How to Use the MakePlans MCP in OpenAI Agents SDK

Schedule appointments directly inside your OpenAI Agents SDK production pipeline using the MakePlans MCP Server.

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Connect MakePlans MCP to OpenAI Agents SDK

Create your Vinkius account to connect MakePlans to OpenAI Agents SDK 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 MakePlans with OpenAI Agents SDK

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Perplexity

Automated Booking Logic

Your agent handles appointment lifecycle management without custom glue code. Use `create_booking` and `delete_booking` to modify your schedule based on real-time agent reasoning. Built-in guardrails in your SDK validate these actions before they hit the API. You maintain full control over the booking flow while the agent manages the repetitive data entry.

Real-time Resource Discovery

Stop hardcoding availability. Your agent queries `list_available_slots` to find open time windows for specific services. It cross-references these slots against `list_resources` and `list_services` to ensure every appointment aligns with your current operational constraints.

Complete Booking Visibility

Your agent maintains a clear view of your schedule by calling `list_bookings` to fetch current records. It uses `get_booking` to drill down into specific details, ensuring your agent-driven workflows stay synced with the actual state of your MakePlans account.

Setup guide

Set up MakePlans MCP in OpenAI Agents SDK

Prerequisites

Python 3.10+ installed
openai-agents package (pip install openai-agents)
Active Vinkius subscription with a valid endpoint token

1

Install the SDK

Run pip install openai-agents to install the OpenAI Agents SDK. The MCP integration is built-in — no extra dependencies needed.
2

Connect via SSE transport

Use MCPServerSse with your Vinkius endpoint URL. Replace [YOUR_TOKEN_HERE] with your token from cloud.vinkius.com. The SDK auto-discovers all MakePlans tools at runtime.
3

Create your Agent

Pass the MCP to Agent(mcp_servers=[server]). The agent receives MakePlans tools as native definitions — JSON schemas resolve automatically.
4

Run the agent

Call Runner.run(agent, prompt) to execute. The agent invokes the appropriate MakePlans tools and returns structured results. Copy the full example on the right to get started.

agent.py

import asyncio
from agents import Agent, Runner
from agents.mcp import MCPServerSse

async def main():
    async with MCPServerSse(
        url="https://edge.vinkius.com/[YOUR_TOKEN_HERE]/mcp"
    ) as server:
        agent = Agent(
            name="MakePlans Agent",
            instructions="You have access to MakePlans tools.",
            mcp_servers=[server],
        )
        result = await Runner.run(agent, "List recent transactions")
        print(result.final_output)

asyncio.run(main())

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Common questions about MakePlans MCP in OpenAI Agents SDK

The server uses standard environment-based authentication. Your agent client wraps these calls in its own security layer, ensuring every request to an MCP Server is authenticated and traced.

Yes, your agent logic controls the iteration. You define the loop in your agent code, and the server executes each `create_booking` call individually per slot.

Performance depends on your network and the API load. The server is lightweight, but you should cache tool definitions to keep your agent's response time snappy.

You get all 10 tools by default. You can restrict which tools the agent sees by filtering the toolset before passing it to the agent constructor.

The server acts as a pass-through for your scheduling data. No PII is stored on our end; it moves directly between your agent and the API.

Use it with your favorite AI tools

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

OpenAI Agents SDK sdk-python

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