How to Use the GoCardless MCP in Pydantic AI

Q: How do I add the GoCardless MCP server toolset to a Pydantic AI agent?

Use the MCPToolset class pointing to your Vinkius HTTP server URL. Pass this toolset instance inside the toolsets argument when initializing your Pydantic AI agent.

Q: How do I check if a customer has an active bank mandate?

Your agent can call getmandatedetails using the customer's mandate identifier. This returns the status, bank name, and authorization state of the account.

Run type-safe bank debit collections using the GoCardless MCP Server and Pydantic AI with strict runtime validation.

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Connect GoCardless MCP to Pydantic AI

Create your Vinkius account to connect GoCardless 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 GoCardless with Pydantic AI

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Type-Safe Bank Debit Flows via Pydantic AI

The `create_new_customer` and `list_active_mandates` tools let your Pydantic AI agent register bank payers with strict schema validation. Every response is validated against Pydantic models at runtime, preventing silent errors from malformed API payloads. Once authorized, the agent triggers `collect_payment` to initiate the bank transfer. If a customer cancels their subscription, the agent calls `stop_pending_payment` to stop the transaction before the processing window closes.

Validate Transaction Statuses and Clearing Logs

The `get_payment_status` and `list_payment_history` tools let your agent track bank settlement delays without silent failures. Bank debits do not settle instantly, requiring your system to track their progress carefully. To build a reliable audit trail, the agent calls `list_system_events` to retrieve the complete log of ledger changes. Because Pydantic AI enforces strict typing, any unexpected field types from the bank gateway are caught immediately.

Manage Creditor Entities and Active Subscriptions

The `list_account_creditors` and `get_customer_details` tools give your agent type-safe access to payout destinations and customer profiles. Large business accounts often route payments to different bank targets, and these tools identify active payout destinations. To keep recurring billing synchronized, the agent calls `list_recurring_payments` to check active subscription schedules. This lets your backend system detect billing gaps without relying on fragile cron jobs.

Setup guide

Set up GoCardless 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": {
        "gocardless-alternative-mcp": {
            "url": "https://edge.vinkius.com/[YOUR_TOKEN_HERE]/mcp"
        }
    }
})

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

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

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Common questions about GoCardless MCP in Pydantic AI

Use the `MCPToolset` class pointing to your Vinkius HTTP server URL. Pass this toolset instance inside the `toolsets` argument when initializing your Pydantic AI agent.

If the server returns unexpected transaction data, Pydantic AI raises a validation error at runtime. This prevents your agent from processing corrupted bank records or hallucinated fields.

Yes. Pydantic AI is model-agnostic, meaning you can connect this toolset to local models, OpenAI, or Anthropic while maintaining strict type validation.

Your agent can call `get_mandate_details` using the customer's mandate identifier. This returns the status, bank name, and authorization state of the account.

This MCP server handles customer bank details, mandate signatures, and payment histories. Vinkius secures these payloads using ephemeral V8 isolates, routing all API requests through a single-token gateway that never exposes credentials to the LLM.

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