How to Use the Kameleoon MCP in Google ADK

Q: How do I integrate the Kameleoon MCP Server into Google ADK?

Use the McpToolset class and provide your server URL. Add this toolset to your LlmAgent definition to give it access to all 10 Kameleoon tools.

Q: Does Google ADK work well with Kameleoon experiment results?

It does. The agent invokes getexperimentresults and processes the report within the same context window, making it easy to compare test outcomes against your other metrics.

Q: Can I filter which tools the Google ADK agent sees?

Yes. Use the toolnames filter when setting up your McpToolset to restrict the agent to only the specific functions you need.

Q: How do I fetch variations in Google ADK for Kameleoon?

You call listvariations with the ID of your experiment. The tool returns the variation details which the agent can then use to inform its next step.

Connect Google ADK to your testing infrastructure using the Kameleoon MCP Server.

See Vinkius in Action

Works with every AI agent you already use

…and any MCP-compatible client

MCP Servers - Free for Subscribers

Connect Kameleoon MCP to Google ADK

Create your Vinkius account to connect Kameleoon 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.

GDPR Free for Subscribers

Setup Kameleoon with Google ADK

Ask AI about this MCP

ChatGPT

Claude

Perplexity

Manage Kameleoon experiments in Google ADK

You can trigger `create_experiment` and `get_experiment` directly from your agent workflows. This allows you to programmatically manage site tests alongside your BigQuery data pipelines.

Targeting and segmentation for Google ADK agents

Use `list_targeting_rules` and `list_segments` to pull your current audience setup into your agent's context. This helps your agent verify that targeting logic aligns with the data stored in your Google Cloud environment.

Extract site data via Google ADK

Run `list_sites` and `get_site` to map your entire account structure. Your agent can then iterate through these sites to pull custom data dimensions using `list_custom_data` for deep analysis.

Setup guide

Set up Kameleoon 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 Kameleoon 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="Kameleoon_agent",
    model="gemini-2.0-flash",
    instruction="You have access to Kameleoon tools via MCP.",
    tools=mcp_tools,
)

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 Kameleoon. 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.

Why Choose Vinkius

Vinkius connects your tools to AI with real-time monitoring and automatic cost savings — all from one dashboard.

Connect Kameleoon now

Real-time monitoring

Live

visibility into every interaction

Connect your favorite tools to your AI and see exactly what's happening — every request, every response, in real time.

Built-in savings

60%

lower AI costs

Vinkius compresses data between your apps and your AI automatically. Lower bills every month — no configuration required.

Single dashboard

One

place for every integration

Every tool your AI connects to, managed from a single screen. One account, complete control.

Common questions about Kameleoon MCP in Google ADK

Use the `McpToolset` class and provide your server URL. Add this toolset to your `LlmAgent` definition to give it access to all 10 Kameleoon tools.

It does. The agent invokes `get_experiment_results` and processes the report within the same context window, making it easy to compare test outcomes against your other metrics.

Yes. Use the tool_names filter when setting up your `McpToolset` to restrict the agent to only the specific functions you need.

You call `list_variations` with the ID of your experiment. The tool returns the variation details which the agent can then use to inform its next step.

The server uses token-based auth for every request. It only accesses your experiment metadata and targeting configuration, ensuring no raw visitor data leaves your controlled environment.

Use it with your favorite AI tools

Connect this server to Cursor, Claude, VS Code, and more.

OpenAI Agents SDK sdk-python

Google ADK sdk-python

Pydantic AI sdk-python

Vercel AI SDK sdk-typescript