How to Use the BoardMix MCP in OpenAI Agents SDK

Build production-grade agents that manipulate your whiteboard files directly within the OpenAI Agents SDK.

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Connect BoardMix MCP to OpenAI Agents SDK

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

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Manage your whiteboard structure with OpenAI Agents SDK

Your agent handles whiteboard creation and organization mapping through the `create_file` and `list_teams` tools. You define the logic, and the server executes the file generation immediately. Automate your visual workflows by chaining `list_files` into your agent’s execution loop. This MCP server lets your code interact with specific whiteboard objects without manual intervention.

Trace every whiteboard change via OpenAI Agents SDK

Audit your collaborative history using `get_file_versions` to pull specific iteration data into your agent’s trace. This gives you a clear path to verify who modified which node. Keep your agent informed by calling `get_comments` to ingest feedback loops directly. It turns passive whiteboard discussions into actionable data points for your agent to process.

Inject template logic using OpenAI Agents SDK

Feed your agent a starting point by invoking `list_templates` to find standard layouts. You load these into your process to standardize how your agent builds new boards. Use `list_nodes` to inspect the contents of any existing board. Your agent parses these node structures to understand complex diagrams before making any updates.

Setup guide

Set up BoardMix 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 BoardMix tools at runtime.
3

Create your Agent

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

Run the agent

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

You instantiate an MCPServerStreamableHttp object using your Vinkius endpoint. Pass this object into your Agent constructor to let the SDK handle tool discovery automatically.

Yes, the tools are fully compatible with your agent's execution cycle. You simply define the server connection, and the SDK maps the tools to your agent's available actions.

It runs reliably on the Vinkius infrastructure. Because the server supports async context managers, it fits perfectly into the production-ready patterns required by the SDK.

You can filter the tool list before passing the server to your agent. This ensures your agent only interacts with the specific endpoints you authorize.

Your whiteboard data, including file structures and comment history, stays within your control. Vinkius manages the transport, and the server only touches the specific metadata required to execute your requested whiteboard actions.

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