Contentsquare remote MCP connector

  • Updated

The Contentsquare remote Model Context Protocol (MCP) connector in Optimizely Opal connects behavioral insights to your Opal workflows. Opal retrieves and analyzes experience data from Contentsquare. Use these tools to uncover why users struggle, for example, by visualizing navigation journeys or ranking technical errors by their impact on business goals. These tools help you identify friction points and conversion leakage, so you can optimize the customer experience faster.

The Contentsquare remote MCP is managed by Contentsquare. See How to set up and use Model Context Protocol (MCP) in their documentation for information.

First, an Opal administrator must Connect the Contentsquare Remote MCP to Opal. After adding the MCP server, individual Opal users and agent builders log in to Contentsquare to access their information from Opal. Administrators need to add the Contentsquare remote MCP only once.

Connect the Contentsquare remote MCP to Opal

To connect the Contentsquare remote MCP to Opal, complete the following steps as an Opal administrator:

  1. Go to Tools > Connectors in Opal.

  2. Click Add Remote MCP. 

    Screenshot of the Opal Connectors page where the Add Remote MCP button is visible
  3. Click Contentsquare.
  4. Click Next.
  5. Click Connect to Contentsquare.
  6. Complete required access configuration in the pop-up window.
  7. Click Accept.

The Contentsquare tile is now available on the Connectors tab for users to authenticate with their personal accounts.

Authenticate with Contentsquare

After an administrator connects the Contentsquare remote MCP to Opal, you can log in to Contentsquare. User-level authentication ensures Opal users and agent builders can access only their authorized Contentsquare data.

To authenticate, complete the following steps in Opal:

  1. Go to Tools > Connectors.
  2. Click Connect for Contentsquare.
  3. Log in to Contentsquare.

After you connect to Contentsquare, the Contentsquare connector tools become available in Opal Chat, agents, and workflows.

Contentsquare connector tools

After an administrator connects Contentsquare remote MCP to Opal and you log in to Contentsquare, the following tools are available in Opal. Click a tool name to expand it and view usage guidance, parameters, and example prompts. If you do not provide a required parameter, Opal prompts you for it.

Behavioral analytics

These tools calculate core behavioral metrics and visualize user paths.

