How to Use the IBGE Nomes MCP in Mastra AI

Build resilient demographic workflows in Mastra AI with automated error handling and reliable IBGE data access.

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Connect IBGE Nomes MCP to Mastra AI

Create your Vinkius account to connect IBGE Nomes to Mastra AI 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 IBGE Nomes with Mastra AI

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Claude

Perplexity

Automated demographic research

Chain `get_name_frequency` calls within your Mastra agents to build complex demographic reports. The workflow engine manages the execution flow automatically. If a request hits a temporary network snag, the engine retries the operation. You get consistent data without writing custom error logic.

Conditional ranking analysis

Use `get_names_ranking` to trigger downstream actions based on population shifts. You can branch your logic depending on which names appear in the top results. It allows your agent to decide the next step, like notifying an admin or updating a database. The logic stays clean and focused on the outcome.

Human-in-the-loop validation

Require manual approval before your agent finalizes a report based on IBGE stats. This MCP Server integrates perfectly with Mastra's approval gates. You keep control over the output while the agent does the heavy lifting of gathering the numbers. It ensures your data-driven decisions remain supervised.

Setup guide

Set up IBGE Nomes MCP in Mastra AI

Prerequisites

Node.js 18+ and a TypeScript project
@mastra/mcp + @mastra/core packages
Active Vinkius subscription with a valid endpoint token

1

Install dependencies
Run npm install @mastra/mcp @mastra/core plus your preferred model provider (e.g. @ai-sdk/openai).
2

Configure the MCPClient
Create an MCPClient with your Vinkius endpoint as a URL object. Replace [YOUR_TOKEN_HERE] with your token from cloud.vinkius.com.
3

Discover and inject tools
Call mcpClient.listTools() and spread the result into your agent's tools object. All IBGE Nomes tools become native Mastra tools.
4

Run with any model
Swap openai("gpt-4o") for any AI SDK-compatible provider. Call agent.generate() and the agent routes tool calls through MCP automatically.

agent.ts

import { MCPClient } from "@mastra/mcp";
import { Agent } from "@mastra/core/agent";
import { openai } from "@ai-sdk/openai";

const mcpClient = new MCPClient({
  id: "ibge-nomes-mcp-client",
  servers: {
    "ibge-nomes-mcp": {
      url: new URL(
        "https://edge.vinkius.com/[YOUR_TOKEN_HERE]/mcp"
      ),
    },
  },
});

const agent = new Agent({
  name: "IBGE Nomes Agent",
  model: openai("gpt-4o"),
  instructions: "You have access to IBGE Nomes tools.",
  tools: {
    ...(await mcpClient.listTools()),
  },
});

const result = await agent.generate(
  "List recent IBGE Nomes transactions"
);
console.log(result.text);

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Common questions about IBGE Nomes MCP in Mastra AI

Absolutely. You add this MCP Server to your agent configuration, and the tools become available as tasks within your workflow definitions.

The server processes each tool call independently. Mastra manages the execution order, ensuring your agents receive the correct data for every step in the chain.

The tool returns an empty result set, which your agent handles as a standard failure state. You can then use Mastra logic to prompt the user or try a broader search.

You define the server in your agent config once. It remains available for all subsequent tasks and automated runs defined in your project.

Your queries stay within the isolated MCP transport layer. Since the data is public census information, the server avoids handling sensitive PII, keeping your agent logic secure.

Use it with your favorite AI tools

Connect this server to Cursor, Claude, VS Code, and more.

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