How to Use the Hub Planner MCP in OpenAI Agents SDK

Plug the Hub Planner MCP Server into your OpenAI Agents SDK to manage resource capacity and project timelines from your Python code.

See Vinkius in Action

Works with every AI agent you already use

…and any MCP-compatible client

MCP Servers - Free for Subscribers

Connect Hub Planner MCP to OpenAI Agents SDK

Create your Vinkius account to connect Hub Planner 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.

GDPR Free for Subscribers

Setup Hub Planner with OpenAI Agents SDK

Ask AI about this MCP

ChatGPT

Claude

Perplexity

Real-time resource and project tracking

Your agent pulls live data directly from your account. Use `list_resources` and `list_projects` to keep your internal status updated without manual refreshes. Everything stays in sync. The agent triggers these tools to verify project availability before it commits to any new schedule.

Automated booking and team management

Stop digging through dashboards to find who is available. Your agent calls `list_bookings` and `list_teams` to identify gaps in your current production plan. It handles the heavy lifting. The agent parses the response to flag conflicts instantly, ensuring your project planning remains accurate.

Client and event data integration

Connect your client records to your planning workflow. The agent uses `list_clients` and `list_events` to cross-reference billing status with upcoming time-off requests. This keeps your team informed. Your agent detects potential bottlenecks by comparing active events against project milestones.

Setup guide

Set up Hub Planner 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 Hub Planner tools at runtime.
3

Create your Agent

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

Run the agent

Call Runner.run(agent, prompt) to execute. The agent invokes the appropriate Hub Planner 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="Hub Planner Agent",
            instructions="You have access to Hub Planner tools.",
            mcp_servers=[server],
        )
        result = await Runner.run(agent, "List recent transactions")
        print(result.final_output)

asyncio.run(main())

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 Hub Planner. 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 Hub Planner 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 Hub Planner MCP in OpenAI Agents SDK

You initialize the connection using the MCPServerStreamableHttp class. Pass your endpoint URL to the constructor and register it as an mcp_server within your agent setup.

Yes, but keep your rate limits in mind. Enable cacheToolsList in your configuration to reduce unnecessary overhead during agent execution.

This server focuses on read-only access to your records. You can query everything from `list_bookings` to `list_categories` to inform your agent's decision-making.

The MCP server will return a connection error to your agent. Implement standard try-except blocks in your Python code to handle these network interruptions.

The server only transmits the specific resource and project data requested by your agent. All traffic remains encrypted, and no raw credentials are stored within the agent runtime itself.

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