How to Use the Airwallex MCP in Pydantic AI

Q: How does Pydantic AI validate data returned by the Airwallex server?

The framework intercepts the tool output from tools like getbalance and parses it through Pydantic models. If the Airwallex server returns unexpected fields or missing data types, Pydantic AI raises a validation error immediately.

Run type-safe Airwallex financial workflows in Pydantic AI with strict runtime validation on every transfer.

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Connect Airwallex MCP to Pydantic AI

Create your Vinkius account to connect Airwallex to Pydantic AI 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 Pydantic AI

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Type-safe Airwallex balance checks in Pydantic AI

Bring strict runtime validation to your treasury operations by connecting this MCP Server to your Pydantic AI agents. When your agent calls `get_balance` or `list_accounts`, every field in the response is validated against Pydantic models before your code can use it. This prevents silent data corruption or hallucinated account balances. If the API structure changes or returning data is malformed, your application fails loudly and immediately, protecting your financial logic from unpredictable model outputs.

Validate cross-border transfers and beneficiaries

Managing global vendors requires absolute precision. By exposing `list_beneficiaries` and `list_transfers` to your agents, you can build workflows that double-check recipient details against your database. Pydantic AI ensures that the structured data returned by these tools matches your exact schema. Your agent can confidently check past transfers without the risk of parsing raw, unvalidated JSON payloads.

Monitor live payments and FX conversions safely

Query live currency quotes using `get_fx_rates` and track settlement progress with `list_payments`. Because Pydantic AI is model-agnostic, you can use these tools with OpenAI, Anthropic, or local models while maintaining strict type safety. You configure this by passing the Vinkius HTTP endpoint to the MCP toolset class. This unified approach sets up the SSE or HTTP transport, letting your agent fetch live rates securely.

Setup guide

Set up Airwallex MCP in Pydantic AI

Prerequisites

Python 3.10+ installed
pydantic-ai-slim[fastmcp] package
Active Vinkius subscription with a valid endpoint token

1

Install Pydantic AI with FastMCP
Run pip install "pydantic-ai-slim[fastmcp]". The FastMCP toolset replaces the deprecated MCPServerHTTP class with full protocol support.
2

Configure the FastMCPToolset
Pass a JSON-style config dict to FastMCPToolset with your Vinkius URL. Replace [YOUR_TOKEN_HERE] with your token from cloud.vinkius.com. Supports Streamable HTTP, SSE, and Stdio transports.
3

Create and run your agent
Pass the toolset to Agent(toolsets=[toolset]) and call agent.run(). Swap openai:gpt-4o for any supported model — Anthropic, Google, Mistral, or Groq.

agent.py

from pydantic_ai import Agent
from pydantic_ai.toolsets.fastmcp import FastMCPToolset

toolset = FastMCPToolset({
    "mcpServers": {
        "airwallex-mcp": {
            "url": "https://edge.vinkius.com/[YOUR_TOKEN_HERE]/mcp"
        }
    }
})

agent = Agent(
    "openai:gpt-4o",
    toolsets=[toolset],
    system_prompt="You have access to Airwallex tools.",
)

result = await agent.run("List recent Airwallex transactions")
print(result.output)

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Common questions about Airwallex MCP in Pydantic AI

The framework intercepts the tool output from tools like `get_balance` and parses it through Pydantic models. If the Airwallex server returns unexpected fields or missing data types, Pydantic AI raises a validation error immediately.

Install the MCP package, then initialize your connection using the toolset class with your Vinkius endpoint. Pass this toolset object into your Agent's toolsets list to give it access to tools like `list_payments`.

Yes, Pydantic AI is model-agnostic. You can run the Airwallex toolset with local models or commercial APIs, and the framework will still enforce strict schema validation on tools like `get_fx_rates`.

No, Vinkius handles the authentication with Airwallex. Your Pydantic AI application only needs the Vinkius endpoint token, keeping your sensitive financial credentials out of your local environment variables.

All beneficiary lists and payment records are fetched through an ephemeral V8 sandbox on Vinkius. This zero-trust architecture ensures that sensitive payment details and vendor bank info are never cached, stored, or exposed to third parties.

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