Zendesk QA MCP. Find, grade, and export support quality scores.
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Zendesk QA (Klaus) connects your AI client directly to quality assurance data. It lets you list all internal quality scores, search specific customer conversations, import external tickets and user profiles, or delete old records from Zendesk QA.
What your AI agents can do
Delete qa tickets
Removes specific, targeted ticket records permanently from the QA platform.
Import qa tickets
Imports conversation data into Zendesk QA so reviewers can score them.
Import qa users
Syncs agent and manager user profiles from external sources into Zendesk QA.
Get a full list of all internal quality scores (IQS) across your entire account or within specific workspaces.
Search the QA platform for customer interactions using criteria like client email or ticket ID to see which ones have been reviewed.
Import conversation data and agent user profiles from outside systems so they can be graded in Zendesk QA.
List all available workspaces to organize your QA efforts or identify the correct IDs for specific review exports.
Permanently remove ticket data from the QA platform using a direct command, which is useful for compliance.
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Zendesk QA (Klaus): 7 Tools for Ticket & Review Management
Use these tools to manage review listings, search conversations, and orchestrate ticket data imports across your Zendesk QA platform.
019d75c1delete qa tickets
Removes specific, targeted ticket records permanently from the QA platform.
019d75c1import qa tickets
Imports conversation data into Zendesk QA so reviewers can score them.
019d75c1import qa users
Syncs agent and manager user profiles from external sources into Zendesk QA.
019d75c1list all reviews
Lists all internal quality assurance reviews across the entire account scope.
019d75c1list qa workspaces
Retrieves a list of every available workspace ID in Zendesk QA, which is needed before exporting specific review groups.
019d75c1list workspace reviews
Lists the quality assurance reviews belonging only to one specified workspace.
019d75c1search qa conversations
Searches for conversations within Zendesk QA based on criteria like client email or ticket number.
Choose How to Get Started
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Build Your Own
Turn any API into an MCP. Import a spec, define Agent Skills, or deploy with MCPFusion.
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- Use this MCP plus 4,700+ others, all in one place
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- Works with Claude, ChatGPT, Cursor, and more
- New servers added to the catalog every week
What you can do with this MCP connector
Listen, this MCP server plugs your AI client right into Zendesk QA data. It lets your agent do more than just talk; it handles the actual quality assurance workflow—listing reviews, finding specific customer chats, syncing user data, and cleaning up records.
Your agent first needs to know what's available in the system. You can use list_qa_workspaces to pull a list of every workspace ID Zendesk QA maintains. That’s crucial because if you wanna export or focus on reviews for a specific group, you gotta have that correct ID.
Once you know where to look, your agent can read the data. You've got two ways to get review scores: run list_all_reviews to pull every single internal quality assurance score across the whole account scope, or if you know which area you wanna check, you can use list_workspace_reviews to limit the results only to one specified workspace.
Need to track down a specific conversation? You don't gotta scroll through pages of logs. Your agent can run search_qa_conversations, letting you pinpoint customer interactions based on criteria like a client’s email or an existing ticket number, so you know exactly which chats have been reviewed.
For feeding data into the system, your AI client handles syncing external sources. You can use import_qa_tickets to bring conversation data directly into Zendesk QA; this lets reviewers score interactions that live outside the platform initially. Similarly, if you gotta update who's working in the system, import_qa_users syncs agent and manager profiles from other systems right into Zendesk QA.
And when it’s time to wipe the slate clean—maybe for compliance or just getting rid of old junk—you can permanently delete targeted ticket records using delete_qa_tickets. That command removes specific data points right out of the QA platform. It keeps your record books tight and focused on what matters now.
How Zendesk QA MCP Works
- 1 Subscribe to this server and enter your Zendesk Subdomain and API Token.
- 2 Tell your AI client what you need—for example, 'List all reviews in the English Support workspace.'
- 3 The agent executes the necessary tool call and returns structured data (like a list of scores or conversation IDs).
The bottom line is that your AI client talks directly to Zendesk QA, letting you manage quality reports without using the web UI.
Who Is Zendesk QA MCP For?
QA Managers and Support Leads who are tired of manually running reports across multiple dashboards. If your job involves tracking agent performance or analyzing support ticket trends, this server cuts out the clicks.
Uses list_all_reviews to export aggregated quality scores for weekly reporting and uses list_qa_workspaces to scope reports by department.
Quickly searches for specific agent reviews using search_qa_conversations when they suspect an issue with a particular client interaction.
Uses import_qa_tickets to synchronize new ticket batches from other systems into Zendesk QA for grading, keeping data sources aligned.
What Changes When You Connect
- Export full review data instantly. Use
list_all_reviewsto pull every internal quality score account-wide for deep reporting without manual exports. - Pinpoint conversations fast. Instead of sifting through dashboards, use
search_qa_conversationsto find any ticket graded by a specific client email or ID. - Keep your data synced and clean. Use
import_qa_ticketsto batch-add new interactions ready for review, making sure no recent support chat gets missed. - Organize efforts by workspace. Run
list_qa_workspacesfirst, then uselist_workspace_reviewsto limit your search scope and keep reports clean. - Maintain compliance easily. If data needs purging, run
delete_qa_ticketsto permanently remove records from the QA platform.
Real-World Use Cases
Quarterly Audit of Agent Performance
A QA Manager needs to report on all performance metrics for Q3. They run list_all_reviews via their agent, which pulls thousands of records into a structured output. The manager then filters that data by date range and department, creating an audit report in minutes instead of hours.
Investigating a Specific Client Complaint
A Support Lead gets a complaint about poor service for 'user@example.com'. They ask their agent to search_qa_conversations using that email. The agent immediately returns the last three graded tickets, allowing the lead to pull up specific scores and coach the agent right away.
