How to Use the IBGE Nomes — Nomes do Brasil MCP in LangChain

Build multi-step reasoning chains in LangChain that analyze Brazilian name trends using historical census data.

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Connect IBGE Nomes — Nomes do Brasil MCP to LangChain

Create your Vinkius account to connect IBGE Nomes — Nomes do Brasil to LangChain 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 — Nomes do Brasil with LangChain

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Track name trends across decades in LangChain

Feed your LangChain agents historical data by calling `get_nome_frequencia`. You can pipe multiple names through the tool to compare their rise or fall across specific decades. Your agent parses this frequency data to build complex demographic profiles. It turns raw census numbers into actionable inputs for your downstream reasoning chains.

Map regional name popularity in LangChain

Use `get_nome_por_localidade` to filter name distribution by specific Brazilian states. Your chain identifies regional naming preferences by passing standard UF codes into the tool. This creates a clear geographic context for your data pipeline. LangSmith traces show exactly how the agent connects regional identity to your broader logic flow.

Rank national naming patterns in LangChain

Trigger `get_ranking_nomes` to retrieve the most popular names across Brazil. Your LangChain agent filters these lists by sex or time period to ground its analysis in reality. This tool serves as the starting point for your agentic workflows. It ensures your logic remains anchored to actual census rankings rather than guesses.

Setup guide

Set up IBGE Nomes — Nomes do Brasil MCP in LangChain

Prerequisites

Python 3.10+ installed
langchain-mcp-adapters + langgraph packages
Active Vinkius subscription with a valid endpoint token

1

Install dependencies
Run pip install langchain-mcp-adapters langgraph langchain-openai. The MCP adapters package converts MCP tools into native LangChain BaseTool objects.
2

Connect via HTTP transport
Use MultiServerMCPClient with "transport": "http" pointing to your Vinkius endpoint. Replace [YOUR_TOKEN_HERE] with your token from cloud.vinkius.com.
3

Create a ReAct agent
Pass the discovered tools to create_react_agent() from LangGraph. The agent automatically routes IBGE Nomes — Nomes do Brasil tool calls through the MCP protocol.
4

Run with any LLM
Swap ChatOpenAI for ChatAnthropic, ChatGoogleGenerativeAI, or any LangChain-compatible model. The MCP tools work identically across all providers.

agent.py

from langchain_mcp_adapters.client import MultiServerMCPClient
from langgraph.prebuilt import create_react_agent
from langchain_openai import ChatOpenAI

async with MultiServerMCPClient({
    "ibge-nomes-nomes-do-brasil-mcp": {
        "transport": "http",
        "url": "https://edge.vinkius.com/[YOUR_TOKEN_HERE]/mcp",
    }
}) as client:
    tools = client.get_tools()

    agent = create_react_agent(
        ChatOpenAI(model="gpt-4o"),
        tools,
    )
    result = await agent.ainvoke({
        "messages": "List recent IBGE Nomes — Nomes do Brasil transactions"
    })
    print(result["messages"][-1].content)

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Common questions about IBGE Nomes — Nomes do Brasil MCP in LangChain

Yes. You just pass names separated by a pipe character into the tool. The agent handles the output list for your chain.

It provides standard tool definitions that LangChain consumes directly. You map these to your agent functions and start querying the census data.

Not necessarily. You can run it statelessly for quick lookups or use a session client if you need the agent to remember historical context.

The server returns a standard error code. Your agent should handle this by retrying the request or logging the failure in LangSmith.

The server connects via a single endpoint token. Your agent only accesses public census statistics, ensuring no sensitive user data is exposed.

Use it with your favorite AI tools

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

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