How to Use the Brivo MCP in OpenAI Agents SDK
Direct control over Brivo security nodes from your OpenAI Agents SDK production environment.
Works with every AI agent you already use
…and any MCP-compatible client
Connect Brivo MCP to OpenAI Agents SDK
Create your Vinkius account to connect Brivo 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.
Automate door state with OpenAI Agents SDK
Your agent checks physical security status by calling `get_door_status` to see if a portal is locked. If the system flags an issue, you can trigger `unlock_door` to grant immediate entry. This setup keeps your logic inside the Python agent flow. You avoid manual dashboard logins and handle access requests through code.
Audit access logs in OpenAI Agents SDK
Pull raw security history using `list_access_events` to monitor who entered and when. The SDK captures these outputs for your tracing dashboard. Parsing these logs allows your agent to flag suspicious patterns. You maintain a clear record of every credential use without leaving your development environment.
Manage user permissions via OpenAI Agents SDK
Query your entire roster using `list_users` or look up specific individual details with `get_user`. This simplifies identity management for your security team. Updating access groups becomes a programmatic task rather than a manual chore. You can verify `list_access_groups` and ensure the right people have the right keys.
Set up Brivo 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 Brivo tools at runtime. - 3
Create your Agent
Pass the MCP to
Agent(mcp_servers=[server]). The agent receives Brivo tools as native definitions — JSON schemas resolve automatically. - 4
Run the agent
Call
Runner.run(agent, prompt)to execute. The agent invokes the appropriate Brivo 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="Brivo Agent",
instructions="You have access to Brivo 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 Brivo. 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.
Why Choose Vinkius
Vinkius connects your tools to AI with real-time monitoring and automatic cost savings — all from one dashboard.
Real-time monitoring
Live
visibility into every interaction
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
Vinkius compresses data between your apps and your AI automatically. Lower bills every month — no configuration required.
Single dashboard
One
place for every integration
Every tool your AI connects to, managed from a single screen. One account, complete control.
Common questions about Brivo MCP in OpenAI Agents SDK
Use it with your favorite AI tools
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