How to Use the Katalon TestOps (AI Test Management) MCP in AutoGen

Let your AutoGen agents debate test failures and coordinate releases using live Katalon TestOps metrics.

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Connect Katalon TestOps (AI Test Management) MCP to AutoGen

Create your Vinkius account to connect Katalon TestOps (AI Test Management) to AutoGen and route execution through our secure gateway. The platform manages server hosting, runtime updates, and security layers. Configuration requires no manual server provisioning.

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Setup Katalon TestOps (AI Test Management) with AutoGen

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Coordinate release debates with AutoGen agents

A QA agent can fetch test metrics using `get_test_run` to start a multi-agent debate on whether a build is ready for production. A release agent reviews active schedules via `list_project_releases` to provide the required context. They debate whether the current pass rate is acceptable. This consensus-driven approach keeps bad code out of production by forcing agents to negotiate using raw data from this MCP Server.

Automate triage using specialized AutoGen roles

When a build fails, the monitoring agent pulls the logs using `get_test_result` to initiate a collaborative triage session. It then asks the infrastructure agent to check `list_execution_environments` to see if a runner went offline. If the infrastructure agent confirms the environment was stable, the monitoring agent can decide to trigger `rerun_test_run`. This division of labor makes automated debugging highly structured and reliable.

Resolve testing conflicts via multi-agent consensus

When a test fails, your agents can run `list_test_runs` to analyze historical trends and debate whether to trigger a retry. This prevents blind test retries from masking real bugs. They weigh the risk of deploying a false positive against the cost of a delayed release, making a calculated decision. Your agents use real data to resolve the conflict before taking action.

Setup guide

Set up Katalon TestOps (AI Test Management) MCP in AutoGen

Prerequisites

Python 3.10+ installed
autogen-ext[mcp] package
Active Vinkius subscription with a valid endpoint token

1

Install AutoGen with MCP
Run pip install "autogen-ext[mcp]" autogen-agentchat. The MCP extension includes mcp_server_tools for stateless tool access.
2

Fetch tools from the MCP
Call mcp_server_tools(SseServerParams(url=...)) with your Vinkius endpoint. Replace [YOUR_TOKEN_HERE] with your token from cloud.vinkius.com.
3

Run your agent
Pass the tools to AssistantAgent and call agent.run(). The agent invokes Katalon TestOps (AI Test Management) tools and returns structured results.

agent.py

from autogen_ext.tools.mcp import SseServerParams, mcp_server_tools
from autogen_agentchat.agents import AssistantAgent
from autogen_ext.models.openai import OpenAIChatCompletionClient

server_params = SseServerParams(
    url="https://edge.vinkius.com/[YOUR_TOKEN_HERE]/mcp"
)

tools = await mcp_server_tools(server_params)

agent = AssistantAgent(
    name="Katalon TestOps (AI Test Management)_assistant",
    model_client=OpenAIChatCompletionClient(model="gpt-4o"),
    tools=tools,
)

result = await agent.run("List recent Katalon TestOps (AI Test Management) data")
print(result.messages[-1].content)

Get your connection token →

Prerequisites

Python 3.10+ installed
autogen-ext[mcp] + autogen-agentchat
Active Vinkius subscription with a valid endpoint token

1

Install dependencies
Same packages as above. McpWorkbench is ideal when your agent needs stateful sessions across multiple tool calls.
2

Use McpWorkbench as context manager
Wrap your agent in async with McpWorkbench(...) to maintain shared state and resources. The workbench manages the full MCP session lifecycle.
3

Run with workbench
Pass workbench=workbench to your agent. State is preserved across multiple tool calls within the same session.

agent.py

from autogen_ext.tools.mcp import McpWorkbench, SseServerParams
from autogen_agentchat.agents import AssistantAgent
from autogen_ext.models.openai import OpenAIChatCompletionClient

server_params = SseServerParams(
    url="https://edge.vinkius.com/[YOUR_TOKEN_HERE]/mcp"
)

async with McpWorkbench(server_params) as workbench:
    agent = AssistantAgent(
        name="Katalon TestOps (AI Test Management)_assistant",
        model_client=OpenAIChatCompletionClient(model="gpt-4o"),
        workbench=workbench,
    )

    result = await agent.run("List recent Katalon TestOps (AI Test Management) data")
    print(result.messages[-1].content)

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 Katalon TestOps. 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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Common questions about Katalon TestOps (AI Test Management) MCP in AutoGen

Use the autogen-ext package to load the server tools via the Streamable HTTP transport. Pass the adapted tools list directly to your AssistantAgent constructor during setup.

Yes. Your agents can discuss the historical pass rates of a project using the project details tools before deciding whether to invoke a rerun to validate a build.

The MCP adapter handles all schema translations automatically. This allows your agents to directly interact with tools like test runs and project builds without manual mapping.

Yes. The adapter supports both stdio and Streamable HTTP transports, making it easy to run the server locally or host it securely on Vinkius.

Your environment details, project IDs, and build names are never exposed or stored. All tool calls, including listing execution environments, run within sandboxed V8 isolates that destroy execution context immediately after completion.

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