Onboarding New Data Sources
The Operations Team gets a new integration providing ticket data from an external system. They use import_qa_tickets via their agent, batch-loading 500 conversations into Zendesk QA so the full team can start scoring them immediately.
Restructuring Departments
A manager is splitting a large support group. They first run list_qa_workspaces to see all current environments, identify which ones belong to the new division, and then use those IDs to scope their reporting using list_workspace_reviews.
The Tradeoffs
Trying to list everything at once
Asking the agent simply to 'Give me all review data.' This is too vague and might result in a massive, unmanageable dump of unstructured text.
→
First, use list_qa_workspaces to get IDs. Then, tell your agent: 'Use this workspace ID [ID] with the list_workspace_reviews tool.' This limits the scope and keeps the output clean.
Editing ticket data manually
Attempting to change a score or update metadata directly through chat. The system only allows reading, searching, importing, or deleting.
→
If you need to remove a record entirely for compliance, use the delete_qa_tickets tool and provide the specific ticket IDs. Don't try to modify data; delete it.
Assuming all users are synced
Running reports that include agent names but getting errors because some agents aren't linked in Zendesk QA.
→
Before running any reporting, first call the import_qa_users tool. This syncs your current list of managers and agents into the platform so the data is ready.
When It Fits, When It Doesn't
Use this server if your core need is managing the lifecycle (creation, reading, deletion) of structured QA metrics within Zendesk QA. If you're constantly running reports on scores or searching for specific tickets, this is what you need.
Don't use it if you simply want to analyze the raw text of a conversation without scoring it first—that requires different tools. Also, don't expect the server to fix underlying data quality issues; if your data is messy, you still have to clean it up before running import_qa_tickets. This tool gives access points, not solutions for poor input.
Independent Platform Disclaimer: Vinkius is an independent platform and is not affiliated with, endorsed by, sponsored by, verified by, or otherwise authorized by Zendesk QA (Klaus). All third-party trademarks, logos, and brand names are the property of their respective owners. Their use on this website is strictly for informational purposes to identify service compatibility and interoperability.
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Works with Claude, ChatGPT, Cursor, and more
The Model Context Protocol standardizes how applications expose capabilities to LLMs. Instead of operating in isolation, your AI gains direct access to external platforms, live data, and real-world actions through secure, standardized connections.
This server provides 7 capabilities that interface natively with Claude, ChatGPT, Cursor, and any MCP client. No middleware. No custom integration required.
Available Capabilities
Manually pulling QA reports across workspaces takes forever.
Today, if your team needs to see the quality scores for 'English Support' and then compare it to 'Technical Escalations,' you have to jump into two different reporting dashboards. You copy a handful of metrics, paste them into a spreadsheet, and hope you didn't miss any workspace or date range.
With this MCP server, your agent handles the scoping. You just ask for reviews across specific workspaces, and the system pulls all the scores—from `list_workspace_reviews` to `list_all_reviews`—and gives them back in a structured format you can use immediately.
Zendesk QA (Klaus) MCP Server: Manage reviews with natural language.
The manual steps that disappear are the opening of multiple tabs, running segmented reports for different teams, and the subsequent copy/paste cycle into a summary document. It’s tedious, error-prone work done before your coffee is cold.
Now, you tell your agent to 'List all reviews for the last month.' The server runs `list_all_reviews` and returns clean, actionable data. That's it. You get the answer instantly.
Common Questions About Zendesk QA MCP
How do I list all my Zendesk QA workspaces using list_qa_workspaces? +
Just ask your agent to call list_qa_workspaces. It returns a comprehensive list of every workspace ID available in your account. This is the first step if you need to run targeted reports.
Can I use search_qa_conversations to find tickets by date range? +
The search_qa_conversations tool searches for conversations based on criteria like client email or ticket ID. While you can narrow it down, the primary filters are not purely time-based.
What is the difference between list_all_reviews and list_workspace_reviews? +
Use list_all_reviews when you need one single report covering every workspace. Use list_workspace_reviews when your focus is locked onto a specific department or area, identified by its unique workspace ID.
Does importing users require me to run import_qa_users first? +
Yes. Before you use any review tools on agent performance, running import_qa_users ensures that the agents and managers are synced into Zendesk QA, guaranteeing accurate reporting.
Before I use `import_qa_tickets`, what credentials does my AI client need to authorize data entry? +
You must provide the Zendesk Subdomain and a valid QA API Token. These tokens allow your agent to write and modify records on your behalf. The connection uses OAuth 2.0 scope permissions, ensuring that only necessary write access is granted.
If I run `list_all_reviews` and there are thousands of results, does the tool handle pagination? +
Yes, the function supports paginated responses for large datasets. The initial response will include a next_page_token. Your AI client must pass this token in subsequent calls to retrieve all available review batches.
How does `import_qa_tickets` handle malformed or invalid conversation data? +
The API validates required fields before processing the batch. If a ticket fails validation, it returns an error code and logs the specific field failure for that record, allowing the rest of your successful imports to complete.
When I use `delete_qa_tickets`, what is the data retention policy within Zendesk QA? +
Deleted tickets are flagged immediately but remain in an archived state. They are recoverable for 30 days before being permanently purged from the platform.
How do I find my Workspace ID? +
Use the list_qa_workspaces tool to retrieve a comprehensive list of all workspaces in your account along with their unique IDs.
Can I export reviews for a specific date range? +
Yes, you can provide a params string (e.g., fromDate=2023-01-01&toDate=2023-01-31) to the list reviews tools to filter by date.
What is the difference between the Export and Import APIs? +
The Export API is for retrieving QA results (scores and reviews), while the Import API is for pushing conversation data and user profiles into the platform for review.
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