?
As of 2026-08-27, Gainsight Customer Communities competes with Velaris Basic, Velaris Intelligence in ChatGPT Customer Success Platforms, ranked by public Discoverability Score.
Where is this profile measured?
This profile uses the geography attached to the latest public registry snapshot: US. Locale tags are intentionally omitted.