Pendo

Return the set of metadata that is available from the accounts table for each account. It is a set of . separated metadata field names to information about that field, including the type. Here is an example return value

{ "metadata.custom.ARR" : "float", "metadata.pendo.donotprocess" : "boolean" }

PERFORMANCE: This is a fast-running tool.

Retrieve account data and metadata OR just the counts of matching accounts by running aggregation queries directly against the account dataset. Every response entity will conceptually be an account of that subscription.

USE THIS TOOL FOR: Getting account information, metadata, and account counts with flexible filtering options.

PERFECT FOR QUERIES LIKE:

• "Get all accounts with their custom metadata fields"
• "Show me accounts from a specific segment"
• "How many accounts match certain criteria?" (set count=true)
• "Get account metadata like ARR, company size, or custom properties"

WHAT THIS TOOL RETURNS:

• Account data with selected metadata fields (without select passed in, no metadata fields are returned)
• Account counts when count=true is specified
• Results filtered by segments, specific account IDs, or other criteria

FILTERING OPTIONS:

• Filter by specific account ID
• Filter by account segments
• Filter by metadata value for a specific metadata group and field
• Select specific metadata fields to include

This tool executes aggregation queries directly and returns results immediately. For available metadata fields, use the accountMetadataSchema tool. Example usage of metadata fileds is select=["metadata.agent.is_paying","metadata.auto.lastvisit"].

PERFORMANCE: This is a fast-running tool.

Query aggregated activity metrics (events, minutes, unique visitors, unique accounts) for pages, features, track types, accounts, or visitors within a date range.

Use this tool to answer questions about usage patterns, engagement metrics, and activity counts. Supports filtering by account, visitor, segment, or specific item IDs, and grouping results by various dimensions.

RANKING PATTERN: For "top N" or "most active" queries, use count=false + group by the entity to rank + sort + limit. count=true returns ONLY a single aggregate number with no entity rows.

PRODUCT AREA: Pass productAreaId to scope the query to one product area (not with itemIds). For page, feature, and trackType entities, results are limited to items in that area; for visitor and account, to entities with any activity attributed to that area, including guides.

USE FOR: Getting activity metrics from various sources with several filtering options.

EXAMPLES:

• Top 3 features by visitors → entityType='feature', count=false, group=['featureId'], sort=['-uniqueVisitorCount'], limit=3, dateRange={range:'relative', lastNDays:30}
• Top 5 pages by traffic → entityType='page', count=false, group=['pageId'], sort=['-uniqueVisitorCount'], limit=5, dateRange={range:'relative', lastNDays:30}
• Most active visitors → entityType='visitor', count=false, group=['visitorId'], sort=['-numEvents'], limit=10, dateRange={range:'relative', lastNDays:30}
• Get account activity metrics for the account ID XYZ → dateRange={range:'relative', lastNDays:30}
• What are the most active pages in the last 30 days? → entityType='page', count=false, group=['pageId'], sort=['-numEvents'], limit=10, dateRange={range:'relative', lastNDays:30}
• How many visitors used feature ABC in the last 7 days? → entityType='feature', itemIds=['featureId'], group=['visitorId'], count=true, dateRange={range:'relative', lastNDays:7}
• How many accounts are active? → entityType='account', group=['accountId'], count=true, dateRange={range:'relative', lastNDays:30}
• Show activity for the top 5 track types → entityType='trackType', count=false, group=['trackTypeId'], sort=['-numEvents'], limit=5, dateRange={range:'relative', lastNDays:30}
• How many views did page X get in the last 30 days? → entityType='page', itemIds=['pageId'], count=true, dateRange={range:'relative', lastNDays:30}
• Count total events for feature X in the last week → entityType='feature', itemIds=['featureId'], count=true, dateRange={range:'relative', lastNDays:7}
• Return only the total number of matching entities for a query → set count=true
• Query specific date range → dateRange={range:'custom', startDate:'2024-01-01', endDate:'2024-01-31'}
• Get page activity for January 2024 → entityType='page', dateRange={range:'custom', startDate:'2024-01-01', endDate:'2024-01-31'}
• Which visitors used feature X in Q1 2024? → entityType='feature', itemIds=['featureId'], group=['visitorId'], dateRange={range:'custom', startDate:'2024-01-01', endDate:'2024-03-31'}
• Which features have the most rage clicks → frustrationMetrics=true, entityType='feature', count=false, group=['featureId'], sort=['-rageClickCount'], limit=10, dateRange={range:'relative', lastNDays:30}
• What is the count of unique events for account → entityType='account', dateRange={range:'relative', lastNDays:30}
• Which visitors were active on the most days? → entityType='visitor', group=['visitorId'], sort=['-daysActive'], limit=5, dateRange={range:'relative', lastNDays:30}
• Top pages in a product area → entityType='page', productAreaId='<id>', group=['pageId'], sort=['-numEvents'], limit=10, dateRange={range:'relative', lastNDays:30}
• How many visitors used a product area? → entityType='visitor', productAreaId='<id>', count=true, dateRange={range:'relative', lastNDays:30} (includes guide engagement; see guide_product_area.go for guide event subtype tuning)
• How many accounts used a product area? → entityType='account', productAreaId='<id>', count=true, dateRange={range:'relative', lastNDays:30} (includes guide engagement; see guide_product_area.go for guide event subtype tuning)
• Filter activity by a feature flag → featureFlag={name:'myFlag', value:true}. Use value:false to filter to events where the flag is not set to true.

