How to Use the VBOUT MCP in OpenAI Agents SDK
Run campaigns with your AI client, the OpenAI Agents SDK.
Works with every AI agent you already use
…and any MCP-compatible client
Connect VBOUT MCP to OpenAI Agents SDK
Create your Vinkius account to connect VBOUT 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.
Manage contacts and lists
The `search_contacts` tool lets you find people based on criteria. You can also use `get_contact` to pull specific details for a user who's already identified. When you need to expand your reach, the `add_contact` function adds new leads directly to an existing list ID.
Handle e-commerce data
Need to track sales? The `add_ecommerce_order` tool processes and records a full purchase. This means your agent can instantly log order details into the system. Beyond just orders, you can also list all available email marketing lists using `list_email_lists`, keeping track of where everything goes.
Automate outreach and content
The agent can draft social posts right through the `create_social_post` tool. It also lets you trigger specific marketing workflows using `trigger_workflow` for a defined contact. Keep your whole operation organized by listing available campaigns via `list_campaigns`, giving full visibility into current initiatives.
Set up VBOUT MCP in OpenAI Agents SDK
Prerequisites
- Python 3.10+ installed
-
openai-agentspackage (pip install openai-agents) - Active Vinkius subscription with a valid endpoint token
- 1
Install the SDK
Run
pip install openai-agentsto install the OpenAI Agents SDK. The MCP integration is built-in — no extra dependencies needed. - 2
Connect via SSE transport
Use
MCPServerSsewith your Vinkius endpoint URL. Replace[YOUR_TOKEN_HERE]with your token from cloud.vinkius.com. The SDK auto-discovers all VBOUT tools at runtime. - 3
Create your Agent
Pass the MCP to
Agent(mcp_servers=[server]). The agent receives VBOUT tools as native definitions — JSON schemas resolve automatically. - 4
Run the agent
Call
Runner.run(agent, prompt)to execute. The agent invokes the appropriate VBOUT tools and returns structured results. Copy the full example on the right to get started.
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="VBOUT Agent",
instructions="You have access to VBOUT tools.",
mcp_servers=[server],
)
result = await Runner.run(agent, "List recent transactions")
print(result.final_output)
asyncio.run(main()) Independent Platform Disclaimer: Vinkius is an independent platform and is not affiliated with, endorsed by, sponsored by, verified by, or otherwise authorized by VBOUT. 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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Live
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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
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place for every integration
Every tool your AI connects to, managed from a single screen. One account, complete control.
Common questions about VBOUT MCP in OpenAI Agents SDK
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