How to Use the zipperHQ MCP in OpenAI Agents SDK
Manage video communications and contacts using your OpenAI Agents SDK.
Works with every AI agent you already use
…and any MCP-compatible client
Connect zipperHQ MCP to OpenAI Agents SDK
Create your Vinkius account to connect zipperHQ 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.
Video Analytics and Performance
The `get_video_analytics` tool pulls hard data on specific videos. You can check metrics like view counts or engagement rates for any video you specify. Need to see what's new? Run `get_recent_videos` to pull the ten most recent uploads and get a quick sense of your content flow.
Contact Management
List all recipients using `list_contacts`. This gives your agent a full roster of every person you've messaged. It's better than guessing who was on the call. If you need to know how many times someone viewed a video, just invoke `get_contact_views` and specify the contact.
Video Search and Retrieval
Don't want to scroll forever? The agent runs `search_videos`, letting you find specific videos using keywords. It’s fast, too. You can also grab general details on a single piece of content by calling `get_video` with the unique ID.
Set up zipperHQ 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 zipperHQ tools at runtime. - 3
Create your Agent
Pass the MCP to
Agent(mcp_servers=[server]). The agent receives zipperHQ tools as native definitions — JSON schemas resolve automatically. - 4
Run the agent
Call
Runner.run(agent, prompt)to execute. The agent invokes the appropriate zipperHQ 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="zipperHQ Agent",
instructions="You have access to zipperHQ 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 zipperHQ. 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 zipperHQ MCP in OpenAI Agents SDK
Use it with your favorite AI tools
Connect this server to Cursor, Claude, VS Code, and more.
Start using the zipperHQ MCP today
We host it, we monitor it, we maintain it. You just paste one token.