NOT FOR: guides and polls; use guideMetrics instead. Finding unused or zero-activity entities within a product area; use productAreaMemberActivity instead.

RETURNS:

• Raw JSON array [{requestId, rows: [...], time, url}]
• When count=true: Returns only aggregate count values (count and meta.totalCount), not ranked entity rows. Use count=false for lists/rankings.
• Aggregated activity metrics for events, minutes spent, visitors, accounts, avgMinutesPerVisitor, avgDaysActivePerVisitor, and (if frustrationMetrics set) some 'frustration' metrics.
• Results can be grouped by a provided field.
• Results can be sorted by a provided field.
• By default, results are limited at 1000.

FILTERING OPTIONS:

• Filter by account ID
• Filter by visitor ID
• Filter by item IDs (i.e. page, feature, track type)
• Filter by product area ID (mutually exclusive with item IDs)
• Filter by visitor metadata (current values via visitorMetadataFilter)
• Filter by historical metadata (event-time visitor/account/parentAccount values via historicalMetadataFilter)

SORT OPTIONS:

• Any SELECT/GROUP field (accountId, day, featureId, itemId, month, pageId, trackTypeId, visitorId, week)
• numEvents - total event count
• numMinutes - total minutes spent
• uniqueAccountCount - count of unique accounts
• uniqueVisitorCount - count of unique visitors
• daysActive - count of unique days active
• avgMinutesPerVisitor - average minutes per visitor
• avgDaysActivePerVisitor - average days active per visitor
• if frustrationMetrics param is set, any frustration metric: errorClickCount, rageClickCount, uTurnCount, deadClickCount

The maximum time range for this tool is 367 days.

PERFORMANCE: This is a fast-running tool.

Returns key aggregate metrics for AI agent conversations with period-over-period comparison. Includes: conversations, visitors, accounts, prompts, rage prompt rates (per-prompt and per-conversation), visitorIds, accountIds, and visitor retention. All metrics include previous-period equivalents for trend analysis.

USE FOR: Getting a high-level summary of AI agent usage and engagement. Use when the user asks about overall agent performance, conversation volume, visitor engagement, rage prompt rates, or retention for a specific agent.

EXAMPLES:

• How many conversations has my ABC agent had in the last 30 days?
• What is the rage prompt rate for Acme agent this month?
• Show me key metrics and trends for my chat agent over the past 2 weeks.
• How many unique visitors have used my chat agent recently?

