How to Use the Cleveland Museum of Art MCP in OpenAI Agents SDK

Connect the Cleveland Museum of Art to OpenAI Agents SDK for production-grade art research and automated metadata retrieval.

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Connect Cleveland Museum of Art MCP to OpenAI Agents SDK

Create your Vinkius account to connect Cleveland Museum of Art 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 Cleveland Museum of Art with OpenAI Agents SDK

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Claude

Perplexity

Direct access to museum records

Your agent queries the collection instantly using `get_artwork` or `get_creator` by ID. It skips manual browsing by pulling precise details directly from the museum database. This MCP Server handles the handshake so your Python code focuses on logic. You'll get raw records back for every call made to `search_artworks`.

Curate collections with OpenAI Agents SDK

Use `search_may_show_creators` to build datasets for historical analysis of local art movements. Your agent maps these results into your custom workflows without extra boilerplate. Everything stays within your defined guardrails. The system ensures `search_similar_artworks` returns relevant data matches for every query.

Automated exhibition tracking

Pull current exhibition schedules using `get_exhibition` to keep your agent informed on museum happenings. It feeds live data into your agent's context window for accurate reporting. Your code manages the `search_exhibitions` tool to stay updated. This keeps your agent's knowledge of the Cleveland Museum of Art current and reliable.

Setup guide

Set up Cleveland Museum of Art 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 Cleveland Museum of Art tools at runtime.
3

Create your Agent

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

Run the agent

Call Runner.run(agent, prompt) to execute. The agent invokes the appropriate Cleveland Museum of Art 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="Cleveland Museum of Art Agent",
            instructions="You have access to Cleveland Museum of Art 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 Cleveland Museum of Art. 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 Cleveland Museum of Art MCP in OpenAI Agents SDK

Yes. You connect the server via the HTTP transport, and the SDK automatically maps the tools into your agent's available actions.

It does. The tools provide structured JSON, which the agent parses to make decisions or answer user questions about the collection.

The server only touches public Open Access API data. No personal visitor information or private museum records are accessible through these tools.

You can selectively pass tool instances to the Agent constructor. This limits the agent to only the functions you choose to expose.

Your agent will receive an error trace. You should implement standard retry logic in your Python code to handle connection drops.

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