A reload task in QlikView fails with the following error in the task log:

Error The sourcedocument failed to save.. Exception=System.Runtime.InteropServices.COMException (0x80004005): Error HRESULT E_FAIL has been returned from a call to a COM component. || at QlikView.Doc.SaveAs(String _FileName, Int16 _Format) || at QVBWrapper.Document.Save(ILogBucket i_LogBucket, String i_SaveAsFileName)

This may be caused by an active virus scan locking the relevant files, or an invalid alert configured on the task.

• QlikView

Virus Scan

Ensure that QlikView file locations (.qvw, qvd, etc..) are excluded from active virus scans. See QlikView Folder And Files To Exclude From Anti-Virus Scanning .

Invalid Alerts

Remove or edit the alerts configured on the document.

Alerts can be configured in the Distribution task. To verify:

• Open the QlikView Management Console
• Go to Documents > Source Documents
• Locate the failing document/task.
• Open the document/task
• Navigate to the Distribute tab
• Go to the Notify tab.
• Uncheck Send notification e-mail to recipients 
• Make sure, there is enough disk space to save the QVW

For additional troubleshooting steps and root causes, see QlikView: Checklist For Reload/Publisher Task Failure.

The Microsoft Fabric Connector is not currently supported as a target system.

A connection using the Azure Storage connector may succeed and pass testing, but reloads will fail with "Operation not supported" on the specific endpoint.

Qlik is actively working on enhancements to provide the functionality in the future: 

• TLV-2349: New Connector for Microsoft Fabric (Discovery)
• TLV-1841: Qlik Open Lakehouse (Iceberg) Connector for Qlik Analytics (Discovery)

A specific release date has not yet been determined.

Stay up to date with the Qlik Cloud changelog. 

Environment

• Qlik Cloud Analytics

After an upgrade to QlikView September 2025 SR1, tasks defined in the QlikView Management Console using an external program fail.

The QlikView server's Windows Event log shows the following error:

Faulting application name: Qv.exe, version: 12.100.20100.0, time stamp: 0x692464ea
Faulting module name: ntdll.dll, version: 10.0.20348.4893, time stamp: 0xfd32fdb3
Exception code: 0xc0000005

Affected versions:

• QlikView September 2025 SR 1

Resolution

This is a known QV.exe defect (QCB-34453). Upgrade to QlikView September 2025 SR 2 or later releases.

Information provided on this defect is given as is at the time of documenting. For up-to-date information, please review the most recent Release Notes or contact support with the ID QCB-34453 for reference.

Cause

Product Defect ID: QCB-34453

Amazon S3 V2 connections and reloads fail with the following error:

Could not load file or assembly 'System.Text.Json, Version=6.0.0.11, Culture=neutral, PublicKeyToken=cc7b13ffcd2ddd51' or one of its dependencies. The located assembly's manifest definition does not match the assembly reference. (Exception from HRESULT: 0x80131040) 

Affected versions:

• Qlik Sense Enterprise on Windows November 2024 SR 25 and SR 26
• Qlik Sense Enterprise on Windows May 2025 SR 15 to SR 18
• Qlik Sense Enterprise on Windows November 2025 SR 3 to SR 8

Resolution

This is a known defect (SUPPORT-8609). QvWebStorageProviderConnectorPackage.exe.config is not correctly overwritten during the upgrade process.

Upgrade to the following versions:

• Qlik Sense Enterprise on Windows November 2024 SR 27 or higher
• Qlik Sense Enterprise on Windows May 2025 SR 19 or higher
• Qlik Sense Enterprise on Windows November 2025 SR 9 or higher

Information provided on this defect is given as is at the time of documenting. For up-to-date information, please review the most recent Release Notes or contact support with the ID SUPPORT-8609 for reference.

Cause

Product Defect ID: SUPPORT-8609

In this article, we walk you through the requirements and process of how to upgrade and unbundle an existing Qlik Sense Repository Database (see supported scenarios) as well as how to install a brand new Repository based on PostgreSQL. We will use the Qlik PostgreSQL Installer (QPI).

For a manual method, see How to manually upgrade the bundled Qlik Sense PostgreSQL version to 12.5 version.

Using the Qlik Postgres Installer not only upgrades PostgreSQL; it also unbundles PostgreSQL from your Qlik Sense Enterprise on Windows install. This allows for direct control of your PostgreSQL instance and facilitates maintenance without a dependency on Qlik Sense. Further Database upgrades can then be performed independently and in accordance with your corporate security policy when needed, as long as you remain within the supported PostgreSQL versions. See How To Upgrade Standalone PostgreSQL.

Index

• Supported Scenarios
• Upgrades
• New installs
• Requirements
• Known limitations
• Installing anew Qlik Sense Repository Database using PostgreSQL
• Qlik PostgreSQL Installer - Download Link
• Upgrading an existing Qlik Sense Repository Database
• The Upgrade
• Next Steps and Compatibility with PostgreSQL installers
• How do I upgrade PostgreSQL from here on?
• Troubleshooting and FAQ
• Related Content

Video Walkthrough

Video chapters:

• 01:02 - Intro to PostgreSQL Repository
• 02:51 – Prerequisites
• 03:24 - What is the QPI tool?
• 05:09 - Using the QPI tool
• 09:27 - Removing the old Database Service
• 11:27 - Upgrading a stand-alone to the latest release
• 13:39 - How to roll-back to the previous version
• 14:46 - Troubleshooting upgrading a patched version
• 18:25 - Troubleshooting upgrade security error
• 21:15 - Additional config file settings

Supported Scenarios

Upgrades

The following versions have been tested and verified to work with QPI: 

Qlik Sense February 2022 to Qlik Sense November 2024.

If you are on a Qlik Sense version prior to these, upgrade to at least February 2022 before you begin.  

Qlik Sense November 2022 and later do not support 9.6, and a warning will be displayed during the upgrade. From Qlik Sense August 2023 a upgrade with a 9.6 database is blocked.

New installs

The Qlik PostgreSQL Installer supports installing a new standalone PostgreSQL database with the configurations required for connecting to a Qlik Sense server. This allows setting up a new environment or migrating an existing database to a separate host.

