How to Use the BookingLive MCP in Pydantic AI

Q: Can I use Pydantic AI to filter BookingLive orders by email?

Yes, use the getordersbyemail tool. The agent returns the records as typed objects, making it simple to process customer history in your application.

Type-safe BookingLive operations for your Pydantic AI agent workflows.

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Connect BookingLive MCP to Pydantic AI

Create your Vinkius account to connect BookingLive 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 BookingLive with Pydantic AI

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Perplexity

Rigorous type validation for BookingLive in Pydantic AI

Every response from the server is checked against your Pydantic schemas. If the API returns a malformed `get_order_details` response, your agent catches it immediately. This prevents silent failures during booking. Your agent only acts on confirmed, valid data structures, keeping your order flow predictable and stable.

Manage BookingLive order state with Pydantic AI

Your agent maintains a strict state machine for every booking. It uses `start_order` to initiate a session, ensuring all required member details are present before moving forward. Validation errors show up before the API call even finishes. This keeps your BookingLive integration clean and prevents invalid data from hitting your production database.

Query BookingLive with Pydantic AI type safety

Search your catalog with confidence. When your agent calls `get_ref_data`, the results are parsed into your defined models for immediate use in your logic. You avoid the common pitfalls of dynamic typing. If the product data format changes, your agent fails loud and clear, allowing you to update your schema before errors propagate.

Setup guide

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

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

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

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Common questions about BookingLive MCP in Pydantic AI

Every MCP response is validated against your Pydantic models at runtime. This forces the agent to handle schema discrepancies before they impact your business logic.

It provides a full suite of tools to manage the order lifecycle. Your agent can read, create, and update bookings while maintaining strict type safety.

We isolate all server traffic and use encrypted tokens for every session. Your data stays private because our architecture never logs your specific API queries.

Yes, use the `get_orders_by_email` tool. The agent returns the records as typed objects, making it simple to process customer history in your application.

We treat customer email records as restricted, short-lived data. The server uses ephemeral transport protocols to ensure that no contact information persists after the agent task completes.

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