How to Use the IBGE Serviços de Dados MCP in LangChain

Chain live Brazilian census data and CNAE economic classifications directly into your LangChain agent pipelines.

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Connect IBGE Serviços de Dados MCP to LangChain

Create your Vinkius account to connect IBGE Serviços de Dados 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 Serviços de Dados with LangChain

Ask AI about this MCP

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Claude

Perplexity

Chain demographic lookups to custom database queries

`get_agregados` pulls raw statistical tables from IBGE to feed your agent's next execution step. The tool outputs raw numbers that your pipeline can parse to determine regional market size before triggering a database insert. This setup avoids manual data copying. Your agent handles the entire sequence, passing the parsed aggregates directly to your vector stores or memory chains in a single run.

Validate economic classifications in LangSmith

`get_cnae_classe` retrieves the official Brazilian economic activity codes to verify business registrations. You feed this tool raw company descriptions, let the agent match the correct CNAE class, and trace the decision logic inside LangSmith to catch classification errors. We trace every API call to monitor latency and token costs. This gives you clear visibility into how the agent processes municipal data without guessing which steps failed.

Map regional trends with LangChain MCP Server tools

`get_malha_estado` fetches geographic boundary coordinates for Brazilian states to fuel your mapping workflows. Your agent calls this tool, extracts the coordinate grid, and passes it to your visualization layers without manual intervention. You build multi-step reasoning chains that first identify high-growth areas and then pull the corresponding state maps. The entire process runs on Vinkius's zero-trust sandbox, keeping your API keys safe.

Setup guide

Set up IBGE Serviços de Dados 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 Serviços de Dados 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-servicos-de-dados-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 Serviços de Dados 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 Serviços de Dados MCP in LangChain

You use the MultiServerMCPClient to fetch the tools and register them directly in your agent's tool list. The output from `get_agregados` or `get_cnae_classe` flows as a string directly into the next chain link. LangGraph handles the state transitions between these steps automatically.

Yes, every tool call is fully traced. You will see the exact payload sent to `get_noticias` or `get_metadados` along with the response times. This makes debugging slow API calls simple.

Yes, you can combine this server with other MCP endpoints. The MultiServerMCPClient aggregates everything into a single toolset for your agent. This lets your pipeline mix Brazilian demographic data with private database queries.

You should implement retry logic in your LangChain runnable chains. Since Vinkius manages the endpoint connection, you only need to manage the agent-side backoff. The server handles the raw HTTP handshake under the hood.

Vinkius runs this MCP server in an isolated V8 sandbox, meaning your queries never touch persistent storage. The transit path only carries public Brazilian demographic, geographic, and economic data from IBGE. No private business information is ever logged or exposed to third parties.

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