NOT FOR: Use list_use_cases for topic/cluster analysis. Use list_ai_agent_issues for issue detection. Use list_ai_agents to get agent IDs and names first when the user has not specified an agent.

RETURNS:

• Current period: numConversations, numPrompts, numVisitors, numAccounts, numRagePrompts, ragePromptsRate, ragePromptsConversationRate, retention (retentionRate, retained, visitors), visitorIds, and accountIds.
• Previous period (same duration, immediately prior): prevNumConversations, prevNumPrompts, prevNumVisitors, prevNumAccounts, prevNumRagePrompts, prevRagePromptsRate, prevRagePromptsConversationRate, prevRetention.
• Also includes conversationsWithRagePrompts and prevConversationsWithRagePrompts.

The maximum time range for this tool is 90 days.

PERFORMANCE: This is a slow-running tool.

Requires startDate and endDate (YYYY-MM-DD); there is no default range. Returns issue diagnoses, flagged response tool/model usage, and user prompt content for the events of a specific detected issue cluster in AI Agent Analytics. Executes a single aggregation with two parallel spawn branches: (1) agenticConversationEvents filtered by conversationIds — deduplicated visitorIds/accountIds and sampled explanations; (2) agenticEvents — tools/models from flagged response eventIds, and prompt content from issue conversationIds.

USE FOR: Diagnosing a specific detected issue cluster — call directly if agentId is known and conversationIds and eventIds are passed; Otherwise, call after list_ai_agents is called to get available AI agents and after list_ai_agent_issues is called to get issues clusters to find match and retrieve conversationIds/eventIds. Use when the user wants to understand why conversations were flagged, see patterns in user prompts that triggered the issue, or identify which tools and models were involved in the flagged responses.

EXAMPLES:

• What patterns exist among instances of the 'incorrect answers' issue?
• Which tools were called in instances of the 'timeout error' issue?
• Show me what users said in conversations flagged as the 'authentication failure' issue
• Why does the 'formatting problem' issue keep occurring in my agent?

NOT FOR: Use list_ai_agent_issues to discover issue clusters and get conversation/event IDs first (not when conversationIds and eventIds are already known). Use agent_analytics_key_metrics for aggregate volume metrics. Use list_use_cases for topic analysis of conversations (not issue diagnosis).

RETURNS:

• Four labeled CSV sections:
• [issue_instances]: visitorIds, accountIds — one summary row with deduplicated lists.
• [explanations]: explanation — one row per sampled issue explanation (capped for MCP size).
• [flagged_response_events]: issueToolsUsed, issueModelsUsed — one summary row with deduplicated lists.
• [user_prompts]: content — one row per sampled user prompt message (capped for MCP size).

The maximum time range for this tool is 90 days.

PERFORMANCE: This is a slow-running tool.

Creates a new feedback item in Pendo Listen. Returns the ID of the created feedback item.

USE FOR: Submitting product feedback, feature requests, bug reports, or user input to the Listen feedback repository

EXAMPLES:

• Log this user's feedback about the dashboard loading slowly
• Create a feature request for dark mode support
• Submit feedback that the export CSV button is confusing
• Capture this bug report about broken pagination
• Record this customer's request for a Slack integration

NOT FOR: Reading existing feedback — use get_feedback_items instead. For AI-extracted insights use get_feedback_insights.

RETURNS:

• feedbackId: ID of the created feedback item

PERFORMANCE: This is a fast-running tool.

This tool is only available to be called for the following subscriptions: (External Customer) Pendo Experience Sandbox (4691349476737024)

Fetch raw devlog events for a visitor or session, including HTTP request/response details, log levels, messages, and stack traces. Accepts a clipId or the individual fields (recordingSessionId, appId, visitorId, accountId, startTime, endTime) that identify a recording. When clipId is provided, the tool looks up the clip to resolve visitorId, accountId, appId, recordingSessionId, and time range automatically. If the user provides a session replay URL, parse the recordingSessionId from the URL path and query parameters (startTime, endTime, visitorId, accountId, appId) before calling this tool.

