How to Use the ENEM Score Calculator MCP in Google ADK

Q: Does Google ADK support filtering tools from the ENEM Score Calculator?

Yes, you can use a toolnames filter to expose only the specific functions your agent needs. This keeps your agent's capabilities focused and prevents unnecessary tool calls.

Process ENEM exam metrics and admission forecasts using the Google ADK and Gemini infrastructure.

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Connect ENEM Score Calculator MCP to Google ADK

Create your Vinkius account to connect ENEM Score Calculator to Google ADK — we handle the hosting, security, and runtime updates so you don't have to. No server setup required.

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Setup ENEM Score Calculator with Google ADK

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Compute area means with Google ADK

The `calculate_area_averages` tool runs within your Google ADK agent to determine the arithmetic mean of objective exam areas. It provides the core data necessary for your agent to evaluate student performance accurately. By keeping these calculations inside your agent, you avoid moving data between disparate services. It keeps your logic local to the Gemini-powered reasoning loop.

Apply custom weights for university targets

Use `calculate_weighted_score` to adjust the importance of specific exam subjects for targeted university programs. Your agent applies these weights to generate a final performance metric tailored to specific institutional criteria. This tool allows your agents to handle complex admission requirements without hardcoding every possible variation. It keeps your agent flexible and responsive to changing university standards.

Forecast admissions via historical benchmarks

The `simulate_admission_possibility` tool matches a student's calculated score against historical cutoff data to estimate success. Your agent uses this output to provide clear, data-backed guidance to the user. This capability connects your agent to actual historical performance trends. It allows for evidence-based predictions that go beyond simple score reporting.

Setup guide

Set up ENEM Score Calculator 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 ENEM Score Calculator 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="ENEM Score Calculator_agent",
    model="gemini-2.0-flash",
    instruction="You have access to ENEM Score Calculator tools via MCP.",
    tools=mcp_tools,
)

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Common questions about ENEM Score Calculator MCP in Google ADK

You use the McpToolset class to point your agent at the MCP endpoint. Once added to your tool list, your agent can call these functions whenever the task requires score analysis.

Absolutely, as the tools provide concise numeric outputs that fit perfectly into your agent's context window. Your agent can then reason over these results alongside massive datasets.

While the MCP itself focuses on score math, your agent can pull data from BigQuery and pass it directly to these tools. It acts as the bridge between your cloud storage and the final performance metrics.

Yes, you can use a tool_names filter to expose only the specific functions your agent needs. This keeps your agent's capabilities focused and prevents unnecessary tool calls.

All calculations occur in-memory during the agent's execution cycle. The MCP does not log or retain your specific student performance numbers, ensuring your data remains within your controlled cloud environment.

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