IBGE Nomes MCP Server for LlamaIndexGive LlamaIndex instant access to 2 tools to Get Name Frequency and Get Names Ranking

Name: IBGE Nomes
Price: 29 USD
Availability: InStock
Rating: 5.0 (1 reviews)
Author: Vinkius

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LlamaIndex specializes in data-aware AI agents that connect LLMs to structured and unstructured sources. Add IBGE Nomes as an MCP tool provider through Vinkius and your agents can query, analyze, and act on live data alongside your existing indexes.

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The IBGE Nomes MCP Server for LlamaIndex is a standout in the Data Analytics category — giving your AI agent 2 tools to work with, ready to go from day one.

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python

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

async def main():
    # Your Vinkius token. get it at cloud.vinkius.com
    mcp_client = BasicMCPClient("https://edge.vinkius.com/[YOUR_TOKEN_HERE]/mcp")
    mcp_tool_spec = McpToolSpec(client=mcp_client)
    tools = await mcp_tool_spec.to_tool_list_async()

    agent = FunctionAgent(
        tools=tools,
        llm=OpenAI(model="gpt-4o"),
        system_prompt=(
            "You are an assistant with access to IBGE Nomes. "
            "You have 2 tools available."
        ),
    )

    response = await agent.run(
        "What tools are available in IBGE Nomes?"
    )
    print(response)

asyncio.run(main())

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About IBGE Nomes MCP Server

Connect to the IBGE (Brazilian Institute of Geography and Statistics) database through any AI agent to explore the rich demographic history of Brazilian names. This server provides direct access to the 'Nomes no Brasil' census data.

LlamaIndex agents combine IBGE Nomes tool responses with indexed documents for comprehensive, grounded answers. Connect 2 tools through Vinkius and query live data alongside vector stores and SQL databases in a single turn. ideal for hybrid search, data enrichment, and analytical workflows.

What you can do

Name Frequency — Query the number of births per decade for specific names (e.g., 'MARIA' or 'ENZO') to see how trends evolved over time.
Rankings & Popularity — Generate rankings of the most frequent names in Brazil, with optional filters for gender and specific decades.
Geographic Insights — Filter results by locality ID to understand regional naming preferences across different Brazilian states and municipalities.
Comparative Analysis — Use the pipe separator to compare multiple names simultaneously and identify cultural shifts.

The IBGE Nomes MCP Server exposes 2 tools through the Vinkius. Connect it to LlamaIndex in under two minutes — credentials fully managed, no infrastructure to provision, no vendor lock-in. Your configuration, your data, your control.

All 2 IBGE Nomes tools available for LlamaIndex

When LlamaIndex connects to IBGE Nomes through Vinkius, your AI agent gets direct access to every tool listed below — spanning demographics, brazil, census, and more. Every call runs in a secure, isolated environment with full audit visibility. Beyond a simple connection, you get real-time monitoring of agent activity, enterprise governance, and optimized token usage.

get

Get name frequency on IBGE Nomes

Multiple names can be separated by a pipe (|). Obtains the frequency of births per decade for a specific name

get

Get names ranking on IBGE Nomes

Obtains a ranking of the most frequent names according to specified filters

Connect IBGE Nomes to LlamaIndex via MCP

Follow these steps to wire IBGE Nomes into LlamaIndex. The entire setup takes under two minutes — your credentials stay safe behind Vinkius.

Install dependencies

Run pip install llama-index-tools-mcp llama-index-llms-openai

Replace the token

Replace [YOUR_TOKEN_HERE] with your Vinkius token

Run the agent

Save to agent.py and run: python agent.py

Explore tools

The agent discovers 2 tools from IBGE Nomes

Why Use LlamaIndex with the IBGE Nomes MCP Server

LlamaIndex provides unique advantages when paired with IBGE Nomes through the Model Context Protocol.

Data-first architecture: LlamaIndex agents combine IBGE Nomes tool responses with indexed documents for comprehensive, grounded answers

Query pipeline framework lets you chain IBGE Nomes tool calls with transformations, filters, and re-rankers in a typed pipeline

Multi-source reasoning: agents can query IBGE Nomes, a vector store, and a SQL database in a single turn and synthesize results

Observability integrations show exactly what IBGE Nomes tools were called, what data was returned, and how it influenced the final answer

IBGE Nomes + LlamaIndex Use Cases

Practical scenarios where LlamaIndex combined with the IBGE Nomes MCP Server delivers measurable value.

Hybrid search: combine IBGE Nomes real-time data with embedded document indexes for answers that are both current and comprehensive

Data enrichment: query IBGE Nomes to augment indexed data with live information before generating user-facing responses

Knowledge base agents: build agents that maintain and update knowledge bases by periodically querying IBGE Nomes for fresh data

Analytical workflows: chain IBGE Nomes queries with LlamaIndex's data connectors to build multi-source analytical reports

Example Prompts for IBGE Nomes in LlamaIndex

Ready-to-use prompts you can give your LlamaIndex agent to start working with IBGE Nomes immediately.

"What is the birth frequency of the name 'Neymar' in Brazil per decade?"

"Show me the top 10 most popular female names in Brazil during the 1980s."

"Compare the popularity of 'Enzo' and 'Valentina' using IBGE data."

Troubleshooting IBGE Nomes MCP Server with LlamaIndex

Common issues when connecting IBGE Nomes to LlamaIndex through Vinkius, and how to resolve them.

BasicMCPClient not found

Install: pip install llama-index-tools-mcp

IBGE Nomes + LlamaIndex FAQ

Common questions about integrating IBGE Nomes MCP Server with LlamaIndex.

How does LlamaIndex connect to MCP servers?

Use the MCP client adapter to create a connection. LlamaIndex discovers all tools and wraps them as query engine tools compatible with any LlamaIndex agent.

Can I combine MCP tools with vector stores?

Yes. LlamaIndex agents can query IBGE Nomes tools and vector store indexes in the same turn, combining real-time and embedded data for grounded responses.