Compatible with every major AI agent and IDE
What is the 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.
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.
How it works
- Subscribe to this server
- No API key is required as it uses the public IBGE Open Data API
- Start querying Brazilian name statistics from Claude, Cursor, or any MCP client
Who is this for?
- Data Analysts & Sociologists — study naming trends and demographic shifts in the Brazilian population.
- Content Creators & Writers — find historically accurate names for characters based on specific decades in Brazil.
- Developers — integrate official Brazilian demographic data into applications without complex setup.
Built-in capabilities (2)
Multiple names can be separated by a pipe (|). Obtains the frequency of births per decade for a specific name
Obtains a ranking of the most frequent names according to specified filters
Why CrewAI?
When paired with CrewAI, IBGE Nomes becomes a first-class tool in your multi-agent workflows. Each agent in the crew can call IBGE Nomes tools autonomously, one agent queries data, another analyzes results, a third compiles reports, all orchestrated through Vinkius with zero configuration overhead.
- —
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
mcpsparameter 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 in CrewAI
IBGE Nomes and 4,000+ other MCP servers. One platform. One governance layer.
Teams that connect IBGE Nomes to CrewAI through Vinkius don't need to source, host, or maintain individual MCP servers. Every tool call runs inside a hardened runtime with credential isolation, DLP, and a signed audit chain.
Raw MCP | Vinkius | |
|---|---|---|
| Server catalog | Find and host yourself | 4,000+ managed |
| Infrastructure | Self-hosted | Sandboxed V8 isolates |
| Credential handling | Plaintext in config | Vault + runtime injection |
| Data loss prevention | None | Configurable DLP policies |
| Kill switch | None | Global instant shutdown |
| Financial circuit breakers | None | Per-server limits + alerts |
| Audit trail | None | Ed25519 signed logs |
| SIEM log streaming | None | Splunk, Datadog, Webhook |
| Honeytokens | None | Canary alerts on leak |
| Custom domains | Not applicable | DNS challenge verified |
| GDPR compliance | Manual effort | Automated purge + export |
Why teams choose Vinkius for IBGE Nomes in CrewAI
The IBGE Nomes 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. All 2 tools execute in hardened sandboxes optimized for native MCP execution.
Your AI agents in CrewAI only access the data you authorize, with DLP that blocks sensitive information from ever reaching the model, kill switch for instant shutdown, and up to 60% token savings. Enterprise-grade infrastructure, zero maintenance.

* 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
How Vinkius secures
IBGE Nomes for CrewAI
Every tool call from CrewAI to the IBGE Nomes MCP Server is protected by DLP redaction, cryptographic audit chains, V8 sandbox isolation, kill switch, and financial circuit breakers.
Frequently asked questions
Can I compare the popularity of two different names in the same query?
Yes! Use the get_name_frequency tool and separate the names with a pipe symbol (e.g., 'MARIA|ANA'). The agent will return the frequency data for both names across the decades.
How do I find the most popular names from the 1990s?
You can use the get_names_ranking tool and provide '1990' in the decada parameter. This will return a list of the most frequent names recorded during that specific period.
Is it possible to filter name statistics by a specific Brazilian state?
Absolutely. Both get_name_frequency and get_names_ranking accept a localidade parameter. You just need to provide the IBGE ID for the target state or municipality.
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.
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.
Explore More MCP Servers
View all →
Zendesk Sell
11 toolsManage sales leads, contacts, and deals via the Zendesk Sell (Base CRM) API.

WPS 365
10 toolsCloud-based office suite and collaboration platform — manage documents, sheets, and presentations via AI.

eduMe
10 toolsEquip your AI agent to manage mobile training, track trainees, and monitor course completion via the eduMe API.

CallGear
10 toolsAnalyze communication performance via CallGear — track calls, monitor advertising campaigns, and retrieve real-time stats directly from any AI agent.
