How to Use the Guidebook MCP in Pydantic AI

Type-safe event management for Pydantic AI agents using Guidebook tools.

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Connect Guidebook MCP to Pydantic AI

Create your Vinkius account to connect Guidebook 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 Guidebook with Pydantic AI

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Pydantic AI runtime validation

Every response from the Guidebook tools is checked against Pydantic models. If `get_event` returns a malformed schedule, your agent throws a validation error immediately. This stops bad data from propagating through your pipeline. You get predictable behavior every time the agent interacts with your event guide.

Manage custom items with Pydantic AI

Use `list_custom_lists` to define the schema for your event content. Pydantic AI ensures your agent only creates items that match your defined structure. This prevents the common issue of hallucinated fields when updating your mobile app. Your data remains clean and consistent.

Structured session updates

Trigger `update_guide` with strictly typed payloads. Your agent validates the input before the MCP Server sends it to the API, ensuring you never push broken schedules. It’s the safest way to automate your event updates. You can trust that the data moving to the mobile app is exactly what your models expect.

Setup guide

Set up Guidebook 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": {
        "guidebook-alternative-mcp": {
            "url": "https://edge.vinkius.com/[YOUR_TOKEN_HERE]/mcp"
        }
    }
})

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

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

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Common questions about Guidebook MCP in Pydantic AI

Install the slim package, then use the MCPToolset class to connect your server. Pass the toolset into your agent to enable type-safe tool execution.

Yes, the framework validates every tool output against your schemas. If the API returns unexpected data, the agent halts, preventing silent corruption.

Since Pydantic AI is model-agnostic, you can swap between local models and hosted LLMs. The MCP Server functions the same regardless of which model you choose.

Use standard Python try-except blocks around your agent calls. The server will surface connectivity issues as clear exceptions that you can catch and log.

The server uses isolated, ephemeral execution. Your attendee lists and event metadata are never stored by the server, ensuring your data remains private and secure.

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