Requirements

• Review the QPI Release Notes before you continue

• Using the Qlik PostgreSQL Installer on a patched Qlik Sense version can lead to unexpected results. If you have a patch installed, either:

  • Uninstall all patches before using QPI (see Installing and Uninstalling Qlik Sense Patches) or
  • Upgrade to an IR release of Qlik Sense which supports QPI

• The PostgreSQL Installer can only upgrade bundled PostgreSQL database listening on the default port 4432.
• The user who runs the installer must be an administrator.
• The backup destination must have sufficient free disk space to dump the existing database  
• The backup destination must not be a network path or virtual storage folder. It is recommended the backup is stored on the main drive. 
• There will be downtime during this operation, please plan accordingly
• If upgrading to PostgreSQL 14 and later, the Windows OS must be at least Server 2016

Known limitations

• (Limitation removed in QPI 2.1 | Release Notes) Cannot migrate a 14.17 embedded database to a standalone
• (Limitation removed in QPI 2.1 | Release Notes) Using QPI to upgrade a standalone database or a database previously unbundled with QPI is not supported.
• The installer itself does not provide an automatic rollback feature.

Installing a new Qlik Sense Repository Database using PostgreSQL

1. Run the Qlik PostgreSQL Installer as an administrator 
   
   
2. Click on Install 
   
   
3. Accept the Qlik Customer Agreement 
   
   
4. Set your Local database settings and click Next. You will use these details to connect other nodes to the same cluster. 
   
   
5. Set your Database superuser password and click Next
   
   
6. Set the database installation folder, default: C:\Program Files\PostgreSQL\14

   Do not use the standard Qlik Sense folders, such as C:\Program Files\Qlik\Sense\Repository\PostgreSQL\ and C:\Programdata\Qlik\Sense\Repository\PostgreSQL\.

7. Set the database data folder, default: C:\Program Files\PostgreSQL\14\data

   Do not  use the standard Qlik Sense folders, such as C:\Program Files\Qlik\Sense\Repository\PostgreSQL\ and C:\Programdata\Qlik\Sense\Repository\PostgreSQL\.

8. Review your settings and click Install, then click Finish
   
   
9. Start installing Qlik Sense Enterprise Client Managed. Choose Join Cluster option.
   
   The Qlik PostgreSQL Installer has already seeded the databases for you and has created the users and permissions. No further configuration is needed.
   
   
10. The tool will display information on the actions being performed. Once installation is finished, you can close the installer.  
    
    If you are migrating your existing databases to a new host, please remember to reconfigure your nodes to connect to the correct host. How to configure Qlik Sense to use a dedicated PostgreSQL database 
    

Qlik PostgreSQL Installer - Download Link

Download the installer here.

Qlik PostgreSQL installer Release Notes

Upgrading an existing Qlik Sense Repository Database

The following versions have been tested and verified to work with QPI (1.4.0): 

February 2022 to November 2023.

If you are on any version prior to these, upgrade to at least February 2022 before you begin.  

Qlik Sense November 2022 and later do not support 9.6, and a warning will be displayed during the upgrade.  From Qlik Sense August 2023 a 9.6 update is blocked.

The Upgrade

1. Stop all services on rim nodes 
   
   
2. On your Central Node, stop all services except the Qlik Sense Repository Database 
   
   
   
   
3. Run the Qlik PostgreSQL Installer. An existing Database will be detected. 
   
   
   
   
4. Highlight the database and click Upgrade 
   
5. Read and confirm the (a) Installer Instructions as well as the Qlik Customer Agreement, then click (b) Next.
   
   
   
   
6. Provide your existing Database superuser password and click Next.
   
   
7. Define your Database backup path and click Next.
   
   
   
   
8. Define your Install Location (default is prefilled) and click Next.
   
   
   
   
9. Define your database data path (default is prefilled) and click Next.
   
   
    
10. Review all properties and click Upgrade.
    
    The review screen lists the settings which will be migrated. No manual changes are required post-upgrade.
    
    
    
    
11. The upgrade is completed. Click Close.
     
12. Open the Windows Services Console and locate the Qlik Sense Enterprise on Windows services.
    
    You will find that the Qlik Sense Repository Database service has been set to manual. Do not change the startup method. 
    
    
    
    You will also find a new postgresql-x64-14 service. Do not rename this service. 
    
    
    

     

13. Start all services except the Qlik Sense Repository Database service. 
    
    
14. Start all services on your rim nodes.
    
    
15. Validate that all services and nodes are operating as expected. The original database folder in C:\ProgramData\Qlik\Sense\Repository\PostgreSQL\X.X_deprecated
    

     

16. Uninstall the old Qlik Sense Repository Database service.

    This step is required. Failing to remove the old service will lead the upgrade or patching issues.

    1. Open a Windows File Explorer and browse to C:\ProgramData\Package Cache
       
       
    2. From there, search for the appropriate msi file.
       
       
       
       If you were running 9.6 before the upgrade, search PostgreSQL.msi
       If you were running 12.5 before the upgrade, search PostgreSQL125.msi
       
       
    3. The msi will be revealed.
       
       
    4. Right-click the msi file and select uninstall from the menu.
       
       
       
       
    
    
17. Re-install the PostgreSQL binaries. This step is optional if Qlik Sense is immediately upgraded following the use of QPI. The Sense upgrade will install the correct binaries automatically. 
    

    Failing to reinstall the binaries will lead to errors when executing any number of service configuration scripts. 

    If you do not immediately upgrade:
    
    
    1. Open a Windows File Explorer and browse to C:\ProgramData\Package Cache
       
       
    2. From there, search for the .msi file appropriate for your currently installed Qlik Sense version
       
       
       
       For Qlik Sense August 2023 and later: PostgreSQL14.msi
       Qlik Sense February 2022 to May 2023: PostgreSQL125.msi
       
       
    3. Right-click the file
    4. Click Open file location
       
       
       
       
    5. Highlight the file path, right-click on the path, and click Copy
       
       
       
       
    6. Open a Windows Command prompt as administrator
       
       
    7. Navigate to the location of the folder you copied
       
       Example command line: 
       
       cd C:\ProgramData\Package Cache\{GUID}
       
       Where GUID is the value of the folder name.
       
       
    8. Run the following command depending on the version you have installed: 
       
       Qlik Sense August 2023 and later
       
       msiexec.exe /qb /i "PostgreSQL14.msi" SKIPINSTALLDBSERVICE="1" INSTALLDIR="C:\Program Files\Qlik\Sense"
       
       Qlik Sense February 2022 to May 2023
       
       msiexec.exe /qb /i "PostgreSQL125.msi" SKIPINSTALLDBSERVICE="1" INSTALLDIR="C:\Program Files\Qlik\Sense"
       
       This will re-install the binaries without installing a database. If you installed with a custom directory adjust the INSTALLDIR parameter accordingly. E.g. you installed in D:\Qlik\Sense then the parameter would be INSTALLDIR="D:\Qlik\Sense".
       
