How to Use the Tock Reservations MCP in Pydantic AI

Q: Can I check business metrics using Tock Reservations and Pydantic AI?

Yes. You can use getbusinessperformancemetrics. The framework ensures that the resulting performance data—like total bookings or average spend—adheres strictly to your defined Python models.

Q: What if I need guest list details using Tock Reservations and Pydantic AI?

The listbusinessguests tool provides the raw data, which Pydantic then validates. You won't have to worry about missing or badly formatted fields in your resulting guest roster.

Process Tock reservations with guaranteed type safety using Pydantic AI.

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Connect Tock Reservations MCP to Pydantic AI

Create your Vinkius account to connect Tock Reservations 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 Tock Reservations with Pydantic AI

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Get full reservation content.

The `get_reservation_details` tool fetches the complete status and contents for a specific booking. Because you're using Pydantic, you get immediate validation on every field returned. If the API sends an unexpected structure, your agent fails with a clear error—no silent data corruption.

View business settings.

Use `get_business_detailed_data` to retrieve all detailed operational settings for any venue. Pydantic ensures that the returned parameters like address or hours are exactly what you expect them to be. This level of type checking means your agent can trust the input data before using it in a complex workflow.

List special events.

Call `list_business_special_events` to see upcoming pop-ups or themed days. The Pydantic validation guarantees that each event object includes required fields like start date and end date. This is essential for building reliable marketing or capacity planning agents.

Setup guide

Set up Tock Reservations 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": {
        "tock-reservations-mcp": {
            "url": "https://edge.vinkius.com/[YOUR_TOKEN_HERE]/mcp"
        }
    }
})

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

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

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Independent Platform Disclaimer: Vinkius is an independent platform and is not affiliated with, endorsed by, sponsored by, verified by, or otherwise authorized by Tock Reservations. All third-party trademarks, logos, and brand names are the property of their respective owners. Their use on this website is strictly for informational purposes to identify service compatibility and interoperability.

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Common questions about Tock Reservations MCP in Pydantic AI

The MCP Server provides raw data, but Pydantic AI validates it. This means every time your agent calls a tool like `get_reservation_details`, you get a guaranteed, correctly typed Python object back.

Yes. You can use `get_business_performance_metrics`. The framework ensures that the resulting performance data—like total bookings or average spend—adheres strictly to your defined Python models.

The `list_business_guests` tool provides the raw data, which Pydantic then validates. You won't have to worry about missing or badly formatted fields in your resulting guest roster.

The server touches reservation details, business configuration settings, event schedules, and performance metrics. The core benefit of this setup is the validated structure across all these domains.

It's extremely safe for development purposes because validation prevents bad data from corrupting your agent logic. You know exactly what fields you are working with, which is key when handling sensitive reservation records.

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