How to Use the IBGE Nomes MCP in LangChain

Q: Does this server support state-level filtering for rankings?

The getnamesranking tool accepts locality parameters to narrow down the statistics. Your agent can query rankings for specific Brazilian states or municipalities instantly.

Feed official Brazilian demographic trends directly into your LangChain reasoning loops.

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Connect IBGE Nomes MCP to LangChain

Create your Vinkius account to connect IBGE Nomes 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 with LangChain

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Claude

Perplexity

Map decade-by-decade popularity in LangChain chains

The `get_name_frequency` tool pulls historical birth counts directly from the IBGE database into your active run context. By separating multiple names with a pipe character, your agent compares naming trends across generations in a single model call. Your LangChain agent feeds these raw numbers into subsequent chain steps automatically. This lets you trace how specific cultural names rose or fell over the decades without manual parsing.

Filter regional rankings with an active MCP Server

The `get_names_ranking` tool queries localized Brazilian name statistics based on gender, state, or city filters. It outputs structured JSON that your ReAct agent uses to answer complex geographic queries. Integrating this MCP Server with LangSmith lets you monitor the latency and token cost of every demographic query. You see exactly how the agent parses the ranking response before passing it to the next prompt template.

Build multi-step demographic analysis pipelines

The `get_names_ranking` and `get_name_frequency` tools combine to form autonomous workflows where the output of a ranking query triggers a deep-dive frequency check. Connecting via MultiServerMCPClient exposes both tools directly to your agent with a single client config. You write simple Python chains where the model decides which tool to run first based on the user's question. No hardcoded logic is needed to route the Brazilian census data.

Setup guide

Set up IBGE Nomes 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 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-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 transactions"
    })
    print(result["messages"][-1].content)

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Independent Platform Disclaimer: Vinkius is an independent platform and is not affiliated with, endorsed by, sponsored by, verified by, or otherwise authorized by IBGE. 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 IBGE Nomes MCP in LangChain

Run pip install langchain-mcp-adapters langgraph in your terminal. After that, configure the MultiServerMCPClient with the server URL and call client.get_tools() to pass them directly to your agent.

Yes, the agent formats the query by separating names with a pipe symbol when calling the `get_name_frequency` tool. This allows the model to analyze comparative trends in one step.

LangSmith tracks every tool call made to the server, showing the exact inputs and outputs. You can inspect the raw JSON payloads returned by the Brazilian census API to fix prompt formatting issues.

The `get_names_ranking` tool accepts locality parameters to narrow down the statistics. Your agent can query rankings for specific Brazilian states or municipalities instantly.

This server only handles public Brazilian name statistics and demographic counts. No personal identification data or private user records are ever accessed or transmitted, as the server runs in an ephemeral, zero-trust sandbox.

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