computeFunnel – Measures drop-offs and conversions. 
  • When to use
    • Measure drop-offs and conversions across key steps in a user journey.
    • Analyze conversion rates, drop-off points, and time to completion across up to 32 steps.
  • Parameters
    • dateRange – Date range for analysis. The start date must be on or before the end date. The end date must be on or before the current date. The maximum range is 92 days. Use YYYY-MM-DDTHH:mm:ss.
    • deviceType – The device type to filter the analysis.
    • funnel – The funnel configuration object. 
    • (Optional) locale – Locale for date and time formatting in Best Current Practice (BCP) 47 format (for example, en-US or fr-FR).
    • pageMappingId – The mapping ID that the page groups belong to. Page groups must be from this mapping.
    • projectId – Project ID for analysis context.
    • (Optional) timezone – Timezone for date calculations (Internet Assigned Numbers Authority (IANA) timezone format, for example, 'America/New_York' or 'Europe/Paris').
    • (Optional) userFilter – Optional filter to analyze a subset of users based on browser type, goal completion, segment membership, or page interactions (bounce, exit, landing). Supports nested filter sets with AND and OR logic. Available filter types – browser, goal, segment, pageview_bounce, pageview_exit, and pageview_landing.
  • Example prompts
    • Calculate the checkout funnel performance for project 12345 comparing mobile and desktop users for the last 30 days.
    • Show me where users are dropping off in our 3-step registration funnel on the main site mapping.
    • Analyze the conversion rate of the subscription funnel for users in the United States over the past month.
computeImpact – Computes impact quantification analysis comparing conversion performance between segments.
  • When to use
    • Compare conversion performance between different user segments.
    • Analyze metrics including conversion rates, bounce rates, session time, pageviews, and revenue impact.
    • Test statistical significance between different segment performances.
  • Parameters
    • base – Base configuration for the impact analysis.
    • conversionGoal – Conversion goal ID for calculating segment performance metrics. Must be from the available goals list.
    • projectId – Project ID for analysis context.
    • (Optional) compare – Optional comparison configuration to compare impact metrics across different date ranges, device types, or user segments.
    • (Optional) locale – Locale for date and time formatting in BCP 47 format (for example, 'en-US' or 'fr-FR').
    • (Optional) timezone – Timezone for date calculations (IANA timezone format, for example, 'America/New_York' or 'Europe/Paris').
  • Example prompts
    • Quantify the impact of the new homepage layout on the Add to Cart goal compared to the previous version.
    • Analyze the revenue impact of returning visitors versus new visitors for our seasonal campaign.
    • Compare the bounce rates and session times between organic and paid traffic segments for project 98765.
computeJourney – Computes user navigation journeys, visualizing site navigation patterns.
  • When to use
    • Visualize how visitors navigate your site with hierarchical tree structures showing common paths.
    • Identify drop-off points and navigation patterns up to 7 steps.
    • Perform forward analysis from landing pages or reverse analysis from exit pages.
  • Parameters
    • dateRange – Date range for analysis. The start date must be on or before the end date. The end date must be on or before the current date. The maximum range is 92 days. Use YYYY-MM-DDTHH:mm:ss.
    • deviceType – The device type to filter the analysis.
    • journey – The journey configuration object.
    • (Optional) locale – Locale for date/time formatting in BCP 47 format (for example, 'en-US', 'fr-FR').
    • pageMappingId – Page mapping ID containing the relevant page groups for analysis.
    • projectId – Project ID for analysis context.
    • (Optional) timezone – Timezone for date calculations (IANA timezone format, for example, 'America/New_York', 'Europe/Paris').
    • (Optional) userFilter – Optional filter to analyze a subset of users based on browser type, goal completion, segment membership, or page interactions (bounce, exit, landing). Supports nested filter sets with AND and OR logic. Available filter types – browser, goal, segment, pageview_bounce, pageview_exit, pageview_landing.
  • Example prompts
    • Show me the most common paths users take starting from the products landing page in project 555.
    • Analyze the reverse journey for users who exited from the checkout confirmation page last week.
    • Visualize the desktop navigation patterns for the last 14 days focused on the main shop mapping.
computePageComparison – Computes page comparison analysis comparing metrics across multiple page groups. 
  • When to use
    • Compare key performance metrics across 2 to 10 page groups.
    • Analyze metrics like views, bounce rate, exit rate, scroll rate, and time spent.
    • Evaluate activity levels, load times, and conversion rates for selected goals.
  • Parameters
    •  
