How to Use the MakePlans MCP in Pydantic AI

Get type-safe, validated scheduling in Pydantic AI with the MakePlans MCP Server integration.

See Vinkius in Action

Works with every AI agent you already use

…and any MCP-compatible client

MCP Servers - Free for Subscribers

Connect MakePlans MCP to Pydantic AI

Create your Vinkius account to connect MakePlans 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.

GDPR Free for Subscribers

Setup MakePlans with Pydantic AI

Ask AI about this MCP

ChatGPT

Claude

Perplexity

Strictly Validated Booking

Your agent uses `create_booking` with strict type enforcement. If the API returns a malformed response, your agent catches it immediately via Pydantic models. This prevents bad data from entering your scheduling system. You get runtime validation for every single interaction.

Precise Slot Retrieval

Query `list_available_slots` and define the expected return schema. The framework verifies the structure of the time slots before your agent attempts to book one. This eliminates silent failures. If the data doesn't match your schema, the agent flags the error instantly.

Service and Resource Integrity

Fetch details using `get_service` and `get_resource` with full type safety. The framework ensures that the resource fields are exactly as your business logic expects. You avoid common bugs related to unexpected nulls or missing fields. The agent acts only on verified data.

Setup guide

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

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

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

Get your connection token →

Independent Platform Disclaimer: Vinkius is an independent platform and is not affiliated with, endorsed by, sponsored by, verified by, or otherwise authorized by MakePlans. 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.

Why Choose Vinkius

Vinkius connects your tools to AI with real-time monitoring and automatic cost savings — all from one dashboard.

Connect MakePlans now

Real-time monitoring

Live

visibility into every interaction

Connect your favorite tools to your AI and see exactly what's happening — every request, every response, in real time.

Built-in savings

60%

lower AI costs

Vinkius compresses data between your apps and your AI automatically. Lower bills every month — no configuration required.

Single dashboard

One

place for every integration

Every tool your AI connects to, managed from a single screen. One account, complete control.

Common questions about MakePlans MCP in Pydantic AI

You get total confidence in your agent's actions. Every tool output is validated against your models, preventing corrupted data from breaking your workflow.

Yes, if the API returns an error or unexpected data, the framework throws a validation error. You can catch this and retry or alert the user.

Not at all. You use the unified MCPToolset, which is designed for clean, type-safe integration with your existing agents.

Absolutely. You can map the tool outputs to your own Pydantic models to ensure the data fits your specific domain requirements.

Your data remains private. The framework only validates the structure of the JSON received; it does not log or store any sensitive scheduling information.

Use it with your favorite AI tools

Connect this server to Cursor, Claude, VS Code, and more.

OpenAI Agents SDK sdk-python

Google ADK sdk-python

Pydantic AI sdk-python

Vercel AI SDK sdk-typescript