USE FOR: Investigating developer console logs, network errors, or HTTP activity captured during a session replay. Use when the user provides a session replay URL (parse the URL yourself to extract params), a clip ID, or when chaining from sessionReplayList results by passing recordingSessionId/appId/visitorId/accountId directly.

EXAMPLES:

• Show me devlogs for this session replay: https://<hostname>/s/123/replay/player/abc
• Show network requests captured in clip https://<hostname>/s/123/replay/clip/saved/xyz
• What HTTP errors occurred during visitor john's session?
• Fetch devlogs for clip ID abc-123
• Find devlog errors for account acme-corp
• What API calls did this visitor make during their session?
• After calling sessionReplayList, pass the row's recordingSessionId/appId/visitorId/accountId/startTime/endTime directly to fetch devlogs

NOT FOR: Listing session replays — use sessionReplayList instead. General page/feature analytics — use activityQuery or topEntities instead.

RETURNS:

• Devlog events including subType (console/network), log level, message, stack trace, HTTP method, request URL, status code, request/response headers and bodies. Limited to 100 events.

The maximum time range for this tool is 31 days.

PERFORMANCE: This is a slow-running tool.

This tool is only available to be called for the following subscriptions: pendo-internal (5668600916475904) Pendo for Pendo Employees (5769426755780608) (Demo) Pendo Experience (6591622502678528) Pendo AI

• Internal (6296072733130752)

tippy_demo (6284013896335360)

Generates AI-clustered topics from customer feedback matching the given filters. Each topic contains a name, description, and count of related insights. Use this for high-level overviews of the most common themes in a feedback subset.

PERFORMANCE: This is a slow-running tool.

This tool is only available to be called for the following subscriptions: pendo-internal (5668600916475904) (Demo) Pendo Experience (6591622502678528) (External Customer) Pendo Experience Sandbox (4691349476737024)

Fetches a grounding document that describes the current contents of a Pendo product resource so the LLM can reason about it. Today the only supported resource is a Pendo Space — a collaborative canvas of product artifacts (pages, features, guides, notes, etc.) curated by a team. Pass resource_type (e.g. "space") and resource_id (the id of that resource, e.g. a space id) to retrieve the document. Call list_spaces first if you need to discover a space id. The response is JSON returned by the Spaces service and typically contains a markdown body plus a schema describing the resource's contents; do not assume a shape beyond what the response declares. Use frame_id to scope a space's context to a single frame on the canvas (and items whose parent is that frame) — useful when the user's UI is focused on that frame; omit frame_id for the full space.

PERFORMANCE: This is a fast-running tool.

Retrieves key customer feedback insights extracted from raw feedback matching the given filters. Each item includes a summary, explanation, and supporting quote. Use this when the user wants to see actionable feedback insights which have been distilled from the raw customer feedback. Note: insights can also be referred to as 'highlights'

PERFORMANCE: This is a slow-running tool.

This tool is only available to be called for the following subscriptions: pendo-internal (5668600916475904) (Demo) Pendo Experience (6591622502678528) (External Customer) Pendo Experience Sandbox (4691349476737024)

Retrieves the original, raw customer feedback matching the given filters. Each item includes id, title, description, and info about the account and visitor which gave the feedback. Use this when the user wants the full raw feedback, as opposed to the extracted insights or clustered topics. A maximum of 30 items will be returned, however there may be more matching the filter set.

PERFORMANCE: This is a slow-running tool.

This tool is only available to be called for the following subscriptions: pendo-internal (5668600916475904) (Demo) Pendo Experience (6591622502678528) (External Customer) Pendo Experience Sandbox (4691349476737024)

Retrieves product ideas submitted by internal product employees which describe product enhancements and new features matching the given filters. Each item includes id, title, and description. A maximum of 30 items will be returned, however there may be more matching the filter set.

PERFORMANCE: This is a slow-running tool.

Get comprehensive guide performance analysis including reach, engagement, and effectiveness metrics.

USE FOR: Analyzing specific guide performance with core metrics like reach, engagement rates, and completion analysis.

