How to Use the Contentsquare MCP in AutoGen

Q: How do AutoGen agents share Contentsquare data?

They pass the JSON output from tools like listsegments through the conversation thread. Every agent in the group has access to the same context.

Let your AutoGen agents debate UX strategy using real-time data from Contentsquare.

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Connect Contentsquare MCP to AutoGen

Create your Vinkius account to connect Contentsquare to AutoGen 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 Contentsquare with AutoGen

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Debate UX metrics using AutoGen

Assign one agent to fetch data via `get_metrics` and another to critique the findings. AutoGen agents discuss these stats to reach a consensus on site optimization. This setup ensures your decisions are backed by hard numbers. One agent flags the bounce rate while the other proposes a fix.

Negotiate exports via AutoGen

Have your agents decide when to run `create_export_job` based on current project needs. One agent might request a data pull, while a security agent checks the constraints. They verify the job status using `list_export_jobs` before proceeding. This keeps your data pipeline orderly.

Audit zonings with AutoGen agents

Use `list_zonings` to provide agents with the context needed to discuss site interaction. Agents compare these zonings against site goals to spot issues. They can cross-reference this with `list_projects` to ensure they are looking at the right domain. The result is a decision backed by multiple perspectives.

Setup guide

Set up Contentsquare MCP in AutoGen

Prerequisites

Python 3.10+ installed
autogen-ext[mcp] package
Active Vinkius subscription with a valid endpoint token

1

Install AutoGen with MCP
Run pip install "autogen-ext[mcp]" autogen-agentchat. The MCP extension includes mcp_server_tools for stateless tool access.
2

Fetch tools from the MCP
Call mcp_server_tools(SseServerParams(url=...)) with your Vinkius endpoint. Replace [YOUR_TOKEN_HERE] with your token from cloud.vinkius.com.
3

Run your agent
Pass the tools to AssistantAgent and call agent.run(). The agent invokes Contentsquare tools and returns structured results.

agent.py

from autogen_ext.tools.mcp import SseServerParams, mcp_server_tools
from autogen_agentchat.agents import AssistantAgent
from autogen_ext.models.openai import OpenAIChatCompletionClient

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

tools = await mcp_server_tools(server_params)

agent = AssistantAgent(
    name="Contentsquare_assistant",
    model_client=OpenAIChatCompletionClient(model="gpt-4o"),
    tools=tools,
)

result = await agent.run("List recent Contentsquare data")
print(result.messages[-1].content)

Get your connection token →

Prerequisites

Python 3.10+ installed
autogen-ext[mcp] + autogen-agentchat
Active Vinkius subscription with a valid endpoint token

1

Install dependencies
Same packages as above. McpWorkbench is ideal when your agent needs stateful sessions across multiple tool calls.
2

Use McpWorkbench as context manager
Wrap your agent in async with McpWorkbench(...) to maintain shared state and resources. The workbench manages the full MCP session lifecycle.
3

Run with workbench
Pass workbench=workbench to your agent. State is preserved across multiple tool calls within the same session.

agent.py

from autogen_ext.tools.mcp import McpWorkbench, SseServerParams
from autogen_agentchat.agents import AssistantAgent
from autogen_ext.models.openai import OpenAIChatCompletionClient

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

async with McpWorkbench(server_params) as workbench:
    agent = AssistantAgent(
        name="Contentsquare_assistant",
        model_client=OpenAIChatCompletionClient(model="gpt-4o"),
        workbench=workbench,
    )

    result = await agent.run("List recent Contentsquare data")
    print(result.messages[-1].content)

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 Contentsquare. 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

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Common questions about Contentsquare MCP in AutoGen

They pass the JSON output from tools like `list_segments` through the conversation thread. Every agent in the group has access to the same context.

Yes, the agents decide which tool to call based on the task. They can fetch metrics or list projects as part of their deliberation.

We use an MCP adapter that turns our tool definitions into agent-compatible functions. The agents see them as native capabilities.

Yes, our V8 sandbox ensures the server environment is isolated and wiped clean after your session ends.

Demographic limits are processed in memory during the agent discussion. We do not persist your raw user data on our servers.

Use it with your favorite AI tools

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