How to Use the EX.CO Video Experience MCP in OpenAI Agents SDK

Q: How do I configure the EX.CO Video Experience MCP Server with OpenAI Agents SDK?

You initialize the connection using MCPServerStreamableHttp with your Vinkius endpoint. Pass the server instance directly into the Agent constructor to auto-discover all ten tools. This setup eliminates manual endpoint mapping in your Python code.

Q: Can OpenAI Agents SDK run getvideoanalyticssummary automatically on EX.CO Video Experience?

Yes, your agent calls getvideoanalyticssummary natively once the MCP Server is registered. It parses the performance metrics to generate automated reports. You can set execution guardrails to control how often the agent pulls this data.

Q: What is the best way to list live videos using EX.CO Video Experience and OpenAI Agents SDK?

Use listsuccessfullypublishedvideos to let your agent query current assets. The OpenAI Agents SDK automatically validates the output schema against your agent's tool definitions. This ensures your code only processes active, fully rendered video files.

Give your OpenAI Agents SDK production system direct access to your EX.CO video assets and analytics with zero manual API wiring.

See Vinkius in Action

Works with every AI agent you already use

…and any MCP-compatible client

MCP Servers - Free for Subscribers

Connect EX.CO Video Experience MCP to OpenAI Agents SDK

Create your Vinkius account to connect EX.CO Video Experience 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.

GDPR Free for Subscribers

Setup EX.CO Video Experience with OpenAI Agents SDK

Ask AI about this MCP

ChatGPT

Claude

Perplexity

Run video health audits inside OpenAI Agents SDK

`quick_video_performance_audit` pulls performance metrics directly into your OpenAI Agents SDK runtime. Your agent reads raw data like play rates and completion percentages to flag drop-offs without waiting for manual exports. This setup uses OpenAI's built-in guardrails to validate the returned JSON payload against your active schemas. You get clean, structured data that triggers automated alerts when a video dips below your target retention threshold.

Map distribution channels and playlists

`list_video_distribution_channels` exposes active syndication endpoints to your AI client. The agent reads where your videos are running and cross-references them with `list_video_playlists` to find gaps in your distribution strategy. By running this through an MCP Server, you bypass manual spreadsheet updates. Empty playlists are identified automatically, allowing the agent to map out new distribution paths using live API data.

Extract granular video metadata

`get_video_detailed_data` retrieves the exact configuration of any asset in your library. The agent inspects publishing states using `list_successfully_published_videos` to ensure only live assets are sent to your distribution pipelines. Your production system uses these tools to automate content hygiene checks. It matches metadata with `get_content_detailed_intelligence` to flag incorrect tags or missing descriptions before they hit your production players.

Setup guide

Set up EX.CO Video Experience 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 EX.CO Video Experience tools at runtime.
3

Create your Agent

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

Run the agent

Call Runner.run(agent, prompt) to execute. The agent invokes the appropriate EX.CO Video Experience 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="EX.CO Video Experience Agent",
            instructions="You have access to EX.CO Video Experience tools.",
            mcp_servers=[server],
        )
        result = await Runner.run(agent, "List recent transactions")
        print(result.final_output)

asyncio.run(main())

Get your connection token →

Independent Platform Disclaimer: Vinkius is an independent platform and is not affiliated with, endorsed by, sponsored by, verified by, or otherwise authorized by EX.CO Video Experience. 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.

Connect EX.CO Video Experience now

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 EX.CO Video Experience MCP in OpenAI Agents SDK

You initialize the connection using `MCPServerStreamableHttp` with your Vinkius endpoint. Pass the server instance directly into the `Agent` constructor to auto-discover all ten tools. This setup eliminates manual endpoint mapping in your Python code.

Yes, your agent calls `get_video_analytics_summary` natively once the MCP Server is registered. It parses the performance metrics to generate automated reports. You can set execution guardrails to control how often the agent pulls this data.

Use `list_successfully_published_videos` to let your agent query current assets. The OpenAI Agents SDK automatically validates the output schema against your agent's tool definitions. This ensures your code only processes active, fully rendered video files.

The SDK auto-discovers all ten EX.CO tools when you pass the MCP server parameter. You set `cacheToolsList=True` to keep performance high and avoid redundant schema lookups.

All video analytics and player metadata remain inside the V8 isolate sandbox. Vinkius processes these credentials ephemerally, meaning your EX.CO API keys are never stored on disk. Your raw engagement data is transmitted over TLS directly to your runtime.

Use it with your favorite AI tools

Connect this server to Cursor, Claude, VS Code, and more.

OpenAI Agents SDK sdk-python

Google ADK sdk-python

Pydantic AI sdk-python

Vercel AI SDK sdk-typescript