Bring Demographics
to Mastra AI
Learn how to connect IBGE Nomes to Mastra AI and start using 2 AI agent tools in minutes. Fully managed, enterprise secure, and ready to use without writing a single line of code.
GDPR Free for SubscribersCompatible with every major AI agent and IDE
Gemini
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 Mastra AI?
Mastra's agent abstraction provides a clean separation between LLM logic and IBGE Nomes tool infrastructure. Connect 2 tools through Vinkius and use Mastra's built-in workflow engine to chain tool calls with conditional logic, retries, and parallel execution. deployable to any Node.js host in one command.
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Mastra's agent abstraction provides a clean separation between LLM logic and tool infrastructure. add IBGE Nomes without touching business code
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Built-in workflow engine chains MCP tool calls with conditional logic, retries, and parallel execution for complex automation
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TypeScript-native: full type inference for every IBGE Nomes tool response with IDE autocomplete and compile-time checks
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One-command deployment to any Node.js host. Vercel, Railway, Fly.io, or your own infrastructure
IBGE Nomes in Mastra AI
IBGE Nomes and 4,000+ other MCP servers. One platform. One governance layer.
Teams that connect IBGE Nomes to Mastra AI 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 Mastra AI
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 Mastra AI 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 Mastra AI
Every tool call from Mastra AI 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 Mastra AI connect to MCP servers?
Create an MCPClient with the server URL and pass it to your agent. Mastra discovers all tools and makes them available with full TypeScript types.
Can Mastra agents use tools from multiple servers?
Yes. Pass multiple MCP clients to the agent constructor. Mastra merges all tool schemas and the agent can call any tool from any server.
Does Mastra support workflow orchestration?
Yes. Mastra has a built-in workflow engine that lets you chain MCP tool calls with branching logic, error handling, and parallel execution.
createMCPClient not exported
Install: npm install @mastra/mcp
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