How to Use the Flexport MCP in LangChain

Q: Can LangChain use Flexport tools to reconcile invoices?

Yes. Your agent can call listinvoices and listshipmentinvoices to compare billing data against your internal shipment records.

Chain your Flexport logistics data directly into LangChain agents to automate supply chain updates and purchase order workflows.

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Connect Flexport MCP to LangChain

Create your Vinkius account to connect Flexport to LangChain 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 Flexport with LangChain

Ask AI about this MCP

ChatGPT

Claude

Perplexity

Automated shipment status tracking

Connect your agent to `list_shipments` to pull real-time freight location data into your LangChain workflow. You can trigger alerts the moment a shipment status changes. Your agent parses the output from `get_shipment` to update your database automatically. This removes the need for manual status checks.

Purchase order management chains

Use `create_purchase_order` to generate new orders directly from your agent's reasoning process. You define the logic for when an order is necessary. Input validation happens within your chain by checking `list_purchase_orders` first. This prevents duplicate entries and keeps your records clean.

Logistics document retrieval

Fetch specific commercial invoices or shipping documents using `get_document` within your LangChain environment. Your agent decides which file is required based on the current shipment status. Use `list_documents` to audit your files. The agent handles the metadata so your team only touches the documents that matter.

Setup guide

Set up Flexport MCP in LangChain

Prerequisites

Python 3.10+ installed
langchain-mcp-adapters + langgraph packages
Active Vinkius subscription with a valid endpoint token

1

Install dependencies
Run pip install langchain-mcp-adapters langgraph langchain-openai. The MCP adapters package converts MCP tools into native LangChain BaseTool objects.
2

Connect via HTTP transport
Use MultiServerMCPClient with "transport": "http" pointing to your Vinkius endpoint. Replace [YOUR_TOKEN_HERE] with your token from cloud.vinkius.com.
3

Create a ReAct agent
Pass the discovered tools to create_react_agent() from LangGraph. The agent automatically routes Flexport tool calls through the MCP protocol.
4

Run with any LLM
Swap ChatOpenAI for ChatAnthropic, ChatGoogleGenerativeAI, or any LangChain-compatible model. The MCP tools work identically across all providers.

agent.py

from langchain_mcp_adapters.client import MultiServerMCPClient
from langgraph.prebuilt import create_react_agent
from langchain_openai import ChatOpenAI

async with MultiServerMCPClient({
    "flexport-mcp": {
        "transport": "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,
    )
    result = await agent.ainvoke({
        "messages": "List recent Flexport transactions"
    })
    print(result["messages"][-1].content)

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Common questions about Flexport MCP in LangChain

You connect your MCP server endpoint to the LangChain adapter. Once configured, your agents can call logistics tools directly in their execution chains.

Yes. Your agent can call `list_invoices` and `list_shipment_invoices` to compare billing data against your internal shipment records.

The MCP server handles all authentication. Your credentials never touch the agent's logic layer, keeping your shipment data isolated.

You can catch errors in your LangGraph state. Use your agent's error-handling logic to retry the specific tool call or notify a human operator.

Only the data requested by your specific tool calls is returned. Sensitive commercial invoices are only accessed when you explicitly invoke the relevant tool.

Use it with your favorite AI tools

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