How to Use the Mabl (AI-Powered Test Automation) MCP in Google ADK

Q: How do I initialize the Mabl (AI-Powered Test Automation) MCP Server using Google ADK?

You install the Google ADK package and initialize the McpToolset class with the server's HTTP endpoint. Pass this toolset directly into your LlmAgent constructor to expose the testing tools to Gemini.

Q: Can I filter which Mabl (AI-Powered Test Automation) tools are exposed to Google ADK?

Yes, you can restrict tool access. The McpToolset class accepts an optional list of tool names, allowing you to expose only mb.triggerplan and mb.getexecution while hiding workspace metadata tools.

Q: How does the Mabl (AI-Powered Test Automation) MCP toolset handle environment variables in Google ADK?

The toolset queries your environments using mb.listenvs. It returns environment variables and target URLs directly to the agent, allowing Gemini to pass them as parameters to other Google Cloud services.

Connect Google ADK enterprise agents to Mabl to automate end-to-end testing and analyze results using Gemini long-context reasoning.

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Connect Mabl (AI-Powered Test Automation) MCP to Google ADK

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Setup Mabl (AI-Powered Test Automation) with Google ADK

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Analyze testing trends with Gemini and Google ADK

Combine the power of Gemini's massive context window with your testing data. Your agent can call `mb.list_executions` to pull hundreds of historical test runs directly into its reasoning loop. This lets the agent spot flaky tests and systemic regressions across your entire application. It can correlate these patterns with deployment logs stored in Google Cloud to pinpoint exactly when a bug crept in.

Trigger targeted test plans on deployment events

Run your tests automatically when code changes using this MCP Server. The agent uses `mb.list_plans` to find the correct test suite and executes it using `mb.trigger_plan` as soon as a Cloud Build trigger completes. Querying `mb.list_envs` allows the agent to dynamically match the deployment target with the active testing environment.

Inspect workspace metadata and application details

Keep your testing pipeline organized without manual registry updates. The agent calls `mb.workspace_info` to verify permissions and retrieve organizational details before starting any test runs. It then uses `mb.get_app` to inspect target URLs and API endpoints. This ensures your agent always knows exactly where to direct its testing efforts, even when endpoints change.

Setup guide

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

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Independent Platform Disclaimer: Vinkius is an independent platform and is not affiliated with, endorsed by, sponsored by, verified by, or otherwise authorized by Mabl. 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 Mabl (AI-Powered Test Automation) MCP in Google ADK

You install the Google ADK package and initialize the `McpToolset` class with the server's HTTP endpoint. Pass this toolset directly into your `LlmAgent` constructor to expose the testing tools to Gemini.

Yes, you can restrict tool access. The `McpToolset` class accepts an optional list of tool names, allowing you to expose only `mb.trigger_plan` and `mb.get_execution` while hiding workspace metadata tools.

The toolset queries your environments using `mb.list_envs`. It returns environment variables and target URLs directly to the agent, allowing Gemini to pass them as parameters to other Google Cloud services.

Absolutely. Gemini can ingest hundreds of historical test results from `mb.list_executions` at once. This makes it incredibly effective at identifying long-term flakiness that short-context models would miss.

Your Mabl API keys and application endpoints are isolated within Vinkius's secure sandboxed environment. The integration acts as a secure MCP bridge, ensuring that raw test screenshots and sensitive database URLs are never cached or exposed to public networks.

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