How to Use the Aracaju MCP in OpenAI Agents SDK

Query Aracaju municipal data directly within your OpenAI Agents SDK production pipeline.

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Connect Aracaju MCP to OpenAI Agents SDK

Create your Vinkius account to connect Aracaju to OpenAI Agents SDK 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 OpenAI Agents SDK

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Claude

Perplexity

Public finance tracking for OpenAI Agents SDK

Feed your agent real-time budget data. It uses `list_expenses` and `list_revenues` to pull raw numbers from the city’s treasury. You won't spend hours scraping PDFs. Just call the tools and let your Python agent parse the fiscal reality.

Bidding and contract oversight

Track active tenders using `list_bids` to catch new opportunities. Your agent flags relevant updates before they hit the morning news. Verify who got paid with `list_contracts`. It keeps your agent grounded in actual signed agreements rather than hearsay.

Personnel and payroll auditing

Monitor public spending on staff through `list_personnel`. Your agent maps out the payroll structure without manual lookups. Safety matters here. Since this is an MCP Server, your agent validates every request through the SDK's built-in guardrails.

Setup guide

Set up Aracaju MCP in OpenAI Agents SDK

Prerequisites

Python 3.10+ installed
openai-agents package (pip install openai-agents)
Active Vinkius subscription with a valid endpoint token

1

Install the SDK

Run pip install openai-agents to install the OpenAI Agents SDK. The MCP integration is built-in — no extra dependencies needed.
2

Connect via SSE transport

Use MCPServerSse with your Vinkius endpoint URL. Replace [YOUR_TOKEN_HERE] with your token from cloud.vinkius.com. The SDK auto-discovers all Aracaju tools at runtime.
3

Create your Agent

Pass the MCP to Agent(mcp_servers=[server]). The agent receives Aracaju tools as native definitions — JSON schemas resolve automatically.
4

Run the agent

Call Runner.run(agent, prompt) to execute. The agent invokes the appropriate Aracaju tools and returns structured results. Copy the full example on the right to get started.

agent.py

import asyncio
from agents import Agent, Runner
from agents.mcp import MCPServerSse

async def main():
    async with MCPServerSse(
        url="https://edge.vinkius.com/[YOUR_TOKEN_HERE]/mcp"
    ) as server:
        agent = Agent(
            name="Aracaju Agent",
            instructions="You have access to Aracaju tools.",
            mcp_servers=[server],
        )
        result = await Runner.run(agent, "List recent transactions")
        print(result.final_output)

asyncio.run(main())

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Independent Platform Disclaimer: Vinkius is an independent platform and is not affiliated with, endorsed by, sponsored by, verified by, or otherwise authorized by Aracaju Transparency. 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.

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Common questions about Aracaju MCP in OpenAI Agents SDK

Install the server and pass it to your Agent constructor. The tools register automatically so your agent sees the functions immediately.

Yes. It manages the connection via HTTP streams, keeping your memory usage predictable. You get the data you need without overloading the agent.

The server only touches public municipal records. Vinkius secures the transport layer, so your agent only sees what the city publishes.

It relies on standard HTTP transport. Your agent keeps a steady connection to the Vinkius sandbox.

Use the built-in tool logic provided by the SDK. You can limit the output before it hits your agent's context window.

Use it with your favorite AI tools

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

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