How to Use the Airwallex MCP in AutoGen

Q: How do AutoGen agents share Airwallex tool outputs?

When an agent calls listaccounts, the resulting data is posted directly into the group chat context. All other agents in the conversation can immediately read and analyze those account details.

Deploy multi-agent AutoGen teams to debate and verify your Airwallex transfers before execution.

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Connect Airwallex MCP to AutoGen

Create your Vinkius account to connect Airwallex 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 Airwallex with AutoGen

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Multi-agent balance verification via MCP Server

The `get_balance` tool lets your AutoGen treasury agent pull real-time funding levels to share with the rest of the agent group. A separate compliance agent can then analyze these balances against pending transfer requests. This collaborative setup ensures no single agent makes financial decisions in isolation. The agents debate funding strategies using the exact, live balances retrieved from your account.

Consensus-driven FX rate evaluation

The `get_fx_rates` tool provides live currency quotes that your AutoGen agents use to negotiate the best conversion times. An execution agent proposes a trade, while an analyst agent checks the rate against historical limits. By requiring consensus over MCP before proceeding, you reduce the risk of executing transfers during high-volatility windows. The entire conversation is logged, showing how the agents agreed on the rate.

Automated transfer reconciliation debates

The `list_transfers` tool retrieves your complete transfer history, allowing your AutoGen agents to cross-reference past activity. A reconciliation agent matches these records against `list_payments` to spot discrepancies. If a discrepancy is found, the agents discuss the issue and flag the exact transaction for human review. This automates the tedious work of manual ledger matching through collaborative debate.

Setup guide

Set up Airwallex 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 Airwallex 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="Airwallex_assistant",
    model_client=OpenAIChatCompletionClient(model="gpt-4o"),
    tools=tools,
)

result = await agent.run("List recent Airwallex 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="Airwallex_assistant",
        model_client=OpenAIChatCompletionClient(model="gpt-4o"),
        workbench=workbench,
    )

    result = await agent.run("List recent Airwallex 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 Airwallex. 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 Airwallex MCP in AutoGen

When an agent calls `list_accounts`, the resulting data is posted directly into the group chat context. All other agents in the conversation can immediately read and analyze those account details.

Yes, you can set up a multi-agent group where one agent checks `get_balance` and another verifies the recipient using `list_beneficiaries` before any action is approved.

The AutoGen MCP adapter automatically converts the JSON schemas of tools like `get_fx_rates` into the format required by your LLM. You do not need to write any manual conversion code.

You should use the Streamable HTTP transport. This allows your AutoGen agents to connect securely over a single MCP endpoint token without complex local setup.

Your transfer logs and transaction details are processed entirely in memory within a zero-trust MCP Server sandbox. No financial data is written to persistent storage, keeping your treasury conversations completely confidential.

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