How to Use the Vidyard MCP in OpenAI Agents SDK
Manage Vidyard assets and players using the OpenAI Agents SDK.
Works with every AI agent you already use
…and any MCP-compatible client
Connect Vidyard MCP to OpenAI Agents SDK
Create your Vinkius account to connect Vidyard 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.
Control Vidyard Players with the MCP Server
You can list every video player container configured in your account by calling `list_video_players`. This lets you see all the facades currently active. You also have a simple way to update how they appear using `update_player_name`.
Get Detailed Info on Video Assets
Need specs on a video? Use `get_video_details` to pull technical metadata for any asset. If you need the actual stream links, `get_video_source_files` fetches direct URLs for various qualities like 480p and 720p. These functions are crucial when your agent needs to verify if a video is ready for embedding before continuing its workflow.
Managing Video Player Lifecycle
Build out players from scratch using `create_empty_player`. After that, you can pull all the necessary player information with `get_player_details`. If a player is retired, `delete_video_player` handles its permanent removal. Remember, this MCP Server lets your agent handle both creation and cleanup of these containers.
Set up Vidyard 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 Vidyard tools at runtime. - 3
Create your Agent
Pass the MCP to
Agent(mcp_servers=[server]). The agent receives Vidyard tools as native definitions — JSON schemas resolve automatically. - 4
Run the agent
Call
Runner.run(agent, prompt)to execute. The agent invokes the appropriate Vidyard 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="Vidyard Agent",
instructions="You have access to Vidyard 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 Vidyard. 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 Vidyard MCP in OpenAI Agents SDK
Use it with your favorite AI tools
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