Bring Open Data
to Pydantic AI
Learn how to connect Mato Grosso do Sul Open Data to Pydantic AI and start using 7 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 Mato Grosso do Sul Open Data MCP Server?
Connect to the Mato Grosso do Sul (MS) Open Data Portal to explore and analyze public information from the Brazilian state. This server allows AI agents to programmatically access datasets, organizations, and specific resource records.
What you can do
- Datasets & Packages — List all available public data packages and retrieve detailed metadata using
list_packagesandget_package. - Resource Inspection — Drill down into specific files or links within datasets to understand their structure with
get_resource. - DataStore Search — Filter and search through actual records in CSVs or spreadsheets directly using
datastore_search. - SQL Queries — Execute complex SQL statements on DataStore resources for advanced data analysis with
datastore_search_sql. - Organizational Context — List the government organizations and groups responsible for the data via
list_organizationsandlist_groups.
How it works
- Subscribe to this server
- Enter your Mato Grosso do Sul Data Portal API Key
- Start querying public state data from Claude, Cursor, or any MCP-compatible client
Who is this for?
- Data Analysts — instantly retrieve and filter state records without manual downloads
- Researchers — automate the collection of public metadata and resource links
- Developers — integrate real-time public data into applications using SQL queries
Built-in capabilities (7)
Search data in a DataStore resource
Execute a SQL query on DataStore resources
Get details of a specific dataset package
Get details of a specific resource
List all groups
List all organizations
List all dataset packages
Why Pydantic AI?
Pydantic AI validates every Mato Grosso do Sul Open Data tool response against typed schemas, catching data inconsistencies at build time. Connect 7 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.
- —
Full type safety: every MCP tool response is validated against Pydantic models, catching data inconsistencies before they reach your application
- —
Model-agnostic architecture. switch between OpenAI, Anthropic, or Gemini without changing your Mato Grosso do Sul Open Data integration code
- —
Structured output guarantee: Pydantic AI ensures tool results conform to defined schemas, eliminating runtime type errors
- —
Dependency injection system cleanly separates your Mato Grosso do Sul Open Data connection logic from agent behavior for testable, maintainable code
Mato Grosso do Sul Open Data in Pydantic AI
Mato Grosso do Sul Open Data and 4,000+ other MCP servers. One platform. One governance layer.
Teams that connect Mato Grosso do Sul Open Data 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 Mato Grosso do Sul Open Data in Pydantic AI
The Mato Grosso do Sul Open Data 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 7 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
Mato Grosso do Sul Open Data for Pydantic AI
Every tool call from Pydantic AI to the Mato Grosso do Sul Open Data MCP Server is protected by DLP redaction, cryptographic audit chains, V8 sandbox isolation, kill switch, and financial circuit breakers.
Frequently asked questions
How do I find specific datasets about health or education?
Use the list_packages tool to see all available dataset names, then use get_package with a specific ID to see the resources and descriptions related to that topic.
Can I perform complex filtering on the data records?
Yes! Use the datastore_search_sql tool to execute standard SQL queries (e.g., SELECT, WHERE, GROUP BY) directly against the DataStore resources for precise analysis.
How do I see which government departments provide the data?
Use the list_organizations action. It will return a list of all state entities and departments that have published data on the portal.
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 Mato Grosso do Sul Open Data 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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