How can I check if an experiment is currently active on a specific site?

Use the `list_experiments` tool to get a summary of all experiments, which includes their current status (e.g., 'ACTIVE', 'PAUSED') and assigned site IDs.

Can I see the defined variations for a particular experiment?

Yes, the `list_variations` tool takes an experiment ID and returns all variants configured for that test, along with their metadata.

Is it possible to list targeting rules and segments?

Absolutely. You can use the `list_segments` and `list_targeting_rules` tools to inspect how your traffic is being allocated across your experimentation ecosystem.

Kameleoon MCP Server for OpenAI Agents SDK 10 tools — connect in under 2 minutes

Name: Kameleoon
Availability: InStock
Author: Vinkius

openai.github.io/openai-agents-python/mcp

Built by Vinkius GDPR 10 Tools SDK

The OpenAI Agents SDK enables production-grade agent workflows in Python. Connect Kameleoon through Vinkius and your agents gain typed, auto-discovered tools with built-in guardrails. no manual schema definitions required.

Get MCP Server for AI Agents

ASK AI ABOUT THIS MCP SERVER

Open in ChatGPT Open in Claude Open in Perplexity

Vinkius supports streamable HTTP and SSE.

python

import asyncio
from agents import Agent, Runner
from agents.mcp import MCPServerStreamableHttp

async def main():
    # Your Vinkius token. get it at cloud.vinkius.com
    async with MCPServerStreamableHttp(
        url="https://edge.vinkius.com/[YOUR_TOKEN_HERE]/mcp"
    ) as mcp_server:

        agent = Agent(
            name="Kameleoon Assistant",
            instructions=(
                "You help users interact with Kameleoon. "
                "You have access to 10 tools."
            ),
            mcp_servers=[mcp_server],
        )

        result = await Runner.run(
            agent, "List all available tools from Kameleoon"
        )
        print(result.final_output)

asyncio.run(main())

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DLPData protection

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Ed25519Audit chain

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Stream every event to Splunk, Datadog, or your own webhook in real-time

* Every MCP server runs on Vinkius-managed infrastructure inside AWS - a purpose-built runtime with per-request V8 isolates, Ed25519 signed audit chains, and sub-40ms cold starts optimized for native MCP execution. See our infrastructure

About Kameleoon MCP Server

Empower your AI agents to control your Kameleoon experimentation platform. This MCP server enables seamless management of experiments, variations, and audience segments directly from natural language interfaces.

The OpenAI Agents SDK auto-discovers all 10 tools from Kameleoon through native MCP integration. Build agents with built-in guardrails, tracing, and handoff patterns. chain multiple agents where one queries Kameleoon, another analyzes results, and a third generates reports, all orchestrated through Vinkius.

What you can do

Experiment Control — List all active experiments and drill down into specific configurations and metadata
Variation Management — Inspect A/B variations and their statuses across different digital properties
Site Inventory — Query all sites and properties registered in your account to ensure correct environment targeting
Audience Segmentation — List defined audience segments and targeting rules used for precise traffic allocation
Results Triggering — Request latest results reports to analyze experiment performance on the fly

The Kameleoon MCP Server exposes 10 tools through the Vinkius. Connect it to OpenAI Agents SDK in under two minutes — no API keys to rotate, no infrastructure to provision, no vendor lock-in. Your configuration, your data, your control.

How to Connect Kameleoon to OpenAI Agents SDK via MCP

Follow these steps to integrate the Kameleoon MCP Server with OpenAI Agents SDK.

Install the SDK

Run pip install openai-agents in your Python environment

Replace the token

Replace [YOUR_TOKEN_HERE] with your Vinkius token from cloud.vinkius.com

Run the script

Save the code above and run it: python agent.py

Explore tools

The agent will automatically discover 10 tools from Kameleoon

Why Use OpenAI Agents SDK with the Kameleoon MCP Server

OpenAI Agents SDK provides unique advantages when paired with Kameleoon through the Model Context Protocol.

Native MCP integration via `MCPServerSse`, pass the URL and the SDK auto-discovers all tools with full type safety

Built-in guardrails, tracing, and handoff patterns let you build production-grade agents without reinventing safety infrastructure

Lightweight and composable: chain multiple agents and MCP servers in a single pipeline with minimal boilerplate

First-party OpenAI support ensures optimal compatibility with GPT models for tool calling and structured output

Kameleoon + OpenAI Agents SDK Use Cases

Practical scenarios where OpenAI Agents SDK combined with the Kameleoon MCP Server delivers measurable value.

Automated workflows: build agents that query Kameleoon, process the data, and trigger follow-up actions autonomously

Multi-agent orchestration: create specialist agents. one queries Kameleoon, another analyzes results, a third generates reports

Data enrichment pipelines: stream data through Kameleoon tools and transform it with OpenAI models in a single async loop

Customer support bots: agents query Kameleoon to resolve tickets, look up records, and update statuses without human intervention

Kameleoon MCP Tools for OpenAI Agents SDK (10)

These 10 tools become available when you connect Kameleoon to OpenAI Agents SDK via MCP:

create_experiment

Requires a name and a site ID. Create a new experiment

get_experiment

Get details for a specific experiment

get_experiment_results

This is an asynchronous process in the Kameleoon API. Request a results report for an experiment

get_site

Get details for a specific site

list_custom_data

List custom data dimensions

list_experiments

Use this to monitor campaign statuses and identify active experiments. List all experiments in Kameleoon

list_segments

List audience segments

list_sites

List all sites in the account

list_targeting_rules

List targeting rules

list_variations

) associated with a specific experiment ID. List variations for an experiment

Example Prompts for Kameleoon in OpenAI Agents SDK

Ready-to-use prompts you can give your OpenAI Agents SDK agent to start working with Kameleoon immediately.

"Show me all active experiments in my Kameleoon account."

"What are the variations for experiment ID '12345'?"

"List all sites registered in my Kameleoon profile."

Troubleshooting Kameleoon MCP Server with OpenAI Agents SDK

Common issues when connecting Kameleoon to OpenAI Agents SDK through the Vinkius, and how to resolve them.

MCPServerStreamableHttp not found

Ensure you have the latest version: pip install --upgrade openai-agents

Agent not calling tools

Make sure your prompt explicitly references the task the tools can help with.

Kameleoon + OpenAI Agents SDK FAQ

Common questions about integrating Kameleoon MCP Server with OpenAI Agents SDK.

How does the OpenAI Agents SDK connect to MCP?

Use MCPServerSse(url=...) to create a server connection. The SDK auto-discovers all tools and makes them available to your agent with full type information.