Bring Public Spending
to Pydantic AI
Learn how to connect Sergipe Dados Abertos to Pydantic AI and start using 4 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 Sergipe Dados Abertos MCP Server?
Connect to the Sergipe Transparency Portal and query official government data through natural conversation. This server provides direct access to the open data infrastructure of the State of Sergipe, Brazil.
What you can do
- Expenditures (Despesas) — Query detailed state spending, including payments to suppliers, sub-elements, and inter-governmental transfers by fiscal year.
- Revenues (Receitas) — Monitor state collection, including tax revenue (ICMS, IPVA) and federal transfers with specific date ranges.
- Personnel (Servidores) — Access information about the state workforce, including active and retired employees, positions, and salary data.
- Budget (Orçamento) — Inspect the Annual Budget Law (LOA) and track real-time budget execution for any given fiscal year.
How it works
- Subscribe to this server
- The server connects to the official Sergipe Open Data API
- Start auditing public accounts from Claude, Cursor, or any MCP-compatible client
Who is this for?
- Journalists & Researchers — quickly extract spending data and personnel counts for investigative reporting
- Citizens & Activists — monitor how public resources are being allocated in the state of Sergipe
- Data Analysts — fetch clean JSON data for fiscal analysis without manual CSV downloads
Built-in capabilities (4)
Get state expenditures (Despesas)
Get budget data (Orçamento)
Get state revenues (Receitas)
Get personnel information (Servidores)
Why Pydantic AI?
Pydantic AI validates every Sergipe Dados Abertos tool response against typed schemas, catching data inconsistencies at build time. Connect 4 tools through Vinkius and switch between OpenAI, Anthropic, or Gemini without changing your integration code. full type safety, structured output guarantees, and dependency injection for testable agents.
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Full type safety: every MCP tool response is validated against Pydantic models, catching data inconsistencies before they reach your application
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Model-agnostic architecture. switch between OpenAI, Anthropic, or Gemini without changing your Sergipe Dados Abertos integration code
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Structured output guarantee: Pydantic AI ensures tool results conform to defined schemas, eliminating runtime type errors
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Dependency injection system cleanly separates your Sergipe Dados Abertos connection logic from agent behavior for testable, maintainable code
Sergipe Dados Abertos in Pydantic AI
Sergipe Dados Abertos and 4,000+ other MCP servers. One platform. One governance layer.
Teams that connect Sergipe Dados Abertos to Pydantic 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 Sergipe Dados Abertos in Pydantic AI
The Sergipe Dados Abertos 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 4 tools execute in hardened sandboxes optimized for native MCP execution.
Your AI agents in Pydantic 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
Sergipe Dados Abertos for Pydantic AI
Every tool call from Pydantic AI to the Sergipe Dados Abertos MCP Server is protected by DLP redaction, cryptographic audit chains, V8 sandbox isolation, kill switch, and financial circuit breakers.
Frequently asked questions
Can I filter state expenditures by a specific government body?
Yes. Use the get_despesas tool and provide the codigoOrgao parameter along with the fiscal year to see spending for a specific department.
Is it possible to see the salary and position of state employees?
Yes, the get_servidores tool allows you to fetch personnel data, including positions and remuneration, filtered by month, year, and type of bond.
How can I check the total budget approved for a specific year?
You can use the get_orcamento tool by passing the exercicio (year) parameter. It will return data regarding the Annual Budget Law (LOA) and its execution.
How does Pydantic AI discover MCP tools?
Create an MCPServerHTTP instance with the server URL. Pydantic AI connects, discovers all tools, and generates typed Python interfaces automatically.
Does Pydantic AI validate MCP tool responses?
Yes. When you define result types as Pydantic models, every tool response is validated against the schema. Invalid data raises a clear error instead of silently corrupting your pipeline.
Can I switch LLM providers without changing MCP code?
Absolutely. Pydantic AI abstracts the model layer. your Sergipe Dados Abertos MCP integration works identically with OpenAI, Anthropic, Google, or any supported provider.
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Update: pip install --upgrade pydantic-ai
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