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

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Connect Katalon TestOps (AI Test Management) MCP to CrewAI

Create your Vinkius account to connect Katalon TestOps (AI Test Management) to CrewAI 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 CrewAI

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Deploy QA Agent Teams via MCP Server

Assigning `list_test_runs` and `list_test_results` to a dedicated monitoring agent allows continuous tracking of your project health. This agent constantly polls your Katalon environment for new execution durations and pass/fail statuses. When a test suite finishes, it hands the raw data off to an analyst agent for review. You stop relying on static dashboards. The crew operates hierarchically, with the monitor agent acting as the trigger for the rest of your autonomous QA operations. It identifies anomalies in test execution times via the MCP Server before they become critical bottlenecks.

Isolate Defects with CrewAI

Investigating failures requires `get_test_run` and `get_test_result` to pull specific error messages from the Katalon API. Your analyst agent takes the failed run ID from the monitor and digs into the exact test case that broke. It reads the error string and formulates a hypothesis about the underlying code defect. The shared memory in CrewAI means the analyst remembers similar failures from past runs it pulled from the MCP Server. It cross-references current errors with historical data from `list_project_builds`. Your development team receives a highly specific root cause summary instead of a generic failure alert.

Execute Reruns Without Human Input

Granting `rerun_test_run` to an action agent enables your crew to fix transient pipeline issues on its own. If the analyst agent determines a failure was caused by a network timeout, it instructs the action agent to fire off a retry. The action agent secures the new run ID and updates the crew on the status. You define the rules of engagement. By restricting write operations to specific roles, you ensure the crew only restarts tests under strict conditions. The agents also check `list_execution_environments` to verify they run the suite on the correct infrastructure.

Setup guide

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

Prerequisites

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

1

Install CrewAI
Run pip install crewai to install the framework. MCP support is built-in via the mcps parameter.
2

Add the MCP URL to your agent
Pass your Vinkius endpoint directly to the mcps list. Replace [YOUR_TOKEN_HERE] with your token from cloud.vinkius.com. CrewAI handles tool discovery and caching automatically.
3

Kick off your crew
Create a Crew with your agent and tasks. Call crew.kickoff() — the agent will automatically invoke Katalon TestOps (AI Test Management) tools as needed.

crew.py

from crewai import Agent, Task, Crew

agent = Agent(
    role="Katalon TestOps (AI Test Management) Analyst",
    goal="Access and analyze Katalon TestOps (AI Test Management) data via MCP.",
    backstory="Expert analyst with direct Katalon TestOps (AI Test Management) access.",
    mcps=[
        "https://edge.vinkius.com/[YOUR_TOKEN_HERE]/mcp"
    ],
)

task = Task(
    description="List recent Katalon TestOps (AI Test Management) transactions",
    agent=agent,
    expected_output="A summary of recent activity",
)

crew = Crew(agents=[agent], tasks=[task])
result = crew.kickoff()
print(result)

Get your connection token →

Prerequisites

Python 3.10+ installed
crewai + crewai-tools packages
Active Vinkius subscription with a valid endpoint token

1

Install dependencies
Run pip install crewai crewai-tools. The MCPServerAdapter handles lifecycle management and tool conversion.
2

Connect with MCPServerAdapter
Use MCPServerAdapter as a context manager with SseServerParameters pointing to your Vinkius endpoint. The adapter automatically manages connection lifecycle.
3

Assign tools and run
Pass the returned mcp_tools to your agent's tools parameter. The adapter converts MCP tools to native BaseTool objects compatible with all CrewAI agents.

crew.py

from crewai import Agent, Task, Crew
from crewai_tools import MCPServerAdapter
from mcp import SseServerParameters

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

with MCPServerAdapter(server_params) as mcp_tools:
    agent = Agent(
        role="Katalon TestOps (AI Test Management) Analyst",
        goal="Access and analyze Katalon TestOps (AI Test Management) data via MCP.",
        backstory="Expert analyst with direct Katalon TestOps (AI Test Management) access.",
        tools=mcp_tools,
    )

    task = Task(
        description="List recent Katalon TestOps (AI Test Management) transactions",
        agent=agent,
        expected_output="A summary of recent activity",
    )

    crew = Crew(agents=[agent], tasks=[task])
    result = crew.kickoff()
    print(result)

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 CrewAI

Pass the Vinkius endpoint URL into the mcps array when defining your agent. CrewAI automatically discovers the available tools and assigns them to that specific role.

Yes. You can provide the same MCP Server connection to different agents, or use the tool_filter to give one agent read access and another agent write access.

A monitoring agent can be scheduled to periodically execute list_test_runs. Once it detects a completed status, it passes that context to the next agent in your sequential process.

CrewAI handles context windows effectively. You should instruct your agents to use list_test_results first, identify the specific failures, and then use get_test_result to drill down, saving token space.

The MCP Server transmits your release schedules, environment names, and pass/fail metrics. Vinkius manages this connection via stateless, ephemeral containers, ensuring no data persists after your agents finish their tasks.

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