How to Use the Buenbit MCP in OpenAI Agents SDK

Connect your OpenAI Agents SDK to Buenbit and execute crypto trades automatically through your agent's decision loop.

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Connect Buenbit MCP to OpenAI Agents SDK

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

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Trade execution for OpenAI Agents SDK

Trigger `create_order` or `cancel_order` directly from your Python agent logic. The server handles the handshake, letting your agent focus on the trade signals rather than API boilerplate. Your agent inspects the market via `get_ticker` and decides whether to commit capital. Safety is baked in because the agent uses the provided schema to validate parameters before hitting the exchange.

Portfolio monitoring with MCP Server

Call `list_balances` to keep your agent updated on current holdings. This keeps your state machine in sync with actual wallet values without manual polling. Every transaction history is accessible via `list_transactions`. Your agent can audit performance or log events to the OpenAI dashboard for full visibility.

Real-time market analysis

Fetch current rates with `get_crypto_prices` to feed your decision models. The data flows straight into your context window for immediate calculation. Check `get_yield_rates` to see where your assets earn interest. Your agent can compare these rates against current market volatility to suggest rebalancing strategies.

Setup guide

Set up Buenbit 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 Buenbit tools at runtime.
3

Create your Agent

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

Run the agent

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

You instantiate an MCPServerStreamableHttp object pointing to your Vinkius endpoint. Pass this to your Agent constructor's mcp_servers list and the SDK handles tool discovery automatically.

Yes. Since the agent executes these tools within its own loop, you can catch exceptions from failed trades or network timeouts. It treats the server response as part of its standard reasoning cycle.

Vinkius manages authentication through a single endpoint token. Your agent only sees the tool outputs, keeping your private exchange credentials siloed within the secure transport layer.

The server runs in a managed sandbox environment. It remains isolated, ensuring consistent performance for your agent's requests.

All traffic is encrypted in transit and the server environment is ephemeral. We never log your wallet balances or transaction history, ensuring your financial data stays private.

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