       
18. Finalize the process by updating the references to the PostgreSQL binaries paths in the SetupDatabase.ps1 and Configure-Service.ps1 files. For detailed steps, see Cannot change the qliksenserepository password for microservices of the service dispatcher: The system cannot find the file specified.

If the upgrade was unsuccessful and you are missing data in the Qlik Management Console or elsewhere, contact Qlik Support.  

Next Steps and Compatibility with PostgreSQL installers

Now that your PostgreSQL instance is no longer connected to the Qlik Sense Enterprise on Windows services, all future updates of PostgreSQL are performed independently of Qlik Sense. This allows you to act in accordance with your corporate security policy when needed, as long as you remain within the supported PostgreSQL versions.

Your PostgreSQL database is fully compatible with the official PostgreSQL installers from https://www.enterprisedb.com/downloads/postgres-postgresql-downloads. 

How do I upgrade PostgreSQL from here on?

See How To Upgrade Standalone PostgreSQL, which documents the upgrade procedure for either a minor version upgrade (example: 14.5 to 14.8) or a major version upgrade (example: 12 to 14). Further information on PostgreSQL upgrades or updates can be obtained from Postgre directly.

Troubleshooting and FAQ

1. If the installation crashes, the server reboots unexpectedly during this process, or there is a power outage, the new database may not be in a serviceable state. Installation/upgrade logs are available in the location of your temporary files, for example:
   
   C:\Users\Username\AppData\Local\Temp\2
   
   A backup of the original database contents is available in your chosen location, or by default in:
   
   C:\ProgramData\Qlik\Sense\Repository\PostgreSQL\backup\X.X
   
   The original database data folder has been renamed to:
   
   C:\ProgramData\Qlik\Sense\Repository\PostgreSQL\X.X_deprecated
   
   
2. Upgrading Qlik Sense after upgrading PostgreSQL with the QPI tool fails with:
   
   This version of Qlik Sense requires a 'SenseServices' database for multi cloud capabilities. Ensure that you have created a 'SenseService' database in your cluster before upgrading. For more information see Installing and configuring PostgreSQL.
   
   See Qlik Sense Upgrade fails with: This version of Qlik Sense requires a _ database for _.
   
   To resolve this, start the postgresql-x64-XX service.

The information in this article is provided as-is and to be used at own discretion. Depending on tool(s) used, customization(s), and/or other factors ongoing support on the solution below may not be provided by Qlik Support. The video in this article was recorded in a earlier version of QPI, some screens might differ a little bit.

Related Content

Qlik PostgreSQL installer version 1.3.0 Release Notes  
Techspert Talks - Upgrading PostgreSQL Repository Troubleshooting
Backup and Restore Qlik Sense Enterprise documentation
Migrating Like a Boss
Optimizing Performance for Qlik Sense Enterprise
Qlik Sense Enterprise on Windows: How To Upgrade Standalone PostgreSQL
How-to reset forgotten PostgreSQL password in Qlik Sense
How to configure Qlik Sense to use a dedicated PostgreSQL database
Troubleshooting Qlik Sense Upgrades 

When working with Qlik Data Gateway Direct Access, any vulnerability identified by your security team or a third-party security vendor should be handled according to Qlik's standard Product Security and Vulnerability Policy.
 

Before opening a support case, verify the following:

1. Confirm the vulnerability originates from the Direct Access Gateway (DAG) itself.
   
   While Qlik requires the Direct Access Gateway to run on a dedicated server, in practice, additional tools may be installed on the same machine. As a result, vulnerabilities flagged by a scan may not actually originate from the Direct Access Gateway installation folder. Before proceeding, verify that the reported issue is genuinely associated with the Direct Access Gateway product and not with another application sharing the server.
   
   
2. Check whether the issue is already resolved in a newer release.
   
   If a specific component has been flagged, check whether the issue has already been addressed in a more current Direct Access Gateway version. Upgrading and re-testing can confirm whether the fix resolves the finding. The Direct Access Gateway release notes are available here:
   
   Qlik Data Gateway Direct Access Release Notes

Without the information outlined in the Product Security and Vulnerability Policy, Qlik Support will not be able to proceed with an investigation. The vulnerability report typically includes the actual file path, which is what confirms whether or not the issue is, in fact, a Direct Access Gateway issue.

Environment

• Qlik Data Gateway - Direct Access

Configure Kerberos-based Windows Authentication on a Linux machine for the Qlik application user, enabling seamless SQL Server connectivity without manual credential management.

The information in this article is provided as-is and will be used at your discretion. Depending on the tool(s) used, customization(s), and/or other factors, ongoing support on the solution below may not be provided by Qlik Support.

1. Confirm the Qlik user exists on the Linux machine and switch to the with:
   

   id qlik

   sudo su - qlik

   whoami

2. Install the required packages (Kerberos client tools, Microsoft ODBC Driver 18, and sqlcmd)  by running the following command as root:
   
   

   sudo yum install -y krb5-workstation krb5-libs

3. Edit the Kerberos configuration file ( /etc/krb5.conf) as root. Delete all existing content and replace it with the following:
   

   sudo vi /etc/krb5.conf

   
   Configuration content:
   

   includedir /etc/krb5.conf.d/

   [logging]
     default = FILE:/var/log/krb5libs.log
     kdc = FILE:/var/log/krb5kdc.log
     admin_server = FILE:/var/log/kadmind.log
   [libdefaults]
     default_realm = <CUSTOMER_DOMAIN_URL>
     dns_lookup_realm = false
     ticket_lifetime = 24h
     renew_lifetime = 7d
     forwardable = true
     rdns = false
     pkinit_anchors = FILE:/etc/pki/tls/certs/ca-bundle.crt
     dns_canonicalize_hostname = fallback
     qualify_shortname = ""
     default_ccache_name = KEYRING:persistent:%{uid}
   [realms]
     <CUSTOMER_DOMAIN_URL> = {
       kdc = <customer_domain_url>
       admin_server = <customer_domain_url>
     }
     RDLUND.<CUSTOMER_DOMAIN_URL> = {
       kdc = RDLund.qliktech.com
       admin_server = RDLund.qliktech.com
     }
   [domain_realm]
     .qliktech.com = QLIKTECH.COM
     qliktech.com = QLIKTECH.COM

4. Switch to the Qlik user and generate a keytab file using ktutil. The keytab allows kinit to run without a password.

   sudo su - qlik

   ktutil

   1. Inside the ktutil prompt, enter the following commands:
      

      addent -password -p <service_account_user>@<email_domain> -k 1 -e aes256-cts-hmac-sha1-96

      # Enter password when prompted
      

      addent -password -p <service_account_user>@<email_domain>.COM -k 1 -e arcfour-hmac