EXAMPLES:

• How is the onboarding guide performing this month?
• Show me metrics for the tooltip guide
• What are the completion rates for the walkthrough guide?
• How many users are dismissing the announcement guide?
• Show me daily guide completion trends over the last 2 weeks
• What's the weekly pattern for guide engagement?

RETURNS:

• Reach metrics: total views, unique viewers, unique accounts
• Engagement metrics: views per user, total interactions
• Effectiveness metrics: completion rate, dismissal rate
• Poll unique visitor response counts and total response counts grouped by pollId (for guides with polls)
• NPS metrics (for NPS guides): npsScore, avgScore, numPromoters, numNeutral, numDetractors, per-score distribution (responseCount0 through responseCount10)
• Range periods (dayRange/weekRange): single aggregated values across entire date range
• Iterative periods (daily/weekly): time series with metrics broken down by day/week
• Raw aggregation results in JSON format

The maximum time range for this tool is 93 days.

PERFORMANCE: This is a fast-running tool.

Lists detected issues in AI agent conversations with instance counts and conversation counts. Returns a table of issue summary, instance count, and conversation count per issue. It also returns visitorIds and accountIds who experienced the issue.

USE FOR: Finding what problems or issues users encountered when using AI agents (e.g., incorrect answers, refusals, errors). Use when the user asks about common issues, problems, or failures with a specific agent.

EXAMPLES:

• What are the common issues my users are encountering using my ABC agent in the last 30 days?
• What problems have users been encountering when using Acme agent in my Acme application lately?
• Have we seen reduced occurrences of issues with incorrect answers in our fooBar agent since last month?
• What models are most often used when users face problems with the chat agent in ScramCorp app?

NOT FOR: Use list_use_cases for topic/cluster analysis of conversations. Use list_ai_agents to get agent IDs and names first when the user has not specified an agent.

RETURNS:

• Table of issues: summary, instance count, conversation count, agentId, appId, visitorIds, and accountIds.
• Sorted by conversation count descending. Limited to 500 rows; narrow by date range if needed.

The maximum time range for this tool is 90 days.

PERFORMANCE: This is a slow-running tool.

Lists all AI agents that the user has access to. AI agents are conversational assistants that can be deployed on specific pages or app-wide.

AI agents have the ability to collect conversations, cluster prompts by topics/use cases, and calculate metrics like conversation counts and rage prompt detection.

This tool returns agent ids and names for usage with other related agent tools.

PERFORMANCE: This is a fast-running tool.

Pendo data is split into subscriptions, which share a set of visitors and accounts. Each subscription is split into separate applications. This call returns a list of all the names and ids of all the subscriptions this user has access to, along with the names and ids of all of the applications in that subscription.

Most tools for this mcp require at least a subscription id; many also require an application id. Application ids are not unique across different subscriptions.

PERFORMANCE: This is a fast-running tool.

Returns all product areas for a subscription — their IDs, names, and descriptions. No search query required.

USE FOR: Enumerating all product areas or finding a productAreaId to pass to productAreaMemberActivity or other tools that require a productAreaId. Use this when the user asks about available product areas or when you need to present them a list to choose from.

EXAMPLES:

• What product areas do we have?
• List all product areas for this subscription
• What product area should I use for onboarding? → call list_product_areas to find the matching name and get its ID
• Show me all available product areas

NOT FOR: Querying activity or engagement metrics within a product area — use productAreaMemberActivity instead.

RETURNS:

• Array of all product areas with: id, name, description
• All product areas are returned in a single call — no pagination needed

PERFORMANCE: This is a fast-running tool.

Lists the Pendo Spaces the current user can access in this subscription. A Pendo Space is a collaborative canvas of product artifacts (pages, features, guides, notes, etc.) that a team curates together; think of it as a shared workspace or board inside Pendo. Returns JSON from the Spaces service (opaque shape — field names depend on the Spaces API response). Use this to discover a space id before calling get_agent_context with resource_type "space" and that id as resource_id.