    • dateRange – Date range for analysis. The start date must be on or before the end date. The end date must be on or before the current date. The maximum range is 92 days. Use YYYY-MM-DDTHH:mm:ss.
    • deviceType – The device type to filter the analysis.
    • pageGroupsToCompare – Array of page group IDs to compare (minimum 2, maximum 10). All page groups must belong to the selected page mapping as 'pageMapping' field.
    • pageMapping – The mapping for the page groups that the user wants to compare.
    • projectId – Project ID for analysis context.
    • (Optional) conversionGoal – The ID of a goal used by the "Conversion rate of selected goal" metric.
    • (Optional) locale – Locale for date and time formatting in BCP 47 format (for example, 'en-US' or 'fr-FR').
    • (Optional) timezone – Timezone for date calculations (IANA timezone format, for example, 'America/New_York' or 'Europe/Paris').
    • (Optional) userFilter – Optional filter to analyze a subset of users based on browser type, goal completion, segment membership, or page interactions (bounce, exit, landing). Supports nested filter sets with AND and OR logic. Available filter types – browser, goal, segment, pageview_bounce, pageview_exit, and pageview_landing.
  • Example prompts
    • Compare the bounce rates and activity levels of the Blog and News page groups for 2025.
    • See which product category page group has the highest scroll rate and time spent for mobile visitors.
    • Run a comparison of the top 5 landing page groups based on the Purchase goal conversion rate for project 123.
computePageGroupMetrics – Compute metrics at the page group level for an overview of performance.
  • When to use
    • Retrieve a performance overview for a specific fraction of the website.
    • Access basic, ecommerce, goal, error, and frustration metrics for page groups.
    • Filter analysis by device or group by dimensions like path, browser, or country.
  • Parameters
    • pageGroupId – ID of the page group to compute metrics for.
    • projectId – Project ID for analysis context.
    • startDateTime – Start date for the analysis in YYYY-MM-DDTHH:mm format.
    • endDateTime – End date for the analysis computation in YYYY-MM-DDTHH:mm format. Must not be later than current time. Maximum range is 92 days.
    • (Optional) device – Device type to filter the analysis. If not provided, all devices are included.
    • (Optional) dimensions – Array of dimensions to group the metrics by. Supported dimensions include path, appVersion, browserName, city, and more.
    • (Optional) goalId – Goal ID to filter the analysis. If not provided, no goal filtering is applied.
    • (Optional) metrics – Array of metrics to compute (ActivityRate, BounceRate, InteractionTime, and so on).
    • (Optional) userFilter – Optional filter to analyze a subset of users based on browser type, goal completion, segment membership, or page interactions (bounce, exit, landing). Supports nested filter sets with AND and OR logic. Available filter types – browser, goal, segment, pageview_bounce, pageview_exit, and pageview_landing.
  • Example prompts
    • Get the views, bounce rate, and visits for page group 456 grouped by country for the first week of October.
    • Calculate the frustration score and activity level for the checkout page group on mobile devices.
    • Show the performance metrics for my 'Sale' page group, grouped by day, for the last month in project 99.
computeSiteMetrics – Computes aggregated site-wide metrics grouped by specified dimensions.
  • When to use
    • Analyze aggregated performance metrics across the entire website.
    • Review site-wide bounce rate, session time, conversion rate, and ecommerce totals.
    • Group results by dimensions like device, browser, city, country, or day.
  • Parameters
    • projectId – Project ID for analysis context.
    • startDateTime – Start date for the analysis in YYYY-MM-DDTHH:mm format.
    • endDateTime – End date for the analysis computation in YYYY-MM-DDTHH:mm format. Must not be later than current time. Maximum range is 92 days.
    • (Optional) device – Device type to filter the analysis. If not provided, all devices are included.
    • (Optional) dimensions – Array of dimensions to group the metrics by. Supported dimensions include appVersion, browserName, city, countryCode, and more.
    • (Optional) goalId – Goal ID to filter the analysis. If not provided, no goal filtering is applied.
    • (Optional) metrics – Array of metrics to compute (bounceRate, sessionTimeAverage, conversionRate, revenue, and so on).
    • (Optional) userFilter – Optional filter to analyze a subset of users based on browser type, goal completion, segment membership, or page interactions (bounce, exit, landing). Supports nested filter sets with AND and OR logic. Available filter types – browser, goal, segment, pageview_bounce, pageview_exit, and pageview_landing.
  • Example prompts
    • Analyze the site-wide revenue and transaction rate grouped by browser for project 101 between March 1 and March 15.
    • What was the average session time and total visits for all mobile users on our site last month?
    • Show me a breakdown of conversion counts and conversion rates by city for our main signup goal.

