How to Use the Brasil.io MCP in Pydantic AI

Validate Brazilian public data with Pydantic AI models and strict runtime checking.

See Vinkius in Action

Works with every AI agent you already use

…and any MCP-compatible client

MCP Servers - Free for Subscribers

Connect Brasil.io MCP to Pydantic AI

Create your Vinkius account to connect Brasil.io to Pydantic AI and route execution through our secure gateway. The platform manages server hosting, runtime updates, and security layers. Configuration requires no manual server provisioning.

GDPR Free for Subscribers

Setup Brasil.io with Pydantic AI

Ask AI about this MCP

ChatGPT

Claude

Perplexity

Type-check schemas in Pydantic AI

Call `get_table_metadata` to retrieve column definitions. Pydantic AI then validates these against your predefined models to ensure data integrity. This catches mismatches immediately. If the table structure changes, your agent throws a validation error rather than processing corrupted data.

List datasets for Pydantic AI

Run `list_datasets` to get a list of available tables. Your agent receives a validated response that fits your expected structure. This turns raw API output into typed objects. You no longer have to worry about missing fields or unexpected null values.

Query with Pydantic AI validation

Use `query_table_data` to pull records filtered by your specific requirements. The response is immediately passed through your Pydantic models for strict verification. This setup guarantees that every record your agent processes is valid. It stops bad data from entering your system.

Setup guide

Set up Brasil.io MCP in Pydantic AI

Prerequisites

Python 3.10+ installed
pydantic-ai-slim[fastmcp] package
Active Vinkius subscription with a valid endpoint token

1

Install Pydantic AI with FastMCP
Run pip install "pydantic-ai-slim[fastmcp]". The FastMCP toolset replaces the deprecated MCPServerHTTP class with full protocol support.
2

Configure the FastMCPToolset
Pass a JSON-style config dict to FastMCPToolset with your Vinkius URL. Replace [YOUR_TOKEN_HERE] with your token from cloud.vinkius.com. Supports Streamable HTTP, SSE, and Stdio transports.
3

Create and run your agent
Pass the toolset to Agent(toolsets=[toolset]) and call agent.run(). Swap openai:gpt-4o for any supported model — Anthropic, Google, Mistral, or Groq.

agent.py

from pydantic_ai import Agent
from pydantic_ai.toolsets.fastmcp import FastMCPToolset

toolset = FastMCPToolset({
    "mcpServers": {
        "brasilio-mcp": {
            "url": "https://edge.vinkius.com/[YOUR_TOKEN_HERE]/mcp"
        }
    }
})

agent = Agent(
    "openai:gpt-4o",
    toolsets=[toolset],
    system_prompt="You have access to Brasil.io tools.",
)

result = await agent.run("List recent Brasil.io transactions")
print(result.output)

Get your connection token →

Independent Platform Disclaimer: Vinkius is an independent platform and is not affiliated with, endorsed by, sponsored by, verified by, or otherwise authorized by Brasil.io. All third-party trademarks, logos, and brand names are the property of their respective owners. Their use on this website is strictly for informational purposes to identify service compatibility and interoperability.

Why Choose Vinkius

Vinkius connects your tools to AI with real-time monitoring and automatic cost savings — all from one dashboard.

Connect Brasil.io now

Real-time monitoring

Live

visibility into every interaction

Connect your favorite tools to your AI and see exactly what's happening — every request, every response, in real time.

Built-in savings

60%

lower AI costs

Vinkius compresses data between your apps and your AI automatically. Lower bills every month — no configuration required.

Single dashboard

One

place for every integration

Every tool your AI connects to, managed from a single screen. One account, complete control.

Common questions about Brasil.io MCP in Pydantic AI

Define a Pydantic model that matches the table schema. The framework automatically validates the output of `query_table_data` against your model, raising an error if the fields don't match.

Yes, it raises a validation error immediately. This prevents your agent from making decisions based on bad or malformed public records.

Yes, it supports SSE and Streamable HTTP. You configure the server in your `MCPToolset`, and the agent handles the transport asynchronously.

The server imposes limits on result sets to keep performance high. You should keep your JSON filter strings specific to avoid hitting these caps.

The server only reads public Brazilian datasets. No user data is transmitted or stored, and your Pydantic models remain entirely local to your execution environment.

Use it with your favorite AI tools

Connect this server to Cursor, Claude, VS Code, and more.

OpenAI Agents SDK sdk-python

Google ADK sdk-python

Pydantic AI sdk-python

Vercel AI SDK sdk-typescript