How to Use the Airwallex MCP in LangChain

Q: Can a LangChain agent chain Airwallex getfxrates and listtransfers together?

Yes, that is how LangChain shines. The output of getfxrates goes directly into the decision-making loop for listtransfers to evaluate past transfer costs against live market rates.

Run complex multi-currency chains with LangChain and this Airwallex MCP Server to move money automatically.

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Connect Airwallex MCP to LangChain

Create your Vinkius account to connect Airwallex 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 Airwallex with LangChain

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Run FX-driven payment chains with this MCP Server

The `get_fx_rates` tool lets your LangChain agent pull real-time currency conversion rates directly into your execution chain. Your agent can immediately feed these live quotes into `list_transfers` to verify if a pending international transfer matches your target rate. Because LangChain links tool outputs sequentially, the agent makes decisions without hardcoded logic. You see every step of the rate evaluation and transfer matching inside LangSmith.

Track global balances inside multi-step chains

The `get_balance` tool checks your current holdings across different currency wallets to feed the next link in your chain. If the balance falls below a threshold, the chain automatically invokes `list_accounts` to find funding sources. This setup lets your LangChain agent handle treasury routing dynamically using the MCP standard. You get a clear log of how your funds are distributed across accounts without writing custom API integration code.

ReAct-based beneficiary verification

The `list_beneficiaries` tool retrieves your approved recipient list so your LangChain agent can validate payment targets. The agent cross-references this list with `list_payments` to ensure you aren't sending duplicate funds to the same contact. By letting the agent reason through these tools, you prevent payment errors. The entire validation process runs as a single, observable chain before any transaction executes.

Setup guide

Set up Airwallex 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 Airwallex 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({
    "airwallex-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 Airwallex transactions"
    })
    print(result["messages"][-1].content)

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Common questions about Airwallex MCP in LangChain

You configure the credentials once in the Vinkius platform. The MCP Server handles the authentication, meaning your LangChain code only needs the single connection token to access the tools.

Yes, that is how LangChain shines. The output of `get_fx_rates` goes directly into the decision-making loop for `list_transfers` to evaluate past transfer costs against live market rates.

LangSmith logs every single input and output from tools like `list_payments` and `get_balance`. You can inspect the exact JSON payloads and execution latency for every financial query your agent makes.

You can use LangGraph by passing the tools directly to your state graph. This lets your agent loop through `list_accounts` and `get_balance` until it resolves your treasury state.

Your account balances and transfer histories never persist on our servers. The MCP connection runs in an isolated, ephemeral sandbox that securely routes requests directly to the API, keeping your financial data private.

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