How to Use the Aracaju MCP in AutoGen

Q: How do AutoGen agents share Aracaju data with each other?

Agents pass the JSON outputs from listexpenses through their conversational context. This allows all agents in the group chat to analyze the same municipal spending records.

Deploy AutoGen agents to debate and audit Aracaju city contracts and public spending autonomously.

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Connect Aracaju MCP to AutoGen

Create your Vinkius account to connect Aracaju to AutoGen 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 AutoGen

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Audit Aracaju contracts using AutoGen agents

The `list_contracts` tool pulls signed municipal agreements into your multi-agent conversation. One AutoGen agent can fetch the contracts while a second agent analyzes the terms for potential compliance issues. This collaborative approach allows agents to debate whether a contract aligns with public interests. You get a deeper analysis than a single agent could provide on its own.

Verify municipal expenses via this MCP Server

The `list_expenses` tool retrieves raw city spending data, which your agents review in real-time. This MCP Server gives your AutoGen agents the live data they need to cross-check municipal outlays against approved budgets. Your agents can argue over whether specific expenses seem inflated or out of place. You benefit from a consensus-driven process that thoroughly vets flagged items.

Analyze bids and personnel with AutoGen

The `list_bids` tool and `list_personnel` tool allow your agents to cross-reference public tenders with city employee databases. AutoGen agents can work together to ensure that no city officials are bidding on public contracts. One agent manages the bidding data while another tracks the payroll records. They exchange messages to flag potential conflicts of interest automatically.

Setup guide

Set up Aracaju MCP in AutoGen

Prerequisites

Python 3.10+ installed
autogen-ext[mcp] package
Active Vinkius subscription with a valid endpoint token

1

Install AutoGen with MCP
Run pip install "autogen-ext[mcp]" autogen-agentchat. The MCP extension includes mcp_server_tools for stateless tool access.
2

Fetch tools from the MCP
Call mcp_server_tools(SseServerParams(url=...)) with your Vinkius endpoint. Replace [YOUR_TOKEN_HERE] with your token from cloud.vinkius.com.
3

Run your agent
Pass the tools to AssistantAgent and call agent.run(). The agent invokes Aracaju tools and returns structured results.

agent.py

from autogen_ext.tools.mcp import SseServerParams, mcp_server_tools
from autogen_agentchat.agents import AssistantAgent
from autogen_ext.models.openai import OpenAIChatCompletionClient

server_params = SseServerParams(
    url="https://edge.vinkius.com/[YOUR_TOKEN_HERE]/mcp"
)

tools = await mcp_server_tools(server_params)

agent = AssistantAgent(
    name="Aracaju_assistant",
    model_client=OpenAIChatCompletionClient(model="gpt-4o"),
    tools=tools,
)

result = await agent.run("List recent Aracaju data")
print(result.messages[-1].content)

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Prerequisites

Python 3.10+ installed
autogen-ext[mcp] + autogen-agentchat
Active Vinkius subscription with a valid endpoint token

1

Install dependencies
Same packages as above. McpWorkbench is ideal when your agent needs stateful sessions across multiple tool calls.
2

Use McpWorkbench as context manager
Wrap your agent in async with McpWorkbench(...) to maintain shared state and resources. The workbench manages the full MCP session lifecycle.
3

Run with workbench
Pass workbench=workbench to your agent. State is preserved across multiple tool calls within the same session.

agent.py

from autogen_ext.tools.mcp import McpWorkbench, SseServerParams
from autogen_agentchat.agents import AssistantAgent
from autogen_ext.models.openai import OpenAIChatCompletionClient

server_params = SseServerParams(
    url="https://edge.vinkius.com/[YOUR_TOKEN_HERE]/mcp"
)

async with McpWorkbench(server_params) as workbench:
    agent = AssistantAgent(
        name="Aracaju_assistant",
        model_client=OpenAIChatCompletionClient(model="gpt-4o"),
        workbench=workbench,
    )

    result = await agent.run("List recent Aracaju data")
    print(result.messages[-1].content)

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 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 AutoGen

Agents pass the JSON outputs from `list_expenses` through their conversational context. This allows all agents in the group chat to analyze the same municipal spending records.

Yes, you can register the tools to specific agents, like an auditor agent, while keeping other agents focused strictly on formatting or report generation.

Use the server tools utility with your Vinkius HTTP URL to fetch the tools, then pass that list directly into your assistant agent constructor.

Yes, the raw financial data returns values in Brazilian Reais, which your agents can easily parse and convert to other currencies if needed.

The data retrieved is entirely public municipal records, meaning no sensitive personal info is involved. Vinkius isolates each agent session, ensuring your private audit conversations and queries are never leaked or stored.

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