      # Enter password again when prompted
      

      wkt /home/qlik/<service_account_user>.keytab

      quit

   2. Secure the keytab file:

      chmod 600 /home/qlik/<service_account_user>.keytab

      chown qlik:qlik /home/qlik/<service_account_user>.keytab

   3. Verify the keytab was created correctly:
      

      klist -kt /home/qlik/<service_account_user>.keytab

5. As the Qlik user, test the keytab authentication by destroying any existing tickets and authenticate using the keytab

   kdestroy

   kinit -kt /home/qlik/<service_account_user>.keytab <service_account_user>@QLIKTECH.COM

   klist

   Expected output from klist:
   
   Ticket cache: KCM:XXXX
   Default principal: <service_account_user>@QLIKTECH.COM
   
   Valid starting Expires Service principal
   04/23/2026 04:14:45 04/23/2026 14:14:31 krbtgt/QLIKTECH.COM@QLIKTECH.COM
   
   
6. As the Qlik user, test the SQL connection
   
   Using isql without DSN:
   

   isql -k "Driver={ODBC Driver 18 for SQL Server};Server=<SQL_Server_FQDN>;Database=TEST_AD;Trusted_Connection=yes;TrustServerCertificate=yes;Encrypt=no;" -v

7. Create a ticket renewal script that checks and renews the Kerberos ticket automatically

   vi /home/qlik/renew_krb.sh

   Script content:
   

   #!/bin/bash
   LOG=/home/qlik/krb_renew.log
   echo "$(date) - Checking Kerberos ticket..." >> $LOG
   klist -s
   if [ $? -ne 0 ]; then
     echo "$(date) - Ticket expired, renewing..." >> $LOG
     kinit -kt /home/qlik/<service_account_user>.keytab <service_account_user>@QLIKTECH.COM >> $LOG 2>&1
     if [ $? -eq 0 ]; then
       echo "$(date) - Ticket renewed successfully" >> $LOG
     else
       echo "$(date) - ERROR: Renewal failed!" >> $LOG
     fi
   else
     echo "$(date) - Ticket valid, renewing proactively..." >> $LOG
     kinit -R >> $LOG 2>&1 || kinit -kt /home/qlik/<service_account_user>.keytab <service_account_user>@QLIKTECH.COM >> $LOG 2>&1
   fi

   
   Make the script executable:
   

   chmod +x /home/qlik/renew_krb.sh
   chown qlik:qlik /home/qlik/renew_krb.sh

8. Configure a cron job to run the renewal script every eight hours and on reboot:
   

   sudo crontab -u qlik -e

   
   Add the following lines:
   

   # Renew Kerberos ticket every 8 hours
   0 */8 * * * /home/qlik/renew_krb.sh
   
   # Renew on system reboot
   @reboot /home/qlik/renew_krb.sh

9. Create a systemd service to ensure the ticket is always maintained, even after reboots:
   

   sudo vi /etc/systemd/system/krb5-qlik.service

   
   Service file content:
   

   [Unit]
   Description=Kerberos Ticket Renewal for Qlik User
   After=network.target
   
   [Service]
   Type=simple
   User=qlik
   ExecStart=/bin/bash -c 'while true; do kinit -R || kinit -kt /home/qlik/<service_account_user>.keytab <service_account_user>@QLIKTECH.COM; sleep 28800; done'
   Restart=always
   RestartSec=10
   
   [Install]
   WantedBy=multi-user.target

   
   Enable and start the service:
   

   sudo systemctl daemon-reload
   sudo systemctl enable krb5-qlik
   sudo systemctl start krb5-qlik
   sudo systemctl status krb5-qlik

   The service runs an infinite loop that tries to renew the ticket every eight hours (sleep 28800). If renewal fails, it falls back to getting a fresh ticket from the keytab. It auto-starts on every boot.

10. Run an end-to-end verification by performing the following checks to confirm everything is working correctly:
    
    
    1. Check Kerberos ticket:

       sudo su - qlik

       klist

    2. Check renewal log:
       

       tail -f /home/qlik/krb_renew.log

    3. Check systemd service status:
       

       sudo systemctl status krb5-qlik

    4. Test SQL connection from Qlik Talend Cloud
       
       The following configuration is mandatory when working with Kerberos:
       
       Account properties: username and password
       Database properties: Enter database name manually, checked; Database name; Name
       Internal properties: useTrusted Connection set to true; useTrustedServerCertificate set to true
       
       
       
       
       
       
       

Environment

• Qlik Talend Cloud

Earn Credley badges by completing Qlik Learning paths and earn Achievement Awards on the way. Awards and badges can be shared on LinkedIn to show off your achievements.

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A Qlik Replicate task targeting a file-based endpoint (ADLS, S3, File, or GCS) intermittently:

• Fails to resume cleanly after a target-side error (such as a connection timeout, recoverable error, or task restart)
• Shows missing or incomplete records at the target compared to the source, with no corresponding data error logged
• Logs errors indicating Replicate could not locate an expected temporary (.tmp) file during file post-processing or resume.

These symptoms are most likely to appear in tasks where table or schema names contain a forward slash (/) or a backslash (\).

Resolution

Qlik Replicate provides an internal parameter, enableSlashInTableName, to allow slash characters in table and schema names.

To enable the parameter: 

1. Open the file-based target endpoint settings (ADLS, S3, File, or GCS).
2. Go to the Advanced tab and click Internal Parameters.
3. Add the parameter enableSlashInTableName and set it to Checked.

   If the parameter is not visible or unavailable in your current Qlik Replicate version, upgrade to v2025.11.0.437 or later.

4. Save and restart the task (a full reload may be required).

The data_files folder within the task needs to be empty before resuming. If the folder was not empty, a full reload will be required.

Recommendation for New Task Design

For any new file-based target task (ADLS, S3, File, GCS):

• Avoid transformation rules that introduce / or \ into table or schema names.
• If a folder-like structure is the goal (e.g., grouping tables under a parent folder), review whether the target's native folder-mapping options can achieve this without modifying the table name itself, before resorting to a slash-prefix transformation rule.

Cause

This is a known limitation.

File-based targets map table and schema names directly into the target's folder and file path structure (such as <target_folder>/<schema>/<table>/<file>.csv). If a table or schema name contains a / or \ character, whether from the source system itself or introduced by a Qlik Replicate transformation rule, Qlik Replicate can misinterpret that character as a path separator rather than as part of the object name.

See Limitations and considerations | Using a file as a target.

