How to Use the CurrencyBeacon MCP in Pydantic AI

Q: How do I connect CurrencyBeacon to Pydantic AI?

Install pydantic-ai-slimmcp. Initialize an MCPToolset with your Vinkius HTTP URL, then pass it to the toolsets argument when building your Agent.

Q: Should I use MCPServerHTTP for the connection?

No, that class is deprecated. You must use the unified MCPToolset with your endpoint URL to enable Streamable HTTP or SSE transports.

Bring strict type safety to foreign exchange rates in your Pydantic AI applications.

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Connect CurrencyBeacon MCP to Pydantic AI

Create your Vinkius account to connect CurrencyBeacon 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 CurrencyBeacon with Pydantic AI

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Claude

Perplexity

Validate live market data

The `get_latest_rates` tool pulls current exchange numbers and forces them through Pydantic AI's strict runtime validation. If the upstream API returns a string instead of a float for a currency value, your agent fails loudly rather than silently corrupting your database. This model-agnostic approach means you get the exact same typed guarantees whether you use OpenAI, Anthropic, or a local model to drive the agent. The framework ensures the incoming rate data strictly matches your expected Python models.

Process historical conversions safely

The `convert_currency` and `get_historical_rates` tools fetch exact valuations for specific past dates. Your agent requests a conversion, and Pydantic AI verifies the response structure before your application writes the finalized local currency value to your ledger. You never have to worry about hallucinated JSON fields. The agent simply cannot proceed if the historical rate payload deviates from the expected schema defined in your application logic.

Fetch typed time-series with this MCP Server

The `get_timeseries` tool retrieves up to 365 days of daily exchange rates. Building financial charts requires exact data, and Pydantic AI guarantees every single day in that massive array contains a valid date string and a numeric rate. Agents can also call `list_currencies` to validate supported symbols before requesting a full year of data. You connect this by passing the Vinkius endpoint to `MCPToolset` and adding it to your `Agent` toolsets.

Setup guide

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

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

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

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Common questions about CurrencyBeacon MCP in Pydantic AI

Install `pydantic-ai-slim[mcp]`. Initialize an `MCPToolset` with your Vinkius HTTP URL, then pass it to the `toolsets` argument when building your Agent.

Yes, every exchange rate and conversion result is validated against Pydantic models at runtime. Any malformed data triggers an immediate validation error.

The framework is completely model-agnostic. You can pull historical rates using local models, Gemini, or Claude, and the type-checking remains identical.

No, that class is deprecated. You must use the unified `MCPToolset` with your endpoint URL to enable Streamable HTTP or SSE transports.

Your requested dates, amounts, and fiat symbols are processed in an isolated, zero-trust V8 environment. Vinkius provisions the container for the exact duration of your Pydantic AI request and destroys it immediately afterward.

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