How to Use the Aracaju MCP in Pydantic AI

Get type-safe Aracaju municipal insights with the Pydantic AI framework.

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Connect Aracaju MCP to Pydantic AI

Create your Vinkius account to connect Aracaju 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.

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Setup Aracaju with Pydantic AI

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Claude

Perplexity

Strictly typed Aracaju data for Pydantic AI

Your agent expects specific structures when it calls `list_revenues`. Pydantic AI ensures the data matches your models perfectly. If the city's API returns a malformed record, the agent catches it instantly. No garbage data ever hits your logic.

Validating municipal contracts

Use `list_contracts` to fetch agreement details. The framework forces every field into a defined schema. You avoid silent failures. If `list_bids` returns an unexpected format, your agent stops and alerts you.

Auditing expenses and payroll

Check salary data with `list_personnel` and expense data with `list_expenses`. Every item is validated at runtime. Your agent behaves reliably. It relies on the strict types you defined for the city's fiscal data.

Setup guide

Set up Aracaju 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": {
        "aracaju-mcp": {
            "url": "https://edge.vinkius.com/[YOUR_TOKEN_HERE]/mcp"
        }
    }
})

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

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

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Common questions about Aracaju MCP in Pydantic AI

It validates the response against your models. If the server output doesn't fit, the agent throws a clear error.

Yes, it uses the MCPToolset to map server responses to your types. It bridges the gap between raw JSON and your code.

The server only handles public financial records. Vinkius ensures the connection is encrypted and scoped.

You can swap your underlying LLM whenever you want. The server interaction remains consistent and type-safe.

It sees public fiscal transparency data. We enforce type validation on these records to ensure your agent never processes corrupt input.

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

Mastra AI sdk-typescript

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