A common way this condition is introduced unintentionally is through a Global Transformation Rule that renames tables and adds a / (or \) as a prefix or suffix, for example, a rule such as:

Even though this may be intended to create a logical folder grouping at the target, it produces an effective table name containing a slash, which is not supported by the underlying file-target path handling. When Replicate then needs to locate the staged .tmp file for that table, and most commonly during resume after a task restart or a recoverable target error, the malformed path can prevent it from finding the correct file, resulting in a stalled resume or, in some cases, records that are never applied to the target.

Environment

• Qlik Replicate

The Qlik Sense on Windows Content Monitor is intended for Qlik Administrators. Its purpose is to monitor and analyze your Qlik Sense content, including app usage, resource consumption, and data sources. This helps with governance, optimization, and identifying unused content.

Requirements

• Platform: Qlik Sense Enterprise on Windows
• Version: November 2025 onwards 
• Availability: Bundled with installation from version November 2025 onwards
• If you are running previous versions of Qlik Sense Enterprise on Windows, the Content Monitor is also available on Qlik's Downloads page here: Content Monitor (download page)
  • This must be manually installed, and a weekly reload is recommended.
  • The downloaded version is supported from Qlik Sense version Feb 2020.

Core Documentation

All technical details can be found in the two attached documents. These are your primary resources.

Qlik Sense Content Monitor User Guide

• • What it covers: A detailed, sheet-by-sheet explanation of the entire app. It describes what every KPI, chart, and table means for sections like "Weekly Summary," "Snapshot," "Applications," "Sessions," "Task Executions," "File Inventory," and "Infrastructure."

  • Use Case: 

    • Guiding a customer on how to read and interpret the data.

    • Answering customer questions like, "What does the 'Session Concurrency' sheet show?" or "How do I read the 'File Inventory' sheet?"

  • See the attached Qlik Sense Content Monitor User Guide

Configuration Guide

• • What it covers: This is the primary guide for setup and reload issues. It contains:

    • Detailed definitions for all script parameters (e.g., vCentralNodeHostName, vVirtualProxyPrefix, vServerLogFolder).

    • Performance tuning options (e.g., vFileScanMaxDuration, vAppRetrievalLoop, exclusion lists).

    • A "Trial Mode" section is used for troubleshooting initial reload failures.

    • A "Troubleshooting" section.

  • Use Case:

    • New installations.

    • Troubleshootings.

    • Tuning performance for long reloads.

  • See the attached Qlik Sense Content Monitor Configuration Guide

Environment

• Qlik Sense Enterprise on Windows

A security scan may flag the Apache CXF CVE-2026-44618 vulnerability in the following files:

<Talend Remote Engine>/system/org/apache/cxf/cxf-core/3.6.10/cxf-core-3.6.10.jar
<Talend Remote Engine>/system/org/apache/cxf/cxf-core/3.6.8/cxf-core-3.6.8.jar

The Talend Remote Engine does not use the impacted org.apache.cxf:cxf-rt-ws-transfer module and is therefore not affected.

With the Remote Engine 2.14.3 release, Apache CXF will be upgraded to 3.6.11. The release is expected in Q3, 2026. Review the Talend Release Notes for details. 

Internal Investigation ID(s):

SUPPORT-10827

Environment

• Remote Engine

When restarting the services for Qlik Sense Enterprise, bundled extensions disappear from the system. The files are missing from the service cluster extension folder and the apps that use those extension are now showing problems. Reinstalling the extensions works, but at the first reinstall, they get removed again.

Environment

•  Qlik Sense Enterprise on Windows, any

Resolution

This usually happens for obsolete extensions that are no longer supported in the current version of Qlik Sense Enterprise. Usually, the functionality of these extensions was replaced by product features. So, apps should be redesigned to use the new features, in order to have a fully supported functionality.
If they are needed for a transition period, following the following steps will prevent the automated deletion.

1. edit the .qext file for each of the affected extensions (they are in the Service Cluster Folder --> StaticContent ---> Extensions ---> folder name of the extension )
2. replace the line:
   
   "installer": "QlikExtensionBundler"
   
   with
   
   "installer": "none"

By doing this, they will not be detected as unsupported extensions, and therefore not removed.

We all learned the rule in grade school math: getting the right answer doesn't count if you can't show your work. Yet much of enterprise AI asks data teams to bet the quarter on a black box. Qlik Answers takes a different approach. This post goes under the hood on the architecture of the reasoning trace, how we handle schema linking, and how you can audit the engine yourself.

After asking your question, click Show Reasoning.

The Architecture: Semantic Routing and Multi-Agent Orchestration

Every natural language input runs through a multi-agent pipeline. The Answers Agent acts as the orchestrator. Rather than attempting to solve the query in a single zero-shot prompt, it uses semantic routing to decompose the question, map the required context, and dispatch work to specialized execution agents:

• Data Analyst Agent: Handles structured data and text-to-query translation. It navigates your data model, performs schema linking to identify the correct dimensions and measures, constructs the deterministic calculation expressions, and generates the resulting visualizations. For multi-part queries, this agent executes iteratively.
  
  An example of the Data Analyst Agent's reasoning
• Knowledge Base Agent: Manages unstructured sources via a RAG (Retrieval-Augmented Generation) pipeline. It retrieves, chunks, and ranks passages from connected documents and transcripts, handling vector search retrieval rather than structured data queries.

The value of the trace is observability. If a response falls short, you aren't left guessing whether it was a routing failure, a vector retrieval miss, or a bad query formulation. The orchestration view isolates the exact node where the gap occurred, putting control back in the hands of the data architect.

Field Discovery: Beyond Keyword Matching

The hardest problem in text-to-analytics is schema linking; accurately mapping a user's messy natural language to rigid database columns. When the Data Analyst Agent interprets a question, it doesn't rely on basic string matching. It uses semantic indexing.

The engine generates embeddings for the user's intent and maps them against the vector representations of your data model's metadata. The trace exposes this ranked vector retrieval list, showing the confidence score for each candidate field.

Strongly matched fields, where the vector proximity is tight, are selected directly. When two fields occupy a similar semantic space, the trace shows you which one the agent selected and why the competing field was discarded. You are observing the actual selection logic, not a post-hoc summary generated by an LLM.

Grounding: Separating Math from Generation

The highest risk in generative BI is a narrative summary that hallucinates a trend contradicting the chart right below it.

Qlik Answers prevents this by separating deterministic calculation from probabilistic text generation. The narrative is heavily grounded. It is constrained by the payload returned by the underlying associative engine. The trace carries this evidence, which references directly to the UI. Every quantitative claim in the generated text is hard-linked to the specific chart object or calculation it was derived from. You can trace any generated sentence back to the exact measure, dimension, and query formulation that produced it.