PERFORMANCE: This is a fast-running tool.

Use case: Get AI agent conversation clustering analysis with comprehensive metrics. Analyzes conversations and prompts, grouping them by semantic topics/use cases.

Requires: agentId which can be obtained using the list_ai_agents tool. Date range is required.

Usage note: You should generally get the user to specify how many days back they want to analyze as well as for which agent.

Returns: Metrics per cluster: conversation counts, visitor engagement, account usage, retention rates, rage prompt detection, and lists of visitorIds and accountIds per use case.

The maximum time range for this tool is 90 days.

PERFORMANCE: This is a fast-running tool.

List and filter in-app guides. Returns guide ID, name, description, state, and scheduling info. Use this tool to find guides by status, type, activation method, or other attributes.

Guides are interactive in-app experiences (tooltips, walkthroughs, banners, lightboxes, etc.) that guide end-users through tasks in their application.

EXAMPLES:

• List all public guides
• Show me draft guides
• Find all walkthrough guides
• Which guides are set to launch automatically?
• List guides that have expired
• Show me all tooltip guides that are currently staged

RETURNS:

• Summary info for each matching guide: ID, name, description, state, type, launch method, and scheduling timestamps (showsAfter, expiresAfter)

FILTERING OPTIONS:

• status: Filter by guide state — public, staged, draft, _pendingReview_, disabled
• guideType: Filter by guide type — banner, tooltip, lightbox, walkthrough, whatsnew, building-block, group, training, launcher, mobile-lightbox
• activation: Filter by launch method — auto (automatic/app launch), api (programmatic), badge, dom (element click), embed (embedded), launcher (guide/resource center), page (page view), feature (element click, mobile), form, track (track event)
• expiration: Filter by expiration status — active (not expired), expired (past expiration date)

PERFORMANCE: This is a fast-running tool.

Returns NPS (Net Promoter Score) metrics for NPS surveys, including the overall NPS score (-100 to +100), average rating, and response distribution across promoters (9-10), passives (7-8), and detractors (0-6).

USE FOR: Answering questions about NPS scores, NPS trends, survey response breakdowns, and promoter/detractor analysis. Supports filtering by app. If no guideId is provided, automatically discovers NPS surveys.

EXAMPLES:

• What is our NPS score?
• What is the NPS score for app X?
• Show me NPS trends over the last 30 days
• What percentage of respondents are detractors?
• How many promoters vs detractors did we get this month?
• What is the NPS score for a specific survey?

NOT FOR: General guide performance metrics like completion rates or dismissal rates — use guideMetrics for those.

RETURNS:

• NPS score (-100 to +100), calculated as (% promoters - % detractors) * 100
• Average rating (0-10 scale)
• Response counts: numPromoters, numNeutral, numDetractors, numResponses
• Per-score distribution: responseCounts object with keys '0' through '10' (count of responses for each score value)
• Guide info: guideName, guideId, pollQuestion, pollId, appIds
• Individual NPS responses with visitorId, npsScore, npsReason, accountId, browserTime (when includeResponses is 'promoters', 'detractors', or 'unsorted', or visitorId is provided). Requires guideId.

The maximum time range for this tool is 93 days.

PERFORMANCE: This is a fast-running tool.

Return all pages, features, or track types belonging to a product area, including those with zero activity in the date range.

Use this tool when you need to identify unused or low-engagement entities within a product area — for example, "which features in the Onboarding product area have had no usage this quarter?" Unlike activityQuery, which only surfaces entities that have generated events, this tool fetches all members of the product area and left-joins activity data so that zero-event entities appear with numEvents: 0.

Supports optional segmentId filtering: when provided, activity metrics reflect only visitors in the segment, but all product area members are still returned (zero-activity rows remain for entities with no segment activity).

WHEN TO USE THIS TOOL vs. activityQuery:

• Use this tool when "not in the results" must mean "zero usage", not "not in the top N"
• Use activityQuery when you want ranked/sorted activity across all entities regardless of product area membership

USE FOR: Listing all members of a product area with their activity metrics, including entities with zero events.

