How to Use the ENEM Score Calculator MCP in AutoGen

Q: How do I install the ENEM Score Calculator in AutoGen?

Run pip install -U "autogen-extmcp" and use mcpservertools with StreamableHttpServerParams pointing to Vinkius. Pass the resulting tool list directly to your AssistantAgent constructor.

Let your AutoGen agents debate university admission strategies using this ENEM calculation MCP.

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Connect ENEM Score Calculator MCP to AutoGen

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Setup ENEM Score Calculator with AutoGen

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Debate Admission Strategies

The `simulate_admission_possibility` function allows your agents to check a student's score against historical cutoffs. A conservative advising agent might reject a borderline probability while an aggressive agent pushes for application. Multiple agents discuss the predicted success rates and challenge each other. They negotiate the best possible university match before presenting a final recommendation to the user.

Calculate Objective Averages

Your math agent invokes `calculate_area_averages` to determine the arithmetic mean of the four objective exam sections. This raw data becomes the foundation for the ensuing multi-agent deliberation. The MCP handles the strict calculations so your conversational framework can focus on strategy. Agents pass these baseline numbers back and forth to build their respective arguments.

Multi-Agent AutoGen Workflows

Calling `calculate_weighted_score` applies specific importance weights to generate a final performance metric. A specialized university agent requests different weight configurations to see how the student ranks across various institutions. Vinkius provides this calculator as part of its massive catalog of 4,000 managed MCPs. You connect your AutoGen environment once and your agents immediately gain the ability to interact with thousands of managed endpoints.

Setup guide

Set up ENEM Score Calculator 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 ENEM Score Calculator 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="ENEM Score Calculator_assistant",
    model_client=OpenAIChatCompletionClient(model="gpt-4o"),
    tools=tools,
)

result = await agent.run("List recent ENEM Score Calculator 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="ENEM Score Calculator_assistant",
        model_client=OpenAIChatCompletionClient(model="gpt-4o"),
        workbench=workbench,
    )

    result = await agent.run("List recent ENEM Score Calculator 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 ENEM Score Calculator. 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 ENEM Score Calculator MCP in AutoGen

Run pip install -U "autogen-ext[mcp]" and use mcp_server_tools with StreamableHttpServerParams pointing to Vinkius. Pass the resulting tool list directly to your AssistantAgent constructor.

Yes. You can equip a specialized math agent with the calculation tools while a separate strategy agent interprets the results. They communicate through the standard AutoGen group chat interface.

The McpToolAdapter converts all required parameters natively. Your agents understand exactly how to format the area scores and custom weights without manual schema definition.

The framework supports both stdio and Streamable HTTP transports. You will use the HTTP transport to connect directly to the Vinkius managed endpoint.

The platform processes the numerical arrays and cutoff parameters in volatile memory. Vinkius purges the routing context immediately after returning the calculation to your AutoGen environment.

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