Tuning the Semantic Layer

Enterprise data models are inherently messy. No one has perfect metadata. The system is designed to work against the model you have today, and the trace makes it highly tunable.
Because field selection relies on semantic indexing, you can diagnose when the engine misinterprets a proprietary acronym or an obscure technical column name like REV_Q3_ACTL_V2. By viewing the trace, you know which fields would benefit from enriched plain-language descriptions in your semantic layer. You are optimizing the metadata that actually matters to user queries, rather than attempting to boil the ocean and document your entire warehouse.

Why the Trace is a Feature, Not a Log

Plenty of systems write backend debug logs. The difference here is that the reasoning is structured as a first-class UI component: orchestration flow, semantic schema linking, and deterministic evidence grounding, all in one view. It serves the business user who simply wants the answer, the analyst who wants to validate the logic, and the data owner who wants to tune the index. One trace, three jobs, no one forced into another's role. That is what reasoning transparency looks like when it is engineered into the product rather than bolted on after the fact.

A Practical Workflow: Trace, Diagnose, Tune

Here is how this plays out day to day.

A user asks a question, and the answer looks off. Instead of filing a vague "the AI got it wrong" ticket, open the reasoning panel on that response and walk it top to bottom:

1. Check the routing. Did the question go to the Data Analyst Agent or the Knowledge Base Agent? If a numbers question got routed to document retrieval, the fix is usually in how the question was phrased or how your assistant's scope is configured, not in the data model.
2. Check the field selection. Look at the ranked candidate fields and their confidence scores. If the agent picked Gross_Rev when the user meant Net_Revenue, the two fields are sitting too close together in semantic space. Add a plain-language description to the field that was lost, or to both.
3. Check the expression. The trace shows the calculation the engine actually constructed. This is where an analyst confirms the aggregation, filter context, and time grain match the user's intent.
4. Check the grounding. Every claim in the narrative links back to a chart object or calculation. If a sentence doesn't hold up, follow the reference, and you will find exactly which evidence produced it.

Each pass through this loop makes the next answer better, because the fixes land in the semantic layer, where every future query benefits. Teams that treat the trace as a tuning instrument rather than a curiosity see their answer quality compound over weeks, not quarters.

For more information, see Troubleshooting Qlik Answers responses with the reasoning trace .

The Bigger Point

Trust in enterprise AI isn't won with accuracy benchmarks on a slide. It is won the first time a skeptical analyst clicks into a trace, follows the logic, and finds nothing hidden. After that, the conversation changes from "can we trust it" to "how do we make it better." That shift, from auditing to tuning, is the whole reason the reasoning trace exists.

If you want to see it in action, open any answer in Qlik Answers and expand the reasoning view. And if you've used the trace to debug a field mapping or tighten up a semantic layer, share what you found in the comments. The best tuning patterns we know came from customers doing exactly that.

Environment

• Qilk Cloud Analytics
• Qlik Answers

Following a QlikView Server upgrade:

When attempting to generate an NPrinting report by clicking on the the Qlik NPrinting On-Demand Extension in the QV IIS Accesspoint, this may result in the following error:

On-demand Compilation Error: Failed to load resource

The error is only encountered if the QlikView AccessPoint is hosted by Microsoft IIS. The built-in QlikView Ajax AccessPoint is not affected.

Resolution

Please do review these carefully: The problem can be avoided by following the upgrade instructions documented in the >>> QlikView Release Notes  <<<

However, if you have already performed the QlikView Upgrade and did not follow the steps in the release notes above, to remedy the issue post-upgrade:

1. Run the QlikView installer or modify the QlikView installation
2. Choose to repair the installation, repairing only the QlikView IIS Server Settings component

Cause

Inspecting the QlikView server file system will show the following files as missing DLLs:

Location:

• C:\Program Files\QlikView\Server\QlikViewClients\QlikViewAjax\bin

DLLs:

• Microsoft.IdentityModel.Abstractions.dll
• Microsoft.IdentityModel.JsonWebTokens.dll
• Microsoft.IdentityModel.Logging.dll
• Microsoft.IdentityModel.Tokens.dll
• Newtonsoft.Json.dll
• System.IdentityModel.Tokens.Jwt.dll

Internal Investigation ID(s)

SUPPORT-10536

Environment

• QlikView upgraded to September 2025 or a later version
• QlikView IIS Settings service 
• Qlik NPrinting On-demand

By Giacomo Brioschi, Principal Solution Architect, Qlik | Sathisan Vannadil, Senior Partner Solutions Architect, AWS | Sunil Yerkola, Senior Solutions Architect, ISV, AWS.

This guide walks you through the complete setup to bridge Amazon Quick and the Qlik MCP server, enabling real-time access to trusted Data Products with Qlik Trust Score for governed, AI-ready data, and insights and context from the Qlik Analytics Engine, all from within Amazon Quick.

Content

• What you'll need
• Step 1: Configure user roles for MCP access
• Step 2: Assign the new MCP role to users or groups
• Step 3: Create a new OAuth client for Amazon Quick
• Step 4: Add the Qlik MCP server as a connection in Amazon Quick
• Step 5: Create a new chat agent in Quick that uses the Qlik MCP server as an action
• Step 6: The power of Amazon Quick and the Qlik MCP server in action
• Troubleshooting
• Related Content

What you'll need

• An active AWS account
• Amazon Quick setup with user rights to create Connectors
• A Qlik Cloud tenant where you have Tenant Admin rights

Step 1: Configure user roles for MCP access

A Qlik tenant administrator must create (or update) a custom user role that grants the Qlik MCP permission. Without this, users will authenticate successfully but won't be able to execute any MCP tools.

1. In the Administration activity center, click Manage users.
2. Go to the Permissions tab and click Create new.
3. Assign a name to the role (e.g., MCP User) and under Features and actions > Agentic AI, set the MCP permission to Allowed.
4. Click Save.
   
   Setting the MCP permission to Allowed under Features and actions in a Qlik Cloud custom role
   

Step 2: Assign the new MCP role to users or groups

1. In the Administration activity center, click Manage users and go to the All users tab.
2. Click the three-dot menu (...) (A) on the right side of the user's row and select Manage roles (B).
   
   
   
   
3. Assign the MCP role to each user who needs access to the Qlik MCP server. Alternatively, you can assign the new role to a group of users.
   
   
   
   
4. Save your changes.

This can also be done from the Permissions tab. Use the Auto assign drop-down to give permission to all users in your tenant.

