How to Use the Xray (Test Management) MCP in Google ADK

Q: Can the Google ADK list all test sets for Xray (Test Management)?

Yes, listtestsets gives you a complete manifest of all defined test groups. Your agent can then process these lists to build out an execution sequence.

Q: Does the Google ADK allow retrieving list of available Xray (Test Management) tests?

You can use listxraytests to get a full roster of all test cases. This data feeds directly into your agent's ability to plan and recommend testing strategies.

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Connect Xray (Test Management) MCP to Google ADK

Create your Vinkius account to connect Xray (Test Management) 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.

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Setup Xray (Test Management) with Google ADK

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Get granular test execution details.

The `get_execution_details` tool pulls specific, detailed results for any given test run. You see exactly what happened—pass/fail status and associated metrics. This works great when your agent needs to analyze failure patterns across massive datasets in BigQuery.

List all configured test plans.

Using `list_test_plans`, your agent gets a full list of every test plan defined. This lets it compare the current testing scope against historical or mandated plans. It's critical for ensuring compliance when you're running complex, multi-stage CI/CD workflows.

Get details on specific test cases.

The `get_test_details` tool retrieves all comprehensive information about one Xray test case. Your agent can read the requirements, prerequisites, and expected outcomes. This helps ground generative reasoning by providing concrete data points from Jira's quality assurance platform.

Setup guide

Set up Xray (Test Management) 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 Xray (Test Management) 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="Xray (Test Management)_agent",
    model="gemini-2.0-flash",
    instruction="You have access to Xray (Test Management) tools via MCP.",
    tools=mcp_tools,
)

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Common questions about Xray (Test Management) MCP in Google ADK

Your agent interacts through a structured toolset that supports long-context reasoning. The integration means your agent can use Xray data to inform decisions within the broader Gemini ecosystem.

Yes, `list_test_sets` gives you a complete manifest of all defined test groups. Your agent can then process these lists to build out an execution sequence.

This server touches test plans, individual test runs, and project settings. The core data is the structured information about how tests are designed and executed within Jira.

You can use `list_xray_tests` to get a full roster of all test cases. This data feeds directly into your agent's ability to plan and recommend testing strategies.

The server touches specific Jira project configuration data, including field mappings. Your agent can use this information while respecting the boundaries of that metadata.

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