EXAMPLES:

• Which features in the Onboarding product area have zero usage this quarter? → entityType='feature', productAreaId='<id>', sort=['+numEvents'], dateRange={range:'custom', startDate:'2025-01-01', endDate:'2025-03-31'}
• What pages in the Analytics product area should we consider sunsetting? → entityType='page', productAreaId='<id>', sort=['+numEvents'], limit=50, dateRange={range:'relative', lastNDays:90}
• Which pages in product area X have zero activity from visitors in segment Y? → entityType='page', productAreaId='<id>', segmentId='<id>', sort=['+numEvents'], dateRange={range:'relative', lastNDays:30}

NOT FOR: ranked activity across all entity types regardless of product area membership; use activityQuery instead.

RETURNS:

• All members of the product area for the given entity type
• Each row includes: entity ID, name, description, numEvents, numMinutes, uniqueVisitorCount, uniqueAccountCount, daysActive, avgMinutesPerVisitor, avgDaysActivePerVisitor
• Entities with no activity in the date range appear with all metrics set to 0
• When segmentId is provided, metrics reflect only activity from visitors in that segment; zero-activity rows still appear for entities with no segment activity

SORT OPTIONS:

• numEvents - total event count (default: ascending, to surface unused entities first)
• numMinutes, uniqueVisitorCount, uniqueAccountCount, daysActive

The maximum time range for this tool is 367 days.

PERFORMANCE: This is a fast-running tool.

A tool designed for running PES (product engagement score) queries. For any score fields that aren't required or provided, default saved PES configuration options are used.

USE FOR: Analyzing the PES, which is made up of scores from feature adoption, stickiness, and growth.

EXAMPLES:

• What is the PES for this feature?
• What is adoption score for a specific feature, page, and track event?
• What is the stickiness score for accounts, weekly over monthly? (This may expressed as WAA over MAA)
• What is the stickiness score for visitors, daily over monthly, excluding weekends? (This may expressed as DAU over MAU)
• What is the growth score for accounts?

RETURNS:

• PES score and component scores (adoption, stickiness, growth)
• Individual component scores (adoption, stickiness, growth)

The maximum time range for this tool is 180 days.

PERFORMANCE: This is a fast-running tool.

Look up the names and descriptions of product entities, such as: accounts, pages, features, track types, guides, starred replays (SessionRecording), saved clips, playlists or product areas. Guide results include a permalink URL that can launch the guide directly in the application. Saved clip and starred Replay results include a permalink URL that links directly to the saved clip in Session Replay. Playlist results include a permalink URL that links directly to the playlist in Session Replay. When users ask "How do I..." or "Help me with..." questions, search for Guide entities to find relevant step-by-step walkthroughs.

Useful for: finding relevant entities in the customer's product for follow-up analysis with other tools, learning more about specific entities, or answering how-to questions by finding relevant guides with direct launch links. Uses semantic search to find entities by conceptual meaning and relevance to natural language queries, with fuzzy search for broad matching.

Tool may be used in one of three ways: 1. Get specific entities: itemIds and exactly one itemType are specified; search_fallback and search are not allowed in this case. 2. Search for relevant entities: search_fallback AND search are BOTH specified, along with one or more itemType; itemIds is not allowed in this case. 3. Get starred entities: starredItemTypes lists one or more entity types and matching itemType are specified; returns only entities of those types starred by the current user. ALWAYS combine multiple starred entity types into a single call (e.g., starred replays AND starred guides in one call, not separate calls).

IMPORTANT: The search parameter should contain only the core query terms (e.g., "onboarding features", "Bridgeway Logistics"), not instructions or meta-commentary.