Space permissions and Section Access rules still apply. The MCP role grants access to the MCP server itself, but what each user can see and do through MCP is governed by their existing Qlik Cloud permissions. See Qlik MCP server access and permissions for details.

Step 3: Create a new OAuth client for Amazon Quick

The OAuth client authenticates and scopes user access when Quick connects to the Qlik MCP server. A tenant administrator must create an OAuth client for the integration. Once the OAuth client is ready, you can add the Qlik MCP server as a connection in Quick.

Alternatively, you can use OAuth Dynamic Client Registration (DCR), which allows an LLM client to register itself automatically with Qlik Cloud, without the tenant administrator needing to create an OAuth client in advance.

For more information, see how to connect to the Qlik MCP server and how to create OAuth clients for LLM clients in our online help.

Amazon Quick supports two OAuth client types for User authentication: Web (server-side, browser-based redirect flow) and Native (client-side, PKCE-based flow without a backend secret). Choose the one that best fits your security requirements and use case. The following section describes the Web configuration as an example.

1. In your Qlik Cloud tenant, navigate to the Administration activity center.
2. Go to OAuth and click Create new.
3. For the Client type, select Web.
4. Enter a name for the OAuth client (e.g., Amazon Quick MCP) and optionally add a description.
5. Under Scopes, select user_default and mcp:execute.
   
   
   
   Optionally add offline_access to reduce re-authentication frequency to once every 30 days from the default 6-hour expiry.
   
   
6. Under Add redirect URLs, enter the authentication callback URL for Quick as a redirect URI: https://{region}.quicksight.aws.amazon.com/sn/oauthcallback. Replace {region} with your AWS Region (for example, us-east-1).
   
   
   
   
7. Click Create.
8. Immediately copy the Client ID and Client Secret; you'll need both in the next step to configure the integration on the Amazon Quick side, and the secret won't be shown again.

Important, tenant admin must connect first: according to Qlik documentation, the tenant administrator has to be the first user to connect and authenticate with any new MCP client. This establishes tenant level trust between Quick and the Qlik OAuth app. Until the admin completes this first connection, other users' connection attempts will fail. Make sure the admin completes the Quick side integration (Step 4) and authenticates before rolling out access to other users.

Step 4: Add the Qlik MCP server as a connection in Amazon Quick

This step is performed in Amazon Quick, not in Qlik Cloud.

In this final configuration step, you will create an Amazon Quick connection to the Qlik MCP server to access your trusted data foundation. Once this is completed, you will be able to use your Amazon Quick Chat Agents to invoke the available tools to retrieve insights from Qlik. Instructions for adding a remote MCP server connection in Quick will depend on the Quick integration UI.

At a high level:

1. Sign in to Amazon Quick using your web browser.
2. Go to More on the sidebar menu, select Connectors, and click Model Context Protocol within the list of supported connectors.
3. On the Create integration screen, enter the Name and Description for your Qlik MCP integration. For the MCP server endpoint, enter the URL of the Qlik MCP server as https://{your-tenant-hostname}.{your-tenant-region}.qlikcloud.com/api/ai/mcp, as shown in the screenshot below, and make sure to replace {your-tenant-hostname} and {your-tenant-region} with the hostname and region of your Qlik Cloud tenant.
   
   
   
   
4. Choose Next once you're done.
5. In the following Authenticate screen, select User Authentication as the Authentication method, Custom user based OAuth as the Auth Configuration, and enter the following details:
   1. Enter the Client ID and Client Secret that you previously copied from the Qlik OAuth client you created in Step 3. If you chose Native as the OAuth client type, leave Client secret empty.
   2. Token URL allows a client to perform an OAuth flow with Qlik to obtain a token set. Enter your token URL as https://{your-tenant-hostname}.{your-tenant-region}.qlikcloud.com/oauth/token, replacing your-tenant-hostname and your-tenant-region with the hostname and region of your Qlik Cloud tenant. 
   3. The Authorization URL is the URL that the MCP server uses to retrieve the authorization token. Enter your Authorization URL as https://{your-tenant-hostname}.{your-tenant-region}.qlikcloud.com/oauth/authorize, again replacing the tenant hostname and region placeholders.
      
      
      
      
6. Click Create and Continue.
7. Authenticate by signing into your Qlik Cloud tenant when prompted.
8. Click Approve to authorise Quick to access your Qlik Cloud data.

   Data sharing notice: by clicking Approve, you enable the Qlik MCP server to share your Qlik Cloud data with Amazon Quick. Quick is not managed by Qlik, and your data will be stored and processed under AWS's control. Check your organisation's AI data sharing policies before proceeding.

   
   
   
9. In Manage Tools & Permissions, you can list the tools available for read and write operations, and in the final section, Publishing the connection, you have the option to share this connection with your team members, e.g., with users or a group of users who can access the Qlik MCP server via Amazon Quick.
   
   In this example, the connection has been shared with a group called Qlik Test.
   
   
   
   
10. Click Publish to create the connection.
11. If the integration creation has been successful, you should be able to see the list of actions (tools) available within the connector, as shown in the snapshot below:
    
    
    
    For a complete list of Qlik tools available, see Qlik MCP tools | help.qlik.com.

Step 5: Create a new chat agent in Quick that uses the Qlik MCP server as an action

With the connector in place, the tools that the Qlik MCP server provides are now available within Amazon Quick. Chat Agents in Amazon Quick help users explore data, analyse information, and take actions through open-ended natural language conversations, now including Qlik's capabilities. Agents are configured with specific goals, knowledge sources, and connected tools, and can evolve from simple question answering to orchestrating complex workflows. You can use chat agents to:

• Generate content and provide answers through natural language conversations
• Analyse and summarise information from connected spaces, dashboards, topics, datasets, and uploaded files
• Invoke actions to perform predefined steps for consistent, repeatable outcomes

For more information, see Create, customize, and deploy AI-powered chat agents in Amazon Quick | docs.aws.

Let's explore together how to create an Agent in Amazon Quick that uses the Qlik MCP server connection.

1. When you are in Amazon Quick, go to More on the left sidebar and click Chat Agents, then select Create a chat agent from the central part of the UI.
   
   
   
   
2. Describe in your own words how you want the agent to behave; Amazon Quick will use that to automate the setup for you. This step is optional and can be skipped in favour of manual configuration.
3. In the Configure chat agent window, make sure that within Actions, the Qlik MCP integration connection configured in Step 3 of this guide is linked; otherwise, link it manually.
4. Once you're done, click Launch chat agent.
   
   

Step 6: The power of Amazon Quick and the Qlik MCP server in action

Now you're ready to harness the full power of Qlik's trusted Data Products and Analytics Engine within Amazon Quick workflows through the newly created agent. What once required switching between tools can now happen in a single, unified experience.

