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.

Zendesk QA (Klaus) MCP Server for Pydantic AI 7 tools — connect in under 2 minutes

Name: Zendesk QA (Klaus)
Availability: InStock
Author: Vinkius

ai.pydantic.dev/mcp

Built by Vinkius GDPR 7 Tools SDK

Pydantic AI brings type-safe agent development to Python with first-class MCP support. Connect Zendesk QA (Klaus) through Vinkius and every tool is automatically validated against Pydantic schemas. catch errors at build time, not in production.

Get MCP Server for AI Agents

ASK AI ABOUT THIS MCP SERVER

Open in ChatGPT Open in Claude Open in Perplexity

Vinkius supports streamable HTTP and SSE.

python

import asyncio
from pydantic_ai import Agent
from pydantic_ai.mcp import MCPServerHTTP

async def main():
    # Your Vinkius token. get it at cloud.vinkius.com
    server = MCPServerHTTP(url="https://edge.vinkius.com/[YOUR_TOKEN_HERE]/mcp")

    agent = Agent(
        model="openai:gpt-4o",
        mcp_servers=[server],
        system_prompt=(
            "You are an assistant with access to Zendesk QA (Klaus) "
            "(7 tools)."
        ),
    )

    result = await agent.run(
        "What tools are available in Zendesk QA (Klaus)?"
    )
    print(result.data)

asyncio.run(main())

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About Zendesk QA (Klaus) MCP Server

Connect your Zendesk QA (formerly Klaus) account to any AI agent to automate your customer service quality assurance workflows. This MCP server enables your agent to export quality scores, search for reviewed conversations, and import external ticket data directly from natural language interfaces.

Pydantic AI validates every Zendesk QA (Klaus) tool response against typed schemas, catching data inconsistencies at build time. Connect 7 tools through Vinkius and switch between OpenAI, Anthropic, or Gemini without changing your integration code. full type safety, structured output guarantees, and dependency injection for testable agents.

What you can do

Review Extraction — List all quality assurance reviews and internal quality scores (IQS) account-wide or by workspace
Workspace Management — List all available workspaces to organize your QA processes and review assignments
Conversation Discovery — Search for specific customer interactions to identify which ones have been graded
Data Integration — Import conversation data and agent profiles from external platforms for grading in Zendesk QA
Record Maintenance — Permanently remove ticket data from the QA platform via simple commands

The Zendesk QA (Klaus) MCP Server exposes 7 tools through the Vinkius. Connect it to Pydantic AI in under two minutes — no API keys to rotate, no infrastructure to provision, no vendor lock-in. Your configuration, your data, your control.

How to Connect Zendesk QA (Klaus) to Pydantic AI via MCP

Follow these steps to integrate the Zendesk QA (Klaus) MCP Server with Pydantic AI.

Install Pydantic AI

Run pip install pydantic-ai

Replace the token

Replace [YOUR_TOKEN_HERE] with your Vinkius token

Run the agent

Save to agent.py and run: python agent.py

Explore tools

The agent discovers 7 tools from Zendesk QA (Klaus) with type-safe schemas

Why Use Pydantic AI with the Zendesk QA (Klaus) MCP Server

Pydantic AI provides unique advantages when paired with Zendesk QA (Klaus) through the Model Context Protocol.

Full type safety: every MCP tool response is validated against Pydantic models, catching data inconsistencies before they reach your application

Model-agnostic architecture. switch between OpenAI, Anthropic, or Gemini without changing your Zendesk QA (Klaus) integration code

Structured output guarantee: Pydantic AI ensures tool results conform to defined schemas, eliminating runtime type errors

Dependency injection system cleanly separates your Zendesk QA (Klaus) connection logic from agent behavior for testable, maintainable code

Zendesk QA (Klaus) + Pydantic AI Use Cases

Practical scenarios where Pydantic AI combined with the Zendesk QA (Klaus) MCP Server delivers measurable value.

Type-safe data pipelines: query Zendesk QA (Klaus) with guaranteed response schemas, feeding validated data into downstream processing

API orchestration: chain multiple Zendesk QA (Klaus) tool calls with Pydantic validation at each step to ensure data integrity end-to-end

Production monitoring: build validated alert agents that query Zendesk QA (Klaus) and output structured, schema-compliant notifications

Testing and QA: use Pydantic AI's dependency injection to mock Zendesk QA (Klaus) responses and write comprehensive agent tests

Zendesk QA (Klaus) MCP Tools for Pydantic AI (7)

These 7 tools become available when you connect Zendesk QA (Klaus) to Pydantic AI via MCP:

delete_qa_tickets

Remove specific ticket data from the QA platform

import_qa_tickets

Import conversation data into Zendesk QA for review

import_qa_users

Sync agents and managers into Zendesk QA

list_all_reviews

List all quality assurance reviews account-wide

list_qa_workspaces

Use this to identify workspace IDs for exporting reviews. List all Zendesk QA workspaces

list_workspace_reviews

List reviews for a specific workspace

search_qa_conversations

Search for conversations in Zendesk QA

Example Prompts for Zendesk QA (Klaus) in Pydantic AI

Ready-to-use prompts you can give your Pydantic AI agent to start working with Zendesk QA (Klaus) immediately.

"List all my Zendesk QA workspaces."

"Show recent QA reviews for the 'English Support' workspace (ID: '123')."

"Search for reviewed conversations associated with client email 'user@example.com'."

Troubleshooting Zendesk QA (Klaus) MCP Server with Pydantic AI

Common issues when connecting Zendesk QA (Klaus) to Pydantic AI through the Vinkius, and how to resolve them.

MCPServerHTTP not found

Update: pip install --upgrade pydantic-ai

Zendesk QA (Klaus) + Pydantic AI FAQ

Common questions about integrating Zendesk QA (Klaus) MCP Server with Pydantic AI.

How does Pydantic AI discover MCP tools?

Create an MCPServerHTTP instance with the server URL. Pydantic AI connects, discovers all tools, and generates typed Python interfaces automatically.

Does Pydantic AI validate MCP tool responses?

Yes. When you define result types as Pydantic models, every tool response is validated against the schema. Invalid data raises a clear error instead of silently corrupting your pipeline.

Can I switch LLM providers without changing MCP code?

Absolutely. Pydantic AI abstracts the model layer. your Zendesk QA (Klaus) MCP integration works identically with OpenAI, Anthropic, Google, or any supported provider.