EXAMPLES:

• What features should I look at to track onboarding success?
• What parts of my app provide administrator functions?
• What communications do we have to end users advertising our annual conference?
• What instrumentation events do we collect for end-user performance?
• Which pages should I measure user activity on to see how much time users are spending in setup?
• What accounts contain 'acme' in their name?
• Do I have any accounts involved in steel manufacturing?
• How do I set up single sign-on?
• Help me configure user permissions in my app
• Show me saved clips about checkout errors
• Show me all my starred items

RETURNS:

• Entity ID, name, description, and search method for each match
• For Guide entities: a permalink URL that launches the guide in-app (when the guide is public and has audience set to everyone)
• For SessionRecording (Replay) entities: a permalink URL that links to the replay player
• For Saved Clip entities: a permalink URL linking directly to the saved clip in Session Replay
• For Playlist entities: a permalink URL linking directly to the playlist in Session Replay

PERFORMANCE: This is a fast-running tool.

List all the segments. The name and the id of each segment is returned, along with the flagName if the segment defines a feature flag. These segments can be used for query build tools. Only publicly shared segments are returned.

PERFORMANCE: This is a fast-running tool.

Get session replay recordings with filtering by duration, activity percentage, date range, frustration types, and track events. Returns detailed session metadata including frustration events, activity scores, and app information. When referencing a page, feature, or guide in a filter in association with a frustration type, defer to use occurredOn/notOccurredOn facts on frustration type filters over pageIds, featureIds, or guideIds filtering.

USE FOR: Finding session replays with specific criteria, analyzing user session quality, identifying high-activity or problematic sessions, scoping replays to specific apps, segments, accounts, features, or guides, filtering for sessions with specific frustration signals, or filtering by track events and their properties

EXAMPLES:

• Show me recordings that occur on page 1234
• Show me session replays from the last week with high activity
• Find session replays longer than 5 minutes
• Show me session replays for visitor 1234
• Show me session replays for account acme-corp
• Show me session replays for app 5678
• Show me session replays where users interacted with feature abc123
• Show me session replays where users saw guide xyz789
• Show me session replays with rage clicks
• Show me session replays where the checkout-completed track event fired

RETURNS:

• Session replay recordings with their URL and metadata including duration, activity percentage, frustration events, and app details. Limited to 50 replays returned.

The maximum time range for this tool is 31 days.

PERFORMANCE: This is a fast-running tool.

This tool is only available to be called for the following subscriptions: pendo-internal (5668600916475904) Pendo for Pendo Employees (5769426755780608) (Demo) Pendo Experience (6591622502678528) Pendo AI

• Internal (6296072733130752)

tippy_demo (6284013896335360)

Return the set of metadata that is available from the visitors table for each visitor. It is a set of . separated metadata field names to information about that field, including the type. Here is an example return value

{ "metadata.auto.lastvisit" : "time", "metadata.pendo.donotproces" : "boolean" }

PERFORMANCE: This is a fast-running tool.

Retrieve visitor data and metadata OR just the counts of matching visitors by running aggregation queries directly against the visitor dataset. Every response entity will conceptually be a visitor (a person who visited the application) and their associated metadata if you use select to ask for them.

USE FOR: Getting visitor information, metadata, and visitor counts with flexible filtering options.

EXAMPLES:

• Get all visitors with their last visit time
• Show me visitors from a specific segment
• How many visitors match certain criteria? (set count=true)
• Get visitor metadata like browser, location, or custom fields
• Find visitors with a specific metadata value

WORKFLOW: Use the visitorMetadataSchema tool to explore available metadata fields, then use this tool for detailed analysis

RETURNS:

• Visitor data with selected metadata fields (without select passed in, no metadata fields are returned)
• Visitor counts when count=true is specified
• Results filtered by segments, specific visitor IDs, metadata, or other criteria
• Results are sorted by last visit time descending
• By default, results are limited to 10,000 visitors per request. If 10,000 visitors are returned, assume there are more visitors and consider refining your filters or increasing the limit.

FILTERING OPTIONS:

• Filter by specific visitor ID
• Filter by visitor segments
• Filter by metadata value for a specific metadata group and field
• Automatically filters out anonymous visitors (unless subscription allows them)

PERFORMANCE: This is a fast-running tool.