How to Use the Bored MCP in OpenAI Agents SDK

Q: Why does my OpenAI Agents SDK call to Bored run so fast?

You probably enabled cacheToolsList=True during initialization. This prevents the SDK from querying the MCP Server schema on every single turn, shaving off precious milliseconds.

Give your OpenAI Agents SDK production workflows instant access to boredom-busting activities with native guardrails.

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Connect Bored MCP to OpenAI Agents SDK

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

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Find Bored activities safely with OpenAI Agents SDK

The `find_activity` tool lets your OpenAI Agents SDK search for curated things to do based on price, participants, and accessibility. Since you are running this in a production environment, the SDK validates the search parameters before letting the tool run. If an agent tries to pass a negative price or a million participants, your built-in guardrails block the call before it hits the network. You get clean, safe activity options without worrying about rogue agent behavior.

Get specific Bored actions using unique keys

The `get_activity_by_key` tool retrieves a highly specific task directly from your agent's execution loop. Your production setup can cache these lookups easily because the Bored MCP server integrates directly with your streamable HTTP server parameters. Setting `cacheToolsList=True` ensures your agent doesn't waste overhead re-fetching the tool definitions. It keeps your latency low while your users get exactly the boredom cure they requested.

Hand off random activity generation to specialized agents

The `get_random_activity` tool serves as a quick fallback when your user has no idea what they want to do. You can set up a routing agent that detects a bored user and hands the conversation over to a dedicated recreational agent. Every single handoff and tool execution shows up in your OpenAI dashboard. This gives you complete tracing of how often your users ask for random suggestions and how the agent responds.

Setup guide

Set up Bored 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 Bored tools at runtime.
3

Create your Agent

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

Run the agent

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

asyncio.run(main())

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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 Bored API. 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 Bored MCP in OpenAI Agents SDK

Install the package and initialize the streamable HTTP class with the Vinkius URL. Pass this server instance in the `mcp_servers` list when instantiating your agent. The SDK handles tool discovery automatically so your agent can instantly find things to do.

Yes, you can control tool access through your agent's guardrails or by wrapping the tools in specialized helper agents. This ensures a routing agent only gets `get_random_activity` while your search agent handles `find_activity`.

You probably enabled `cacheToolsList=True` during initialization. This prevents the SDK from querying the MCP Server schema on every single turn, shaving off precious milliseconds.

The agent receives the response data and processes it according to your system prompt. You can write a guardrail to filter out solo tasks if your user specifically asked for group activities.

This server only processes basic filters like budget, participant counts, and accessibility ratings. No personally identifiable information is ever sent to the Bored endpoint, and Vinkius runs the MCP Server in an ephemeral sandbox that destroys memory states instantly.

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