How to Use the Zendesk QA (Klaus) MCP in Google ADK

Q: How can I get all my departmental QA review summaries using Zendesk QA (Klaus) and Google ADK?

You first run listqaworkspaces to identify the scope. Then, you pass those IDs into listworkspacereviews. This gives your agent a structured way to pull all necessary metrics.

Q: Is it possible with Zendesk QA (Klaus) and Google ADK to search for conversations in BigQuery?

The MCP Server handles the initial search via searchqaconversations. Your agent can then take the resulting data and feed it into BigQuery for long-context analysis within your Google Cloud environment.

Q: What steps are necessary to sync new personnel using Zendesk QA (Klaus) and Google ADK?

You use the importqausers tool. Your agent runs this, which syncs all relevant agents and managers into the Zendesk QA system, keeping your user data accurate.

Q: If I need to delete historical records with Zendesk QA (Klaus) and Google ADK, which tool works?

You use deleteqatickets. This function allows your agent to remove specific ticket data from the QA platform, ensuring compliance and clean datasets.

Build Enterprise QA Pipelines and Process Zendesk QA (Klaus) Data with Google ADK.

See Vinkius in Action

Works with every AI agent you already use

…and any MCP-compatible client

MCP Servers - Free for Subscribers

Connect Zendesk QA (Klaus) MCP to Google ADK

Create your Vinkius account to connect Zendesk QA (Klaus) to Google ADK and route execution through our secure gateway. The platform manages server hosting, runtime updates, and security layers. Configuration requires no manual server provisioning.

GDPR Free for Subscribers

Setup Zendesk QA (Klaus) with Google ADK

Ask AI about this MCP

ChatGPT

Claude

Perplexity

Exporting All Quality Assurance Reviews

The `list_all_reviews` tool gathers every quality assurance review account-wide, giving you a full picture of support performance. Once you have the general list, use `list_qa_workspaces` to get the IDs needed for deep dives. For specific departmental reviews, run `list_workspace_reviews`. This lets your agent isolate and pull all metrics tied only to one workspace.

Finding Specific Service Conversations

Need to track down a conversation from six months ago? Use `search_qa_conversations`. Your Google ADK agent can query the Zendesk QA platform using this tool. It searches across all available records. This function is key for audit trails. Instead of guessing, your agent finds exactly what was said and when it happened.

Managing User Syncs and Importing Data

Keep your user base current by running `import_qa_users`. This syncs agents and managers into the QA system. If you need to update ticket records, `import_qa_tickets` lets your agent push new conversation data directly in. When finished with old data or needing a fresh start, the `delete_qa_tickets` tool cleans up specific tickets from the platform.

Setup guide

Set up Zendesk QA (Klaus) MCP in Google ADK

Prerequisites

Python 3.10+ installed
google-adk package (pip install google-adk)
Active Vinkius subscription with a valid endpoint token

1

Install Google ADK

Run pip install google-adk to install the Agent Development Kit. MCP support is included via the McpToolset class.
2

Connect via SSE transport

Use McpToolset.from_server() with SseServerParams pointing to your Vinkius endpoint. Replace [YOUR_TOKEN_HERE] with your token from cloud.vinkius.com.
3

Create an LlmAgent

Pass the returned mcp_tools list directly to LlmAgent(tools=mcp_tools). The ADK maps each MCP tool to a native Gemini function call — no manual schema definitions required.
4

Run with any Gemini model

The agent works with any Gemini model (gemini-2.0-flash, gemini-2.5-pro, etc.). Copy the full example on the right to get started with Zendesk QA (Klaus) tools in your ADK agent.

agent.py

from google.adk.agents import LlmAgent
from google.adk.tools.mcp_tool.mcp_toolset import McpToolset
from google.adk.tools.mcp_tool.mcp_session_manager import SseServerParams

# Connect to the MCP via SSE
mcp_tools, exit_stack = await McpToolset.from_server(
    connection_params=SseServerParams(
        url="https://edge.vinkius.com/[YOUR_TOKEN_HERE]/mcp"
    )
)

# Create your agent with auto-discovered tools
agent = LlmAgent(
    name="Zendesk QA (Klaus)_agent",
    model="gemini-2.0-flash",
    instruction="You have access to Zendesk QA (Klaus) tools via MCP.",
    tools=mcp_tools,
)

Get your connection token →

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.

Why Choose Vinkius

Vinkius connects your tools to AI with real-time monitoring and automatic cost savings — all from one dashboard.

Connect Zendesk QA (Klaus) now

Real-time monitoring

Live

visibility into every interaction

Connect your favorite tools to your AI and see exactly what's happening — every request, every response, in real time.

Built-in savings

60%

lower AI costs

Vinkius compresses data between your apps and your AI automatically. Lower bills every month — no configuration required.

Single dashboard

One

place for every integration

Every tool your AI connects to, managed from a single screen. One account, complete control.

Common questions about Zendesk QA (Klaus) MCP in Google ADK

You first run `list_qa_workspaces` to identify the scope. Then, you pass those IDs into `list_workspace_reviews`. This gives your agent a structured way to pull all necessary metrics.

The MCP Server handles the initial search via `search_qa_conversations`. Your agent can then take the resulting data and feed it into BigQuery for long-context analysis within your Google Cloud environment.

You use the `import_qa_users` tool. Your agent runs this, which syncs all relevant agents and managers into the Zendesk QA system, keeping your user data accurate.

This server handles review metrics, ticket data, user synchronization, and conversation history. Your agent can manage the lifecycle of all these core components.

You use `delete_qa_tickets`. This function allows your agent to remove specific ticket data from the QA platform, ensuring compliance and clean datasets.

Use it with your favorite AI tools

Connect this server to Cursor, Claude, VS Code, and more.

OpenAI Agents SDK sdk-python

Google ADK sdk-python

Pydantic AI sdk-python

Vercel AI SDK sdk-typescript