How to Use the Focus Logística MCP in AutoGen
Deploy AutoGen agent teams to negotiate, emit, and audit Brazilian CT-e and MDF-e documents via Focus Logística.
Works with every AI agent you already use
…and any MCP-compatible client
Connect Focus Logística MCP to AutoGen
Create your Vinkius account to connect Focus Logística 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.
Multi-Agent Document Auditing and Emission
The `emit_cte` and `emit_mdfe` tools are assigned to specialized AutoGen agents to separate Focus Logística drafting from validation. One AutoGen agent compiles the shipping data, while a compliance agent reviews the Focus Logística payload before execution. This MCP capability stops bad tax data before it hits Focus Logística servers. You avoid costly validation failures and potential tax fines through automated AutoGen team review.
Collaborative Manifest Closure and Verification
The `close_mdfe` and `consult_mdfe` tools allow your AutoGen agents to coordinate the end-of-transit workflow. An AutoGen tracking agent monitors the progress, and a logistics agent closes the Focus Logística manifest once delivery is verified. If the Focus Logística closure fails, the AutoGen agents debate the resolution. They check the Focus Logística status, pull the logs, and determine whether to retry or escalate.
Automated Error Resolution via MCP Server Tools
The `cancel_cte` tool is managed by a dedicated risk-mitigation agent in your AutoGen network. When an emission error is detected, this agent coordinates with other AutoGen agents to cancel the incorrect Focus Logística document. The AutoGen agents negotiate the cancellation window. They ensure the Focus Logística cancellation occurs within the legal timeframe allowed by Brazilian tax authorities.
Set up Focus Logística 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 includesmcp_server_toolsfor 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
AssistantAgentand callagent.run(). The agent invokes Focus Logística tools and returns structured results.
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="Focus Logística_assistant",
model_client=OpenAIChatCompletionClient(model="gpt-4o"),
tools=tools,
)
result = await agent.run("List recent Focus Logística data")
print(result.messages[-1].content) 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.
McpWorkbenchis 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=workbenchto your agent. State is preserved across multiple tool calls within the same session.
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="Focus Logística_assistant",
model_client=OpenAIChatCompletionClient(model="gpt-4o"),
workbench=workbench,
)
result = await agent.run("List recent Focus Logística data")
print(result.messages[-1].content) Independent Platform Disclaimer: Vinkius is an independent platform and is not affiliated with, endorsed by, sponsored by, verified by, or otherwise authorized by Focus NFe. 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 Focus Logística MCP in AutoGen
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