How to Use the YouTube MCP in OpenAI Agents SDK

Q: How do I use YouTube analytics with OpenAI Agents SDK?

Your agent runs getchannel to pull stats, then passes that data to a specialized module. Since you're using the OpenAI Agents SDK, every action is traced in the dashboard so you know exactly when and why it ran.

Q: Can I search for YouTube videos with OpenAI Agents SDK?

Yeah, use searchvideos. It returns a clean list of titles and descriptions. You can then hand off those video IDs to another agent that runs the specific analytics on each one.

Q: What happens if I need comment data with OpenAI Agents SDK?

You use listcomments after fetching a video ID. The tool pulls recent or relevant comment threads, giving your agent context about community sentiment around that piece of content.

Q: Does the MCP Server support YouTube data types with OpenAI Agents SDK?

It handles core YouTube metadata like channel stats (getchannel), video details (getvideo), and comment threads. This covers most standard auditing needs you'll run in production.

Build production YouTube analytics agents using the OpenAI Agents SDK.

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Connect YouTube MCP to OpenAI Agents SDK

Create your Vinkius account to connect YouTube 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.

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Setup YouTube with OpenAI Agents SDK

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Audit Channel Performance

The `get_channel` tool pulls complete statistics and branding details for any specified YouTube channel. You get a full performance snapshot, letting you audit how channels are performing right out of the gate. This is critical when building production agents; you need to know if the data source itself is reliable before running complex analysis workflows.

Search for Video Content

Need a list of videos? Use `search_videos` to pull metadata, including titles and descriptions, based on keywords or an exact phrase. It's a simple way to map out the content landscape. The results let your agent quickly identify relevant video targets that need deeper statistical analysis later in your workflow.

Deep Dive Video Statistics

The `get_video` tool fetches all metadata, description details, and full statistics for a single YouTube video. You get granular data points you can't find anywhere else. If an agent needs to analyze one specific piece of content—say, tracking watch time or views—this is the definitive source it uses.

Setup guide

Set up YouTube 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 YouTube tools at runtime.
3

Create your Agent

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

Run the agent

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

asyncio.run(main())

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Common questions about YouTube MCP in OpenAI Agents SDK

Your agent runs `get_channel` to pull stats, then passes that data to a specialized module. Since you're using the OpenAI Agents SDK, every action is traced in the dashboard so you know exactly when and why it ran.

Yeah, use `search_videos`. It returns a clean list of titles and descriptions. You can then hand off those video IDs to another agent that runs the specific analytics on each one.

You use `list_comments` after fetching a video ID. The tool pulls recent or relevant comment threads, giving your agent context about community sentiment around that piece of content.

It handles core YouTube metadata like channel stats (`get_channel`), video details (`get_video`), and comment threads. This covers most standard auditing needs you'll run in production.

This server touches public YouTube metadata, including channel statistics, video titles/descriptions, and user-generated comment content.

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