How to Use the Chi-Square Test Engine MCP in AutoGen

Agents that argue over math. AutoGen uses the Chi-Square Test Engine to reach consensus on your data.

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Connect Chi-Square Test Engine MCP to AutoGen

Create your Vinkius account to connect Chi-Square Test Engine 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 Chi-Square Test Engine with AutoGen

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Perplexity

Consensus-driven statistical analysis

Deploy a team of agents where one acts as the analyst and another as the validator. The analyst calls `calculate_chi_square`, and the validator checks the result against the contingency table. This debate ensures that your statistical conclusions are rock solid. The agents negotiate until they agree on the interpretation of the test results.

Automated tool negotiation in AutoGen

Your agents decide which tools to use based on the complexity of the data. When they encounter categorical sets, they call the `calculate_chi_square` tool to get the facts. This removes the burden of manual tool selection. The agents figure out the right way to approach the math without your constant intervention.

Multi-agent statistical debugging

Have one agent propose a hypothesis and another use the `calculate_chi_square` tool to test it. If the p-value doesn't support the claim, the agents adjust their strategy. This iterative process leads to better outcomes. You get a clear log of the deliberation that led to the final statistical insight.

Setup guide

Set up Chi-Square Test Engine 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 Chi-Square Test Engine 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="Chi-Square Test Engine_assistant",
    model_client=OpenAIChatCompletionClient(model="gpt-4o"),
    tools=tools,
)

result = await agent.run("List recent Chi-Square Test Engine data")
print(result.messages[-1].content)

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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="Chi-Square Test Engine_assistant",
        model_client=OpenAIChatCompletionClient(model="gpt-4o"),
        workbench=workbench,
    )

    result = await agent.run("List recent Chi-Square Test Engine data")
    print(result.messages[-1].content)

Get your connection token →

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Common questions about Chi-Square Test Engine MCP in AutoGen

Yes, simply pass the tool list into your AssistantAgent. The agents will trigger the calculation whenever the conversation requires a definitive statistical test.

The McpToolAdapter handles the heavy lifting. It exposes the tool schema, allowing your agents to invoke the math functions seamlessly during their debates.

It serves as a shared source of truth. Any agent in your group chat can call the tool to resolve disagreements about data patterns.

The server is strictly ephemeral. It processes your contingency tables locally within the sandbox and does not store them after the tool call is finished.

The server operates with a zero-trust model. Your categorical data exists only in memory during the brief time the server computes the p-value.

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