How to Use the CoinGate MCP in Pydantic AI

Q: Can Pydantic AI validate the output of getaccountinfo?

Yes. The getaccountinfo tool output is validated against runtime schemas, ensuring your agent reads merchant profile details without risk of silent data corruption.

Build type-safe crypto payment workflows with Pydantic AI and strict runtime validation.

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Connect CoinGate MCP to Pydantic AI

Create your Vinkius account to connect CoinGate 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 CoinGate with Pydantic AI

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Type-Safe Order Creation with Pydantic AI

The `create_order` tool uses Pydantic AI to enforce strict type checking on every payment request before it leaves your application. If your agent attempts to pass an invalid currency code or a malformed price string, the framework rejects it instantly. This runtime validation prevents silent failures and API errors. Your agent operates with absolute certainty that every outbound payload conforms exactly to the schema.

Validated Financial Audits via CoinGate MCP Server

The `list_orders` tool returns transaction histories that are parsed directly into typed Python models. Using this CoinGate MCP Server connection ensures that your agent never processes corrupt or hallucinated payment records. If the API response structure changes, your application raises a validation error immediately. This loud-failure design protects your accounting pipelines from dirty data.

Strict Exchange Rate Calculations

The `get_exchange_rates` tool feeds live price feeds into your agent's decision-making loop. The framework checks the incoming rate data against strict numerical schemas to ensure calculations remain precise. Your agent uses these validated rates to verify pricing on active checkouts. It guarantees that conversion math is always backed by real-time, typed data.

Setup guide

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

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

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

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Common questions about CoinGate MCP in Pydantic AI

Use the MCPToolset class with your Vinkius HTTP URL and pass it to your Agent's toolsets parameter. The framework automatically registers the payment tools.

Yes. The framework supports both Streamable HTTP and SSE transports, allowing your agent to read live endpoints like `get_order` with minimal latency.

Your agent will fail loudly with a validation error rather than proceeding with corrupt data. This is critical for keeping financial records clean.

Yes. The `get_account_info` tool output is validated against runtime schemas, ensuring your agent reads merchant profile details without risk of silent data corruption.

Your CoinGate transaction records and account balances are processed in memory and validated locally. Vinkius secures the MCP transport layer with a single token, keeping your payout logs isolated from unauthorized actors while Pydantic AI enforces type safety.

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