How to Use the GeekJoke MCP in Pydantic AI

Q: How do I add GeekJoke to my Pydantic AI agent?

First, pip install "pydantic-ai-slimmcp". Then create an MCPToolset with the MCP server URL and include it in the toolsets list when you initialize your Agent. The tools are then ready to be called.

Q: What happens if the GeekJoke API changes its response format?

Your Pydantic AI agent will raise a ValidationError. Because every tool output is validated against a model, you're protected from unexpected API changes that could cause silent bugs.

Q: Is the GeekJoke MCP server a good fit for Pydantic AI?

Yes, it's a perfect example. The tools (getrandomjoke, getmetadata) have simple, predictable outputs that are easy to model with Pydantic, giving you the full benefit of runtime type safety.

Q: How does Pydantic AI handle the two joke tools from GeekJoke?

Pydantic AI exposes both getrandomjoke and generaterandomjoke if they are on the server. You can choose which one to call from your agent's logic, and both of their outputs will be validated.

Get jokes you can trust. GeekJoke and Pydantic AI deliver structurally validated humor, so your agent never breaks on a bad response.

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Connect GeekJoke MCP to Pydantic AI

Create your Vinkius account to connect GeekJoke 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 GeekJoke with Pydantic AI

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Get Type-Safe Jokes

When your agent calls `get_random_joke`, Pydantic AI automatically validates the response. You expect a string, and if the server ever returns anything else, your code will raise a `ValidationError` instantly. This means no silent failures. Your agent either gets a clean joke or you know exactly why it failed. It's reliability you don't have to code yourself.

Validate Server Metadata at Runtime

The `get_metadata` tool returns a JSON object with server information. With Pydantic AI, you can define a Pydantic model that matches this structure. Now, every time your agent calls `get_metadata`, the response is parsed into your model. If the MCP server API ever adds or removes a field, your agent will fail loudly instead of using incomplete data.

Use Any LLM You Want

Pydantic AI doesn't lock you into a specific model provider. You can use the GeekJoke toolset with an agent powered by OpenAI, Anthropic, Gemini, or a local model. The tool integration is separate from the LLM logic. As long as your agent uses the `MCPToolset`, it can call `get_random_joke` regardless of which brain is driving it.

Setup guide

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

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

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

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Common questions about GeekJoke MCP in Pydantic AI

First, `pip install "pydantic-ai-slim[mcp]"`. Then create an `MCPToolset` with the MCP server URL and include it in the `toolsets` list when you initialize your `Agent`. The tools are then ready to be called.

Your Pydantic AI agent will raise a `ValidationError`. Because every tool output is validated against a model, you're protected from unexpected API changes that could cause silent bugs.

Yes, it's a perfect example. The tools (`get_random_joke`, `get_metadata`) have simple, predictable outputs that are easy to model with Pydantic, giving you the full benefit of runtime type safety.

Pydantic AI exposes both `get_random_joke` and `generate_random_joke` if they are on the server. You can choose which one to call from your agent's logic, and both of their outputs will be validated.

No data is stored. The server is designed to be stateless. It receives a request for a joke, returns a joke string, and logs nothing about the caller. The process is ephemeral and secured by your Vinkius auth token.

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