How to Use the Bizzabo MCP in Pydantic AI

Q: How do I add Bizzabo to Pydantic AI?

Install the pydantic-ai-slimmcp package and initialize the MCPToolset with your server URL. It integrates directly into your agent's toolsets list.

Enforce strict types on Bizzabo event data using Pydantic AI for error-free agent logic.

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Connect Bizzabo MCP to Pydantic AI

Create your Vinkius account to connect Bizzabo 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 Bizzabo with Pydantic AI

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Validate Bizzabo data with Pydantic AI

Every call to `get_event` or `list_sessions` is validated against your schema. If Bizzabo sends bad data, your agent catches it before it breaks the logic. This gives you total control over the data structure. You know exactly what the agent is working with at every step.

Fetch contact records in Pydantic AI

Use `get_contact` to verify attendee details with type-safe precision. Your agent will crash gracefully if the data doesn't match your expected model. It's the safest way to build event automation. You eliminate hallucinated fields by enforcing schema rules on the MCP response.

Automate registration lists via Pydantic AI

Run `list_registrations` to pull attendee lists into your type-safe agent environment. The framework validates every entry against your Python models. Your code becomes much more predictable. You stop guessing if the Bizzabo API returned the right fields and start relying on your runtime checks.

Setup guide

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

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

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

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Common questions about Bizzabo MCP in Pydantic AI

Install the pydantic-ai-slim[mcp] package and initialize the MCPToolset with your server URL. It integrates directly into your agent's toolsets list.

It ensures that every piece of data from the MCP server matches your defined models. You get runtime validation that prevents silent failures in your agent.

Yes, the MCPToolset handles both Streamable HTTP and SSE transports. You just need to ensure the server is running and reachable from your environment.

Yes, you define the schema for event and session objects. The framework handles the parsing and validation for you automatically.

By forcing every piece of contact data through a rigid validation schema, you ensure no malformed data enters your agent's state. Only validated fields survive the check.

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