Troubleshooting

Problem: Non-admin users can't connect
Likely root cause: Tenant admin hasn't completed first connection yet (see note in Step 3)

Problem: OAuth callback fails
Likely root cause: Region placeholder in the redirect URL doesn't match your Quick instance's actual region

Problem: User connects but can't access specific apps or data
Likely root cause: Space permissions or Section Access rules are restricting access; this is by design

Problem: The user is not able to use Qlik tools from the Amazon Quick Chat Agent
Likely root cause: Make sure the Qlik MCP server connection is added to the Chat Agent's available actions

Related Content

• Deploying and administering Qlik MCP server
• Qlik MCP server access and permissions
• Connecting to the Qlik MCP server
• OAuth2 clients Qlik Cloud supports
• Integration demo

Qlik Reporting-printed PDFs or Excel exports may not display fonts as expected, specifically when custom fonts are imported using CSS.

Resolution

This is expected behavior: 

• Custom CSS styling applied to sheets is not included in reports; see Customizing sheet styling with CSS | Qlik Cloud for details and recommendations.
• Qlik Reporting uses a set of open-source fonts and will automatically replace an unknown or unavailable font with a preset one; see Qlik Cloud Reporting and font support.
• Importing, for example, Google Fonts through custom CSS for use in reports and exports is not supported.

Related Content

• Customizing sheet styling with CSS | Qlik Cloud 
• Qlik Cloud Reporting and font support
• Fonts do not display properly in reports | Qlik NPrinting

Internal Investigation ID(s)

00463549

Environment

• Qlik Cloud

The Model Context Protocol (MCP) is an open standard that lets AI assistants connect to external data sources and tools.

This article provides step-by-step instructions for connecting Antigravity to the Qlik MCP server in any tenant.

Step 1: Create the OAuth client to be used by Antigravity

1. In the Qlik Cloud Administration activity center, go to OAuth.
2. Click Create new and use the following values:
   • Client type: Web
   • Name and Description: Name and describe your client
   • Add the required Scopes: user_default and mcp:execute
   • Redirect url: https://antigravity.google/oauth-callback
3. Click Create and copy the ClientID and Secret 

   Do not forget to save the client secret. Qlik will not show it again.

Step 2: Create the MCP connection in Antigravity

1. In Antigravity, open Antigravity IDE by clicking Open IDE
2. Click the ellipses (...) menu in the top right corner
3. Click MCP Servers
   
   
   
   
4. Click Manage MCP servers (A) in the top right corner and View raw config (B) to open your mcp_config.json
   
   
   
   
   
   
5. Enter your configuration in the following format:
   
   

   {
    "mcpServers" : {
      "qlik-mcp": {
        "oauth": {
          "clientId": "00000000",
          "clientSecret": "00000000" 
        },
        "serverUrl": "https://YOURTENANT.qlikcloud.com/api/ai/mcp" 
      }
    }
   }

   
   
   
   
6. Save your configuration
7. Return to Antigravity, go to Settings > Customization, navigate to installed MCP servers, and click Refresh
8. Click Authenticate 
   
   
   
   
9. A redirect takes you to the Antigravity URL; copy the Authorization code
   
   
   
   
10. Paste the code and click Submit
    
    
    
    
    
    

The connection is now available in a conversation.

Environment

• Qlik MCP
• Qlik Cloud

This article provides answers to the most frequent questions asked about Qlik MCP.

For the more general Qlik Answers FAQ, see Qlik Answers Agentic Analytics FAQ.

How do I troubleshoot my connection to the LLM I’m using?

Qlik Model Context Protocol (MCP) server integrates Qlik Cloud into your LLM workflow, allowing you to work with Qlik Cloud using your LLM without having to leave your LLM. Connection issues will often be tied to misconfiguration.

• Before you begin, review Deploying and administering Qlik MCP server and Connecting to the Qlik MCP server
• If you are using ChatGPT, verify that you are on the correct ChatGPT plan (see Connecting to ChatGPT)
• Typically, OAuth authentication issues with your client will be caused by:
  • Incorrect Remote MCP server URL (<your tenant URL>/api/ai/mcp)
  • Wrong Client ID
    
• If an error code is returned, reconnect; if reconnecting does not resolve the issue, submit the code returned by MCP to your LLM vendor for further troubleshooting

How do I troubleshoot my app if I am not getting the answers I expect?  

In a case where you do not get the response you expect based on the sources, or you receive an error:

• Ask again in case of an error (see the appendix for possible error codes)
• Rewrite the prompt (see Best practices for chatting with Qlik Answers)

Has your app been prepared for Qlik Answers?

• Best practices for preparing applications for Qlik Answers
• Writing master item descriptions for Qlik Answers

How much does the Qlik MCP cost?

For now, Qlik MCP will continue to be priced based on current models for the number of questions asked. You get capacity at corresponding levels in Standard, Premium, and Enterprise editions, as well as Qlik Sense Enterprise SaaS. There is currently no additional cost for structured data questions or task automation requests; a question is a question.

Use of the MCP server consumes questions when Qlik is accessed using Tool Calls. A Tool Call is a request made by the LLM to interact with Qlik's capabilities, such as, but not limited to, querying databases, calling APIs, or performing computations. These are typically visible in the LLM's log.

For Qlik's MCP server, 5 Tool calls consume 1 question. More questions may be purchased for expanded use cases.

See Pricing and the Qlik MCP server product description for details.

Qlik’s pricing does not include your chosen LLM subscription or usage, which will need to be paid separately.

Does Qlik MCP work with my existing Qlik apps?

Yes. Qlik MCP works on top of existing Qlik Sense applications and uses the same data, logic, and security model.

But to get the best experience, apps should be prepared beforehand:

• Best practices for preparing applications for Qlik Answers
• Writing master item descriptions for Qlik Answers

What capacity limitations do we need to consider?

Your Qlik Cloud subscription determines the quota of questions asked by users. If you are licensed for Qlik Answers, both MCP and Qlik Answers will use your monthly question capacity. See Administering Qlik MCP server. 

What happens when we reach a capacity limit?

Question capacity quotes are per month and reset every month. When you hit your limit, users can no longer ask questions until the next month. Overage is only allowed, depending on your subscription. For more information, see Qlik MCP server product description.

For more information on overage, see Overage. 

How do we turn off features?

Features can be turned off for individual users through user scopes.

1. Go to your Administration Center
2. Go to Manage Users
3. Switch to the Permissions tab
4. Click User Defaults and change the scope as required

See Control access to AI features.