Where does this name data come from?

All name data comes from **official IBGE Census records** spanning over 90 years. The frequency counts represent actual birth registrations aggregated by decade since the 1930s.

IBGE Nomes — Nomes do Brasil MCP Server for CrewAI 3 tools — connect in under 2 minutes

Name: IBGE Nomes — Nomes do Brasil
Availability: InStock
Author: Vinkius

docs.crewai.com/mcp/overview

Built by Vinkius GDPR 3 Tools Framework

Connect your CrewAI agents to IBGE Nomes — Nomes do Brasil through Vinkius, pass the Edge URL in the `mcps` parameter and every IBGE Nomes — Nomes do Brasil tool is auto-discovered at runtime. No credentials to manage, no infrastructure to maintain.

Get MCP Server for AI Agents

ASK AI ABOUT THIS MCP SERVER

Open in ChatGPT Open in Claude Open in Perplexity

Vinkius supports streamable HTTP and SSE.

python

from crewai import Agent, Task, Crew

agent = Agent(
    role="IBGE Nomes — Nomes do Brasil Specialist",
    goal="Help users interact with IBGE Nomes — Nomes do Brasil effectively",
    backstory=(
        "You are an expert at leveraging IBGE Nomes — Nomes do Brasil tools "
        "for automation and data analysis."
    ),
    # Your Vinkius token. get it at cloud.vinkius.com
    mcps=["https://edge.vinkius.com/[YOUR_TOKEN_HERE]/mcp"],
)

task = Task(
    description=(
        "Explore all available tools in IBGE Nomes — Nomes do Brasil "
        "and summarize their capabilities."
    ),
    agent=agent,
    expected_output=(
        "A detailed summary of 3 available tools "
        "and what they can do."
    ),
)

crew = Crew(agents=[agent], tasks=[task])
result = crew.kickoff()
print(result)

Fully ManagedVinkius Servers

60%Token savings

High SecurityEnterprise-grade

IAMAccess control

EU AI ActCompliant

DLPData protection

V8 IsolateSandboxed

Ed25519Audit chain

<40msKill switch

Stream every event to Splunk, Datadog, or your own webhook in real-time

* Every MCP server runs on Vinkius-managed infrastructure inside AWS - a purpose-built runtime with per-request V8 isolates, Ed25519 signed audit chains, and sub-40ms cold starts optimized for native MCP execution. See our infrastructure

About IBGE Nomes — Nomes do Brasil MCP Server

Tap into Brazil's most viral dataset — the IBGE Names API that broke the internet when launched, as 200 million Brazilians rushed to look up their own names.

When paired with CrewAI, IBGE Nomes — Nomes do Brasil becomes a first-class tool in your multi-agent workflows. Each agent in the crew can call IBGE Nomes — Nomes do Brasil tools autonomously, one agent queries data, another analyzes results, a third compiles reports, all orchestrated through Vinkius with zero configuration overhead.

What you can do

Name Frequency — How many "Marias" were born in each decade since 1930? Track any name's rise and fall across almost 100 years
National Ranking — Top 20 most popular names by decade + filter by sex (M/F)
Regional Trends — Compare name popularity across Brazilian states (is "José" more popular in Bahia or São Paulo?)

The IBGE Nomes — Nomes do Brasil MCP Server exposes 3 tools through the Vinkius. Connect it to CrewAI in under two minutes — no API keys to rotate, no infrastructure to provision, no vendor lock-in. Your configuration, your data, your control.

How to Connect IBGE Nomes — Nomes do Brasil to CrewAI via MCP

Follow these steps to integrate the IBGE Nomes — Nomes do Brasil MCP Server with CrewAI.

Install CrewAI

Run pip install crewai

Replace the token

Replace [YOUR_TOKEN_HERE] with your Vinkius token from cloud.vinkius.com

Customize the agent

Adjust the role, goal, and backstory to fit your use case

Run the crew

Run python crew.py. CrewAI auto-discovers 3 tools from IBGE Nomes — Nomes do Brasil

Why Use CrewAI with the IBGE Nomes — Nomes do Brasil MCP Server

CrewAI Multi-Agent Orchestration Framework provides unique advantages when paired with IBGE Nomes — Nomes do Brasil through the Model Context Protocol.

