How to Use the Cuiabá Transparency MCP in OpenAI Agents SDK

Q: Can OpenAI Agents SDK read Cuiabá Transparency payroll data?

Yes. The server exposes a listpersonnel tool. Your agent calls it to retrieve public servant salaries and positions directly.

Build production-ready agents with OpenAI Agents SDK that query real-time municipal budgets and contracts from Cuiabá.

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Connect Cuiabá Transparency MCP to OpenAI Agents SDK

Create your Vinkius account to connect Cuiabá Transparency 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 Cuiabá Transparency with OpenAI Agents SDK

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Track municipal spending via OpenAI Agents SDK

Your agent needs exact figures before it makes a recommendation. Calling `list_expenses` pulls raw expenditure data right into your Python environment. You get the actual numbers Cuiabá reported instead of guessing. Handoffs work perfectly here. One specialized agent fetches the data using `list_budget`, then passes the structured context to an analysis agent. Guardrails ensure your bot only reads public records and never attempts unsupported writes.

Audit public contracts with this MCP Server

Digging through city tenders usually requires human eyes. Now your code runs `list_contracts` to pull active vendor agreements directly. It reads the terms, amounts, and involved parties without leaving the OpenAI trace dashboard. Checking payroll is just as direct. Running `list_personnel` returns public servant data. You can cross-reference names against vendor lists automatically to spot conflicts of interest.

Monitor city revenue streams

Tax collection and municipal income fluctuate constantly. Your code triggers `list_revenues` to grab the latest deposit records. The agent auto-discovers this tool as soon as you pass the endpoint. Setup takes two lines. You initialize `MCPServerStreamableHttp` with your Vinkius URL and hand it to the Agent constructor. Setting `cacheToolsList=True` drops the latency on repeated queries.

Setup guide

Set up Cuiabá Transparency 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 Cuiabá Transparency tools at runtime.
3

Create your Agent

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

Run the agent

Call Runner.run(agent, prompt) to execute. The agent invokes the appropriate Cuiabá Transparency 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="Cuiabá Transparency Agent",
            instructions="You have access to Cuiabá Transparency tools.",
            mcp_servers=[server],
        )
        result = await Runner.run(agent, "List recent transactions")
        print(result.final_output)

asyncio.run(main())

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 Cuiabá Transparency Portal. 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 Cuiabá Transparency MCP in OpenAI Agents SDK

Install the openai-agents package via pip. Create an MCPServerStreamableHttp object with your Vinkius endpoint and pass it into the mcp_servers array. Your agent detects the tools automatically.

Yes. The server exposes a list_personnel tool. Your agent calls it to retrieve public servant salaries and positions directly.

It handles them perfectly. You assign one agent to fetch data using list_expenses and hand the result off to a separate reasoning agent. Tracing tracks the exact handoff payload.

Scraping government portals breaks constantly. This MCP connection provides a stable interface to actual city records. You get structured JSON instead of parsing messy HTML tables.

We run the server inside a V8 Isolate Sandbox. Your agent fetches public servant salaries and vendor contracts, but the ephemeral container shuts down immediately after the request. Nothing gets cached on our end.

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