How to Use the Finmo MCP in Pydantic AI

Q: How do I integrate the Finmo MCP Server with Pydantic AI?

Use pip install "pydantic-ai-slimmcp", instantiate MCPToolset with your Vinkius server URL, and pass it to the Pydantic AI Agent constructor via the toolsets argument.

Q: Can a Pydantic AI agent generate Finmo deposit details for a customer?

Yes. The Pydantic AI agent calls createcustomer to set up the profile, then executes createpayin to generate virtual account details using listpayinmethods.

Q: How does Pydantic AI handle currency conversion checks?

The Pydantic AI agent calls getfxrate to fetch real-time conversion rates. The response is validated against a strict schema, allowing the agent to safely compute transfers.

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Setup Finmo with Pydantic AI

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Type-safe payout execution with Pydantic AI

This MCP Server guarantees that your agent never executes a payout with malformed data by validating inputs before calling `create_payout`. Pydantic AI catches missing routing codes or negative amounts before they hit the API. If the bank returns an unexpected response structure, the Pydantic AI framework rejects the payload at runtime. The agent reads the exact validation error, checks `list_beneficiaries` to find the correct bank details, and retries the transfer safely.

Runtime-validated ledger reconciliation

Reconciling books requires absolute data integrity, which is why the Pydantic AI agent calls `list_payins` and `list_refunds` to fetch raw transaction data. The framework automatically parses the results into strongly-typed Pydantic models. When matching refunds to customers, the Pydantic AI agent queries `list_customers` to ensure the customer ID matches the schema. This strict validation prevents silent database corruption and ensures your accounting agent always works with clean data.

Multi-currency wallet tracking

Managing global cash flow requires monitoring multiple currencies, which your Pydantic AI agent does by querying `list_wallets` to fetch balances across your organization. This MCP Server integration lets you track balances securely and uses `get_fx_rate` to calculate total liquidity in your base currency. Because Pydantic AI is model-agnostic, you can run this workflow on cheap local models or advanced commercial LLMs. The tool schemas for `list_virtual_accounts` are parsed identically, ensuring consistent behavior regardless of the underlying model.

Setup guide

Set up Finmo 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": {
        "finmo-mcp": {
            "url": "https://edge.vinkius.com/[YOUR_TOKEN_HERE]/mcp"
        }
    }
})

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

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

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Common questions about Finmo MCP in Pydantic AI

Use `pip install "pydantic-ai-slim[mcp]"`, instantiate `MCPToolset` with your Vinkius server URL, and pass it to the Pydantic AI `Agent` constructor via the `toolsets` argument.

The framework raises a validation error immediately. This prevents your Pydantic AI agent from processing corrupted data or hallucinating fields when reading from `list_wallets`.

Yes. The Pydantic AI agent calls `create_customer` to set up the profile, then executes `create_payin` to generate virtual account details using `list_payin_methods`.

The Pydantic AI agent calls `get_fx_rate` to fetch real-time conversion rates. The response is validated against a strict schema, allowing the agent to safely compute transfers.

Raw API tokens are managed securely by Vinkius's ephemeral container environment. This ensures your Pydantic AI runtime never handles raw credentials, keeping customer profiles and payout records isolated from exposure.

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