Multi-agent collaboration lets you decompose complex workflows into specialized roles, one agent researches, another analyzes, a third generates reports, each with access to MCP tools

CrewAI's native MCP integration requires zero adapter code: pass Vinkius Edge URL directly in the `mcps` parameter and agents auto-discover every available tool at runtime

Built-in task delegation and shared memory mean agents can pass context between steps without manual state management, enabling multi-hop reasoning across tool calls

Sequential and hierarchical crew patterns map naturally to real-world workflows: enumerate subdomains → analyze DNS history → check WHOIS records → compile findings into actionable reports

IBGE Nomes — Nomes do Brasil + CrewAI Use Cases

Practical scenarios where CrewAI combined with the IBGE Nomes — Nomes do Brasil MCP Server delivers measurable value.

Automated multi-step research: a reconnaissance agent queries IBGE Nomes — Nomes do Brasil for raw data, then a second analyst agent cross-references findings and flags anomalies. all without human handoff

Scheduled intelligence reports: set up a crew that periodically queries IBGE Nomes — Nomes do Brasil, analyzes trends over time, and generates executive briefings in markdown or PDF format

Multi-source enrichment pipelines: chain IBGE Nomes — Nomes do Brasil tools with other MCP servers in the same crew, letting agents correlate data across multiple providers in a single workflow

Compliance and audit automation: a compliance agent queries IBGE Nomes — Nomes do Brasil against predefined policy rules, generates deviation reports, and routes findings to the appropriate team

IBGE Nomes — Nomes do Brasil MCP Tools for CrewAI (3)

These 3 tools become available when you connect IBGE Nomes — Nomes do Brasil to CrewAI via MCP:

get_nome_frequencia

Supports multiple names separated by |. Example: "Maria", "João|Pedro". Get birth frequency by decade for a Brazilian name

get_nome_por_localidade

Use the IBGE UF code (e.g., 33 for RJ, 35 for SP). Get name frequency filtered by Brazilian state

get_ranking_nomes

Can be filtered by decade and/or sex (M or F). Get ranking of most popular names in Brazil

Example Prompts for IBGE Nomes — Nomes do Brasil in CrewAI

Ready-to-use prompts you can give your CrewAI agent to start working with IBGE Nomes — Nomes do Brasil immediately.

"How popular was the name 'Maria' across decades in Brazil?"

"What are the top 10 baby names in Brazil in the 2000s?"

"Is 'João' more popular in Bahia or in Rio Grande do Sul?"

Troubleshooting IBGE Nomes — Nomes do Brasil MCP Server with CrewAI

Common issues when connecting IBGE Nomes — Nomes do Brasil to CrewAI through the Vinkius, and how to resolve them.

MCP tools not discovered

Ensure the Edge URL is correct. CrewAI connects lazily when the crew starts. check console output.

Agent not using tools

Make the task description specific. Instead of "do something", say "Use the available tools to list contacts".

Timeout errors

CrewAI has a 10s connection timeout by default. Ensure your network can reach the Edge URL.

Rate limiting or 429 errors

Vinkius enforces per-token rate limits. Check your subscription tier and request quota in the dashboard. Upgrade if you need higher throughput.

IBGE Nomes — Nomes do Brasil + CrewAI FAQ

Common questions about integrating IBGE Nomes — Nomes do Brasil MCP Server with CrewAI.

How does CrewAI discover and connect to MCP tools?

CrewAI connects to MCP servers lazily. when the crew starts, each agent resolves its MCP URLs and fetches the tool catalog via the standard tools/list method. This means tools are always fresh and reflect the server's current capabilities. No tool schemas need to be hardcoded.

Can different agents in the same crew use different MCP servers?

Yes. Each agent has its own mcps list, so you can assign specific servers to specific roles. For example, a reconnaissance agent might use a domain intelligence server while an analysis agent uses a vulnerability database server.

What happens when an MCP tool call fails during a crew run?

CrewAI wraps tool failures as context for the agent. The LLM receives the error message and can decide to retry with different parameters, fall back to a different tool, or mark the task as partially complete. This resilience is critical for production workflows.

Can CrewAI agents call multiple MCP tools in parallel?

CrewAI agents execute tool calls sequentially within a single reasoning step. However, you can run multiple agents in parallel using process=Process.parallel, each calling different MCP tools concurrently. This is ideal for workflows where separate data sources need to be queried simultaneously.

Can I run CrewAI crews on a schedule (cron)?

Yes. CrewAI crews are standard Python scripts, so you can invoke them via cron, Airflow, Celery, or any task scheduler. The crew.kickoff() method runs synchronously by default, making it straightforward to integrate into existing pipelines.