How to Use the ENEM Score Calculator MCP in Vercel AI SDK

Stream ENEM grades and admission odds directly into your React components in real-time with the Vercel AI SDK.

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Works with every AI agent you already use

…and any MCP-compatible client

MCP Servers — Included with Plan

Connect ENEM Score Calculator MCP to Vercel AI SDK

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

GDPR Included with Plan

Setup ENEM Score Calculator with Vercel AI SDK

Ask AI about this MCP

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Claude

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Gemini

Grok

Real-time score calculations inside Vercel AI SDK

The `calculate_area_averages` tool computes the arithmetic mean of the four objective exam areas instantly. Your user sees the numbers change on screen as they type, bypasses the usual loading spinners, and gets immediate feedback. This tool handles the raw math on the edge. It takes the individual area scores and spits out a clean average that feeds directly into your UI components.

Custom weight processing on the edge

The `calculate_weighted_score` tool applies specific university weights to the student's grades. Different programs value different subjects, and this tool handles those complex weight distributions in milliseconds. You get back a clean, weighted average that reflects actual university requirements. The React hook updates the UI instantly, letting applicants test different scenarios on the fly.

Instant admission odds simulation

The `simulate_admission_possibility` tool matches student grades against historical cutoff data to predict their chance of getting in. Your agent pulls historical benchmarks and returns a realistic probability score. Because this runs via an MCP, your client handles the data lookup and UI streaming in a single step. Students get immediate clarity on their target schools without page reloads.

Setup guide

Set up ENEM Score Calculator MCP in Vercel AI SDK

Prerequisites

Node.js 18+ and a TypeScript project
ai + @modelcontextprotocol/sdk packages
Active Vinkius subscription with a valid endpoint token

1

Install dependencies

Run npm install ai @modelcontextprotocol/sdk plus your preferred model provider (e.g. @ai-sdk/openai).
2

Create the Streamable HTTP transport

Use StreamableHTTPClientTransport with your Vinkius endpoint URL. Replace [YOUR_TOKEN_HERE] with your token from cloud.vinkius.com.
3

Discover and use tools

Call mcpClient.tools() to auto-discover all ENEM Score Calculator tools. Pass them directly to generateText() or streamText() — no manual schema definitions needed.
4

Works with any model provider

Swap openai("gpt-4o") for any AI SDK provider — Anthropic, Google, Mistral. The MCP tools work identically across all supported models.

index.ts

import { experimental_createMCPClient as createMCPClient } from "ai";
import { StreamableHTTPClientTransport } from "@modelcontextprotocol/sdk/client/streamableHttp";
import { generateText } from "ai";
import { openai } from "@ai-sdk/openai";

const transport = new StreamableHTTPClientTransport(
  new URL("https://edge.vinkius.com/[YOUR_TOKEN_HERE]/mcp")
);

const mcpClient = await createMCPClient({ transport });
const tools = await mcpClient.tools();

const { text } = await generateText({
  model: openai("gpt-4o"),
  tools,
  prompt: "List recent ENEM Score Calculator transactions",
});

console.log(text);
await mcpClient.close();

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 Vercel AI SDK

Install the SDK and the MCP client package, then configure your connection. Pass the MCP tools directly into your text generation function. The tools execute during the model call and stream results back.

Yes, this MCP works perfectly in edge environments. The lightweight design ensures fast execution times and zero cold-start penalties for your users.

Yes, you can pass OAuth tokens using the SDK's auth provider. This keeps user data secure when querying student records through the MCP.

The SDK catches tool execution errors gracefully. If a student inputs invalid scores, the system returns a clean error message instead of crashing the stream.

Your student scores and exam grades are processed in memory and never stored on Vinkius. The MCP only performs calculations and compares them against public historical cutoff points.

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