Error and conversion insights

These tools identify friction points, technical errors, and conversion leakage.

getTopErrorsByImpactOnGoal – Gets top errors ranked by impact on conversion goals.
  • When to use
    • Perform business impact analysis of technical errors.
    • Prioritize bug fixes based on their direct effect on revenue and conversions.
    • Determine which revenue-critical issues are affecting specific business goals.
  • Parameters
    • analysisScope – The scope of the error analysis.
    • dateRange – Date range for analysis. The start date must be on or before the end date. The end date must be on or before the current date. The maximum range is 92 days. Use YYYY-MM-DDTHH:mm:ss.
    • deviceType – The device type to filter the analysis.
    • goalId – Conversion goal for error impact measurement. Use -1 for ecommerce goal.
    • mappingId – Page mapping ID for grouping pages. Must be from the available mappings list.
    • projectId – Project ID for analysis context.
    • (Optional) errorType – Error category filter. Options – all (default), JS, API, CUSTOM, CRASH, and FLUTTER.
    • (Optional) locale – Locale for date and time formatting in BCP 47 format (for example, 'en-US' or 'fr-FR').
    • (Optional) timezone – Timezone for date calculations (IANA timezone format).
    • (Optional) userFilter – Optional filter to analyze a subset of users based on browser type, goal completion, segment membership, or page interactions.
  • Example prompts
    • Which JavaScript errors had the highest impact on our 'Purchase' goal last week?
    • Rank the top API failures affecting our 'Sign Up' conversion for mobile users in project 456.
    • Show me the most business-critical errors impacting the ecommerce goal for the last 30 days.
getTopErrorsByMissedOpportunity – Gets top errors ranked by missed business opportunities.
  • When to use
    • Identify errors that resulted in the highest missed revenue opportunities.
    • Analyze lost sales specifically for ecommerce environments.
    • Quantify the financial impact of technical failures on checkout and transaction flows.
  • Parameters
    • analysisScope – The scope of the error analysis. 
    • dateRange – Date range for analysis. The start date must be on or before the end date. The end date must be on or before the current date. The maximum range is 92 days. Use YYYY-MM-DDTHH:mm:ss.
    • deviceType – The device type to filter the analysis.
    • mappingId – Page mapping ID for grouping pages. Must be from the available mappings list.
    • projectId – Project ID for analysis context.
    • (Optional) errorType – Error category filter. Options – all (default), JS, API, CUSTOM, CRASH, and FLUTTER.
    • (Optional) goalId – Conversion goal for missed opportunity measurement. Use -1 for ecommerce goal.
    • (Optional) locale – Locale for date/time formatting in BCP 47 format (for example, 'en-US' or 'fr-FR').
    • (Optional) timezone – Timezone for date calculations (IANA timezone format).
    • (Optional) userFilter – Filter to analyze a subset of users based on browser type, goal completion, segment membership, or page interactions.
  • Example prompts
    • Show me the top 5 errors that caused the most missed revenue for project 123 this month.
    • What were the primary checkout errors leading to lost sales on mobile devices last quarter?
    • Analyze the missed opportunities due to custom errors on the checkout page using mapping 789.
getTopErrorsBySessionsWithErrors – Gets top errors ranked by sessions with errors.
  • When to use
    • Perform a general error analysis to find trends and patterns.
    • Identify the most frequent errors affecting the total user base.
    • Compare the volume of different error types like JS, API, or custom failures.
  • Parameters
    • analysisScope – The scope of the error analysis. 
    • dateRange – Date range for analysis. The start date must be on or before the end date. The end date must be on or before the current date. The maximum range is 92 days. Use YYYY-MM-DDTHH:mm:ss.
    • deviceType – The device type to filter the analysis.
    • projectId – Project ID for analysis context.
    • (Optional) errorDisplayUnit – Metric display format. percent for rates or trends (default) or unit for absolute volumes.
    • (Optional) errorType – Error category filter. Options – all (default), JS, API, CUSTOM, CRASH, and FLUTTER.
    • (Optional) granularity – Time interval granularity for time-series data. Valid values: MINUTE, HOUR, DAY, WEEK, MONTH.
    • (Optional) locale – Locale for date and time formatting in BCP 47 format (for example, 'en-US' or 'fr-FR').
    • (Optional) timezone – Timezone for date calculations (IANA timezone format).
    • (Optional) userFilter – Optional filter to analyze a subset of users based on browser type, goal completion, segment membership, or page interactions.
  • Example prompts
    • What are the most frequent errors our users encountered yesterday in project 999?
    • Show me the trend of JS errors versus API failures over the last 14 days grouped by week.
    • List the top errors affecting mobile sessions for the last 7 days in terms of absolute volume.
getTopPageGroupsByLostConversions – Gets page groups ranked by lost conversions due to errors.
  • When to use
    • Analyze the business impact of errors grouped by specific site sections (page groups).
    • Identify which major site areas (for example, Checkout or Product Pages) are losing the most conversions.
    • Determine where to focus development efforts to restore the most lost business value.
  • Parameters
    • analysisScope – The scope of the error analysis. 
    • dateRange – Date range for analysis. The start date must be on or before the end date. The end date must be on or before the current date. The maximum range is 92 days. Use YYYY-MM-DDTHH:mm:ss.
    • deviceType – The device type to filter the analysis.
    • goalId – Conversion goal for error impact measurement. Use -1 for an ecommerce goal.
    • mappingId – Page mapping ID for grouping pages. Must be from the available mappings list.
    • projectId – Project ID for analysis context.
    • (Optional) errorType – Error category filter. Options – all (default), JS, API, CUSTOM, CRASH, and FLUTTER.
    • (Optional) locale – Locale for date/time formatting in BCP 47 format (for example, 'en-US' or 'fr-FR').
    • (Optional) timezone – Timezone for date calculations (IANA timezone format).
    • (Optional) userFilter – Optional filter to analyze a subset of users based on browser type, goal completion, segment membership, or page interactions.
  • Example prompts
    • Which page groups are losing the most conversions due to technical errors this month?
    • Show the top product page groups that were impacted by API errors for the last 30 days.
    • Identify the page categories in project 456 that had the highest number of lost 'Checkout' goal completions.
getTopPagesBySessionsWithErrors – Gets pages most affected by errors through volume and traffic comparison.
  • When to use
    • Identify the specific pages where technical issues are most concentrated relative to traffic.
    • Prioritize development resources by seeing which high-traffic pages have high error rates.
    • Perform scatter plot style analysis comparing error volume with page traffic.
  • Parameters
    • analysisScope – The scope of the error analysis.
    • dateRange – Date range for analysis. The start date must be on or before the end date. The end date must be on or before the current date. The maximum range is 92 days. Use YYYY-MM-DDTHH:mm:ss.
    • deviceType – The device type to filter the analysis.
    • mappingId – Page mapping ID for grouping pages. Must be from the available mappings list.
    • projectId – Project ID for analysis context.
    • (Optional) displayType – Aggregation level for page analysis. pagegroups (default) or pages for individual URLs.
    • (Optional) errorType – Error category filter. Options – all (default), JS, API, CUSTOM, CRASH, and FLUTTER.
    • (Optional) locale – Locale for date/time formatting in BCP 47 format (for example, 'en-US' or 'fr-FR').
    • (Optional) timezone – Timezone for date calculations (IANA timezone format).
    • (Optional) userFilter – Optional filter to analyze a subset of users based on browser type, goal completion, segment membership, or page interactions.
  • Example prompts
    • Show me a breakdown of which individual URLs have the highest error rates in project 123.
    • Which high-traffic page groups are currently most affected by JavaScript errors?
    • Find the pages with the highest volume of sessions with errors for the last 7 days using mapping 456.

