Focus Logística MCP Server for LangChain 7 tools — connect in under 2 minutes
LangChain is the leading Python framework for composable LLM applications. Connect Focus Logística through Vinkius and LangChain agents can call every tool natively. combine them with retrievers, memory, and output parsers for sophisticated AI pipelines.
ASK AI ABOUT THIS MCP SERVER
Vinkius supports streamable HTTP and SSE.
import asyncio
from langchain_mcp_adapters.client import MultiServerMCPClient
from langchain_openai import ChatOpenAI
from langgraph.prebuilt import create_react_agent
async def main():
# Your Vinkius token. get it at cloud.vinkius.com
async with MultiServerMCPClient({
"focus-logistica": {
"transport": "streamable_http",
"url": "https://edge.vinkius.com/[YOUR_TOKEN_HERE]/mcp",
}
}) as client:
tools = client.get_tools()
agent = create_react_agent(
ChatOpenAI(model="gpt-4o"),
tools,
)
response = await agent.ainvoke({
"messages": [{
"role": "user",
"content": "Using Focus Logística, show me what tools are available.",
}]
})
print(response["messages"][-1].content)
asyncio.run(main())
* Every MCP server runs on Vinkius-managed infrastructure inside AWS - a purpose-built runtime with per-request V8 isolates, Ed25519 signed audit chains, and sub-40ms cold starts optimized for native MCP execution. See our infrastructure
About Focus Logística MCP Server
Connect Focus Logística to any AI agent and manage your Brazilian cargo transport documentation — issue CT-e (Conhecimento de Transporte), MDF-e (Manifesto de Carga), close manifests, and download XMLs through natural conversation.
LangChain's ecosystem of 500+ components combines seamlessly with Focus Logística through native MCP adapters. Connect 7 tools via Vinkius and use ReAct agents, Plan-and-Execute strategies, or custom agent architectures. with LangSmith tracing giving full visibility into every tool call, latency, and token cost.
What you can do
- Emit CT-e — Issue transport invoices for all modalities (road, air, rail, waterway)
- Emit MDF-e — Create cargo manifests grouping multiple CT-e documents
- Consult Status — Check authorization and current status of CT-e and MDF-e
- Close Manifests — Mark MDF-e as finished/encerrado after delivery
- Cancel Documents — Cancel CT-e with valid justification
- Download XML — Retrieve XML for accounting and legal compliance
The Focus Logística MCP Server exposes 7 tools through the Vinkius. Connect it to LangChain in under two minutes — no API keys to rotate, no infrastructure to provision, no vendor lock-in. Your configuration, your data, your control.
How to Connect Focus Logística to LangChain via MCP
Follow these steps to integrate the Focus Logística MCP Server with LangChain.
Install dependencies
Run pip install langchain langchain-mcp-adapters langgraph langchain-openai
Replace the token
Replace [YOUR_TOKEN_HERE] with your Vinkius token
Run the agent
Save the code and run python agent.py
Explore tools
The agent discovers 7 tools from Focus Logística via MCP
Why Use LangChain with the Focus Logística MCP Server
LangChain provides unique advantages when paired with Focus Logística through the Model Context Protocol.
The largest ecosystem of integrations, chains, and agents. combine Focus Logística MCP tools with 500+ LangChain components
Agent architecture supports ReAct, Plan-and-Execute, and custom strategies with full MCP tool access at every step
LangSmith tracing gives you complete visibility into tool calls, latencies, and token usage for production debugging
Memory and conversation persistence let agents maintain context across Focus Logística queries for multi-turn workflows
Focus Logística + LangChain Use Cases
Practical scenarios where LangChain combined with the Focus Logística MCP Server delivers measurable value.
RAG with live data: combine Focus Logística tool results with vector store retrievals for answers grounded in both real-time and historical data
Autonomous research agents: LangChain agents query Focus Logística, synthesize findings, and generate comprehensive research reports
Multi-tool orchestration: chain Focus Logística tools with web scrapers, databases, and calculators in a single agent run
Production monitoring: use LangSmith to trace every Focus Logística tool call, measure latency, and optimize your agent's performance
Focus Logística MCP Tools for LangChain (7)
These 7 tools become available when you connect Focus Logística to LangChain via MCP:
cancel_cte
Cancel a CT-e
close_mdfe
Close/Finish a MDF-e
consult_cte
Consult CT-e status
consult_mdfe
Consult MDF-e status
download_xml
Download XML for CT-e or MDF-e
emit_cte
Emit a Conhecimento de Transporte (CT-e)
emit_mdfe
Emit Manifesto de Carga (MDF-e)
Example Prompts for Focus Logística in LangChain
Ready-to-use prompts you can give your LangChain agent to start working with Focus Logística immediately.
"Emit a CT-e for a freight of R$1,200.00 from SP to RJ."
"Close the MDF-e reference MDF-001."
"Download the XML for CT-e reference CTE-001."
Troubleshooting Focus Logística MCP Server with LangChain
Common issues when connecting Focus Logística to LangChain through the Vinkius, and how to resolve them.
MultiServerMCPClient not found
pip install langchain-mcp-adaptersFocus Logística + LangChain FAQ
Common questions about integrating Focus Logística MCP Server with LangChain.
How does LangChain connect to MCP servers?
langchain-mcp-adapters to create an MCP client. LangChain discovers all tools and wraps them as native LangChain tools compatible with any agent type.Which LangChain agent types work with MCP?
Can I trace MCP tool calls in LangSmith?
Connect Focus Logística with your favorite client
Step-by-step setup guides for every MCP-compatible client and framework:
Anthropic's native desktop app for Claude with built-in MCP support.
AI-first code editor with integrated LLM-powered coding assistance.
GitHub Copilot in VS Code with Agent mode and MCP support.
Purpose-built IDE for agentic AI coding workflows.
Autonomous AI coding agent that runs inside VS Code.
Anthropic's agentic CLI for terminal-first development.
Python SDK for building production-grade OpenAI agent workflows.
Google's framework for building production AI agents.
Type-safe agent development for Python with first-class MCP support.
TypeScript toolkit for building AI-powered web applications.
TypeScript-native agent framework for modern web stacks.
Python framework for orchestrating collaborative AI agent crews.
Leading Python framework for composable LLM applications.
Data-aware AI agent framework for structured and unstructured sources.
Microsoft's framework for multi-agent collaborative conversations.
Connect Focus Logística to LangChain
Get your token, paste the configuration, and start using 7 tools in under 2 minutes. No API key management needed.