Can I rerun a failed test suite using my agent?

Yes. Use the `rerun_test_run` tool by providing the ID of the failed execution. Your agent will trigger a fresh run using the exact same configuration and return the new Test Run ID for tracking.

How do I see the screenshots from a specific test failure?

Ask your agent to `get_test_result` for a specific result ID. If the test was configured to capture visuals, your agent will retrieve the screenshot links along with diagnostic logs and error messages.

Can I check which browser versions were used in a test run?

Absolutely. Use the `list_execution_environments` tool for your project. Your agent will return detailed OS, browser, and device configurations used for executions, ensuring you have the full technical context.

Katalon TestOps (AI Test Management) MCP Server for Pydantic AI 10 tools — connect in under 2 minutes

Name: Katalon TestOps (AI Test Management)
Availability: InStock
Author: Vinkius

ai.pydantic.dev/mcp

Built by Vinkius GDPR 10 Tools SDK

Pydantic AI brings type-safe agent development to Python with first-class MCP support. Connect Katalon TestOps (AI Test Management) through the 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 Katalon TestOps (AI Test Management) "
            "(10 tools)."
        ),
    )

    result = await agent.run(
        "What tools are available in Katalon TestOps (AI Test Management)?"
    )
    print(result.data)

asyncio.run(main())

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* Every MCP server runs on Vinkius-managed infrastructure inside AWS - a purpose-built runtime with per-request V8 isolates, Ed25519 signed audit chains, and sub-40ms cold starts optimized for native MCP execution. See our infrastructure

About Katalon TestOps (AI Test Management) MCP Server

Connect your Katalon TestOps account to any AI agent and take full control of your AI-powered test management and quality orchestration through natural conversation.

Pydantic AI validates every Katalon TestOps (AI Test Management) tool response against typed schemas, catching data inconsistencies at build time. Connect 10 tools through the 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

Execution Orchestration — List all test runs and trigger immediate re-executions of specific suites to verify bug fixes directly from your agent
Quality Analytics — Retrieve detailed test outcome summaries, including pass/fail rates, execution durations, and error stack traces
Diagnostic Inspection — Deep-dive into individual test results to extract application logs, error messages, and visual screenshots for rapid debugging
Environment Audit — List configured execution environments to understand target OS, browser, and device distributions across your projects
Release Management — Monitor defined software releases and track aggregated test run statistics to ensure build quality before deployment
Project CRM — Navigate across multiple Katalon projects and retrieve detailed metadata including team assignments and suite counts securely

The Katalon TestOps (AI Test Management) MCP Server exposes 10 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 Katalon TestOps (AI Test Management) to Pydantic AI via MCP

Follow these steps to integrate the Katalon TestOps (AI Test Management) 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 10 tools from Katalon TestOps (AI Test Management) with type-safe schemas

Why Use Pydantic AI with the Katalon TestOps (AI Test Management) MCP Server

Pydantic AI provides unique advantages when paired with Katalon TestOps (AI Test Management) 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 Katalon TestOps (AI Test Management) integration code

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

Dependency injection system cleanly separates your Katalon TestOps (AI Test Management) connection logic from agent behavior for testable, maintainable code

Katalon TestOps (AI Test Management) + Pydantic AI Use Cases

Practical scenarios where Pydantic AI combined with the Katalon TestOps (AI Test Management) MCP Server delivers measurable value.

Type-safe data pipelines: query Katalon TestOps (AI Test Management) with guaranteed response schemas, feeding validated data into downstream processing

API orchestration: chain multiple Katalon TestOps (AI Test Management) tool calls with Pydantic validation at each step to ensure data integrity end-to-end

Production monitoring: build validated alert agents that query Katalon TestOps (AI Test Management) and output structured, schema-compliant notifications

Testing and QA: use Pydantic AI's dependency injection to mock Katalon TestOps (AI Test Management) responses and write comprehensive agent tests

Katalon TestOps (AI Test Management) MCP Tools for Pydantic AI (10)

These 10 tools become available when you connect Katalon TestOps (AI Test Management) to Pydantic AI via MCP:

get_project

Get full details of a Katalon project

get_test_result

Get full details of a single Katalon test result

get_test_run

Get full details of a Katalon test run

list_execution_environments

List execution environments in a Katalon project

list_project_builds

Returns build identifier names, IDs, and the count of associated test runs. List software builds in a Katalon project

list_project_releases

Returns release names, scheduled dates, and aggregated test run statistics. List defined releases in a Katalon project

list_projects

Returns project names, IDs, and descriptions. List all projects on Katalon TestOps

list_test_results

Returns durations, statuses, and error messages. List detailed test results within a test run

list_test_runs

Returns run IDs, pass/fail status, total counts, and execution durations. List test runs within a Katalon project

rerun_test_run

Returns the newly created test run ID. Re-run an existing Katalon test run

Example Prompts for Katalon TestOps (AI Test Management) in Pydantic AI

Ready-to-use prompts you can give your Pydantic AI agent to start working with Katalon TestOps (AI Test Management) immediately.

"List the last 5 test runs in project 'E-commerce API' (ID: 123)"

"Rerun test run ID 986"

"What are the active releases defined in project 123?"

Troubleshooting Katalon TestOps (AI Test Management) MCP Server with Pydantic AI

Common issues when connecting Katalon TestOps (AI Test Management) to Pydantic AI through the Vinkius, and how to resolve them.

MCPServerHTTP not found

Update: pip install --upgrade pydantic-ai

Katalon TestOps (AI Test Management) + Pydantic AI FAQ

Common questions about integrating Katalon TestOps (AI Test Management) 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 Katalon TestOps (AI Test Management) MCP integration works identically with OpenAI, Anthropic, Google, or any supported provider.