Data discovery and search

These tools list, find, and retrieve metadata and existing configurations.

getPageGroupsForMapping – Retrieves all page groups for a specific mapping, sorted alphabetically by name. 
  • When to use
    • To get a complete list of page groups belonging to a mapping.
    • When page groups need to be viewed in alphabetical order.
  • Parameters
    • mappingId – The ID of the mapping to retrieve page groups for.
    • projectId – Project ID to get data for.
  • Example prompts
    • Find all page groups for mapping ID 12345 in project 9876.
    • List the page groups for the main site mapping (ID 555) for my current project.
    • Retrieve the alphabetical list of page groups for mapping 112233.
listProjects – Returns a list of projects (ID and name) accessible to you. 
  • When to use
    • To see all Contentsquare projects available to the authenticated user.
    • To find a specific project ID needed for other analysis tools.
  • Parameters
    • No parameters required.
  • Example prompts
    • Show me all the Contentsquare projects I can access.
    • List the names and IDs of my available projects.
    • Which projects are currently connected to my account?
searchGoals – Searches and retrieves goals for a project. 
  • When to use
    • To find conversion goals associated with a specific project.
    • When you need a list of goals to filter analytics data.
  • Parameters
    • projectId – Project ID to get data for.
    • (Optional) limit – Maximum number of goals to return.
  • Example prompts
    • Search for all goals in project 101.
    • Find up to 50 conversion goals for project 4321.
    • Retrieve the goals registered for project 8888.
searchMappings – Searches and retrieves mappings for a project. 
  • When to use
    • To identify the different page mappings configured for a project.
    • To discover mapping IDs for page group analyses.
  • Parameters
    • projectId – Project ID to get data for.
    • (Optional) limit – Maximum number of mappings to return.
  • Example prompts
    • Find the available page mappings for project 202.
    • List the mappings for project 7777 with a limit of 10 results.
    • Search for mappings in project 5555.
searchSegments – Searches and retrieves segments for a project. 
  • When to use
    • To find user segments used for filtering behavioral analysis.
    • To discover segment IDs for specialized user reports.
  • Parameters
    • projectId – Project ID to get data for.
    • (Optional) limit – Maximum number of segments to return.
  • Example prompts
    • Search for user segments in project 303.
    • List up to 20 segments available for project 6666.
    • Find segments for my current project ID 1234.

