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

Index historical Brazilian name data directly into your LlamaIndex knowledge base.

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Connect IBGE Nomes — Nomes do Brasil MCP to LlamaIndex

Create your Vinkius account to connect IBGE Nomes — Nomes do Brasil to LlamaIndex 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 LlamaIndex

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Feed name frequency into LlamaIndex

Use `get_nome_frequencia` to pull decade-by-decade birth counts for any name. LlamaIndex then indexes these results, allowing you to query them alongside your private documents. This allows your RAG application to answer questions about name longevity. The data becomes a permanent part of your searchable index.

Perform state-based queries in LlamaIndex

Call `get_nome_por_localidade` to ground your search in specific Brazilian regions. You pass the UF code, and the tool returns localized frequency data for your index. Your agent uses this to provide geographically accurate answers. It prevents the model from hallucinating naming trends that don't exist in specific states.

Query national rankings via LlamaIndex

Invoke `get_ranking_nomes` to pull national popularity lists into your knowledge base. Once indexed, these rankings provide a baseline for your semantic searches. This ensures your application treats census data as a ground-truth document. You get precise answers derived from historical records rather than general model knowledge.

Setup guide

Set up IBGE Nomes — Nomes do Brasil MCP in LlamaIndex

Prerequisites

Python 3.10+ installed
llama-index-tools-mcp package
Active Vinkius subscription with a valid endpoint token

1

Install dependencies
Run pip install llama-index-tools-mcp llama-index-llms-openai. The MCP tools package provides BasicMCPClient and McpToolSpec.
2

Connect with BasicMCPClient
Point BasicMCPClient to your Vinkius endpoint URL. Replace [YOUR_TOKEN_HERE] with your token from cloud.vinkius.com. Supports SSE and Streamable HTTP transports.
3

Convert to LlamaIndex tools
Call mcp_tool_spec.to_tool_list_async() to convert all IBGE Nomes — Nomes do Brasil MCP tools into native FunctionTool objects that any LlamaIndex agent can use.
4

Run with any LLM
Create a FunctionAgent with the tools and your preferred LLM. Swap OpenAI for Anthropic, Gemini, or any LlamaIndex-supported provider.

agent.py

from llama_index.tools.mcp import BasicMCPClient, McpToolSpec
from llama_index.core.agent.workflow import FunctionAgent
from llama_index.llms.openai import OpenAI

# Connect to the MCP
mcp_client = BasicMCPClient(
    "https://edge.vinkius.com/[YOUR_TOKEN_HERE]/mcp"
)
mcp_tool_spec = McpToolSpec(client=mcp_client)

# Convert MCP tools to LlamaIndex tools
tools = await mcp_tool_spec.to_tool_list_async()

# Create and run the agent
agent = FunctionAgent(
    tools=tools,
    llm=OpenAI(model="gpt-4o"),
    system_prompt="You have access to IBGE Nomes — Nomes do Brasil tools.",
)
response = await agent.run("List recent IBGE Nomes — Nomes do Brasil data")

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

You use the MCP tool spec to pull the data and add it to your vector store. The API responses become searchable nodes in your index.

Absolutely. By indexing the tool output, your agent performs semantic searches across state-specific name frequencies.

The data is based on census intervals. You can refresh your index periodically to ensure your agent reflects the latest available statistics.

Yes. The tool adapter maps the IBGE endpoints to your agent functions. You just point it at the server URL and it handles the rest.

Your queries stay local to your machine. The server only transmits public census data, and your index remains within your own control.

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