How to Use the ClubPlanner MCP in Pydantic AI

Q: How do I install the ClubPlanner integration for Pydantic AI?

Install the package using pip install "pydantic-ai-slimmcp" to get the lightweight runtime. Then, initialize MCPToolset with your Vinkius HTTP URL to start calling ClubPlanner gym tools from your Pydantic AI agent.

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Connect ClubPlanner MCP to Pydantic AI

Create your Vinkius account to connect ClubPlanner 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 ClubPlanner with Pydantic AI

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Type-safe member check-ins via Pydantic AI

This MCP Server provides type-safe access to ClubPlanner, letting Pydantic AI validate member check-ins at runtime. Stop bad data from corrupting your ClubPlanner database by using Pydantic AI to validate every single payload from this server. Pydantic AI validates inputs for `create_checkin` and `create_prospect` to ensure they exactly match your expected ClubPlanner schemas. If your Pydantic AI agent tries to register a check-in with a missing member ID, the framework catches the validation error before it hits ClubPlanner.

Strict validation for club contracts and products

This MCP Server exposes ClubPlanner product schemas so Pydantic AI validates contracts before your agent acts on them. When your Pydantic AI agent queries `list_products` or `list_contracts`, the framework parses the raw JSON into strictly typed Python models before your agent acts on ClubPlanner data. This prevents your Pydantic AI agent from hallucinating ClubPlanner pricing structures or misinterpreting contract end dates. You get absolute certainty that the ClubPlanner details validated by Pydantic AI are exactly what is written in your database.

Unified HTTP toolsets for gym scheduling

This MCP Server connects your ClubPlanner schedule to Pydantic AI using a unified HTTP toolset. Build reliable scheduling tools using Pydantic AI's unified `MCPToolset` class to query `list_appointments` and update schedules using `create_appointment` in ClubPlanner. Because the legacy MCPServerHTTP approach is deprecated, this unified Pydantic AI toolset ensures your Python agent remains compatible with future ClubPlanner updates. Your Pydantic AI agent coordinates trainer schedules using `list_staff` without worrying about broken ClubPlanner connections.

Setup guide

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

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

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

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Common questions about ClubPlanner MCP in Pydantic AI

Install the package using `pip install "pydantic-ai-slim[mcp]"` to get the lightweight runtime. Then, initialize `MCPToolset` with your Vinkius HTTP URL to start calling ClubPlanner gym tools from your Pydantic AI agent.

The Pydantic AI framework will fail loudly with a validation error instead of passing bad data to your agent. This ensures ClubPlanner tools like `get_member` or `list_checkins` never cause silent failures in your Pydantic AI application logic.

Yes, Pydantic AI is model-agnostic, letting you run your ClubPlanner management agent on local LLMs. You use this MCP Server to run tools like `create_appointment` to manage your club's calendar while keeping model costs low.

The Pydantic AI framework automatically inspects the ClubPlanner MCP Server's tool definitions and builds runtime validation guards. Your Pydantic AI agent gets a clear, structured understanding of how to use tools like `list_prospects` without manual schema mapping.

The integration processes ClubPlanner membership details, class bookings, and prospect records using Vinkius's zero-trust sandboxed environment. Raw validation data handled by Pydantic AI is processed in memory and never stored on the Vinkius hosting layer, keeping your customer records completely secure.

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