AI recommendations 

These tools use AI to suggest goals, segments, and mappings for analysis.

recommendGoals – Recommends goals based on user engagement and usage frequency within the platform. 
  • When to use
    • Identify goals that are frequently viewed or used in analyses.
    • Discover popular conversion targets among team members.
    • Set up dashboards using the most relevant performance indicators.
  • Parameters
    • projectId – Project ID to get data for.
    • (Optional) limit – Maximum number of goals to return.
  • Example prompts
    • Which goals are most frequently used in project 1234?
    • Suggest the top 5 goals based on team engagement for project 567.
    • Recommend some conversion goals I should track for my recently launched project.
recommendMappings – Recommends mappings based on user engagement and usage frequency within the platform. 
  • When to use
    • Discover which page mappings are analyzed most often by your organization.
    • Identify the most active site structures for your reporting.
    • Quickly find relevant mappings for a new analysis.
  • Parameters
    • projectId – Project ID to get data for.
    • (Optional) limit – Maximum number of mappings to return.
  • Example prompts
    • Which page mappings are currently the most active in my project?
    • Show me a recommended list of mappings to use for analysis in project 432.
    • Suggest the top 3 page mappings based on recent platform usage.
recommendPageGroups – Recommends page groups based on user engagement and usage frequency within the platform. 
  • When to use
    • Understand which site sections, for example product pages or checkout flows, are most frequently analyzed.
    • Identify high-traffic or high-interest page groups for focused optimization.
    • Determine which page groups are most valuable for your current project context.
  • Parameters
    • projectId – Project ID to get data for.
    • (Optional) limit – Maximum number of page groups to return.
  • Example prompts
    • Which page groups do my teammates analyze most often in project 888?
    • Recommend the most relevant page groups for my project's primary mapping.
    • Suggest several page groups that are highly engaged for project 123.
recommendSegments – Recommends segments based on user engagement and usage frequency within the platform. 
  • When to use
    • Find user segments that are commonly used in reports, for example mobile users, returning visitors, and so on.
    • Identify the most impactful audience categories for your site.
    • Get suggestions for segments that have high visibility within your team’s analyses.
  • Parameters
    • projectId – Project ID to get data for.
    • (Optional) limit – Maximum number of segments to return.
  • Example prompts
    • Recommend the most significant user segments to analyze for project 991.
    • Which user segments are being viewed most frequently by our team?
    • Provide a list of the top 10 recommended segments based on platform usage.

Feedback

This tool manages feedback for the connector experience.

submitMcpFeedback – Submits feedback about your MCP server experience.
  • When to use
    • Provide feedback on your experience with the Contentsquare MCP server.
    • Rate specific tools to help improve the Contentsquare MCP server.
    • Share thoughts or comments about tool performance and usability.
  • Parameters
    • projectId – The ID of the project submitting feedback.
    • rating – Rating from 1 (poor) to 5 (excellent).
    • (Optional) comment – Additional context about your experience.
    • (Optional) toolName – The name of the tool you are providing feedback about.
  • Example prompts
    • Submit a rating of 5 for project 12345 to let the team know the connector is working perfectly.
    • Provide feedback on the computeFunnel tool for project 9876 with a rating of 3 and a comment about the parameter complexity.
    • Rate my experience with project 444 as a 4 and share a thought that the error analysis tools are very helpful for debugging.

If you use Opti ID, administrators can turn off generative AI in the Opti ID Admin Center. See Turn generative AI off across Optimizely applications.