How to Use the YouTube MCP in Google ADK

Q: How do I process YouTube analytics with Google ADK?

You use the getchannel tool first. The resulting statistics are then passed into a Gemini model within your agent for advanced, multi-step reasoning against data stored in BigQuery.

Q: Can I search YouTube videos with Google ADK?

Yes, call searchvideos. It provides the titles and descriptions. You can then filter this list within your agent workflow before running deeper analysis on GCP infrastructure.

Q: What about comment threads using Google ADK?

You use listcomments to get recent or relevant comments for a video. Your agent treats these unstructured text inputs as data points, analyzing sentiment alongside the structured metadata.

Q: Does this MCP Server support YouTube data types with Google ADK?

It handles core public statistics: channel details via getchannel, video metadata via getvideo, and comment threads. This works perfectly for enterprise-level audits.

Build enterprise YouTube intelligence agents using the Google ADK.

See Vinkius in Action

Works with every AI agent you already use

…and any MCP-compatible client

MCP Servers - Free for Subscribers

Connect YouTube MCP to Google ADK

Create your Vinkius account to connect YouTube to Google ADK 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 YouTube with Google ADK

Ask AI about this MCP

ChatGPT

Claude

Perplexity

Analyze Channel Health

Start by calling `get_channel` to retrieve full branding and performance stats for any given YouTube channel. This gives your agent a baseline view of the account's overall health. Because you're running on Google Cloud, this data immediately feeds into BigQuery for long-term analysis alongside other enterprise metrics.

Find Target Videos

Need to find specific content? `search_videos` returns a list of video metadata based on keywords or phrases. It's fast, and it sets up your agent for bulk processing. This process helps you identify groups of videos that need statistical deep dives into Vertex AI.

Extract Video Details

The `get_video` tool pulls every piece of metadata, the description, and all available statistics for one YouTube video. You get a massive context block perfect for Gemini's long-context reasoning. Your agent can then analyze that detailed data against your BigQuery records to spot trends.

Setup guide

Set up YouTube MCP in Google ADK

Prerequisites

Python 3.10+ installed
google-adk package (pip install google-adk)
Active Vinkius subscription with a valid endpoint token

1

Install Google ADK

Run pip install google-adk to install the Agent Development Kit. MCP support is included via the McpToolset class.
2

Connect via SSE transport

Use McpToolset.from_server() with SseServerParams pointing to your Vinkius endpoint. Replace [YOUR_TOKEN_HERE] with your token from cloud.vinkius.com.
3

Create an LlmAgent

Pass the returned mcp_tools list directly to LlmAgent(tools=mcp_tools). The ADK maps each MCP tool to a native Gemini function call — no manual schema definitions required.
4

Run with any Gemini model

The agent works with any Gemini model (gemini-2.0-flash, gemini-2.5-pro, etc.). Copy the full example on the right to get started with YouTube tools in your ADK agent.

agent.py

from google.adk.agents import LlmAgent
from google.adk.tools.mcp_tool.mcp_toolset import McpToolset
from google.adk.tools.mcp_tool.mcp_session_manager import SseServerParams

# Connect to the MCP via SSE
mcp_tools, exit_stack = await McpToolset.from_server(
    connection_params=SseServerParams(
        url="https://edge.vinkius.com/[YOUR_TOKEN_HERE]/mcp"
    )
)

# Create your agent with auto-discovered tools
agent = LlmAgent(
    name="YouTube_agent",
    model="gemini-2.0-flash",
    instruction="You have access to YouTube tools via MCP.",
    tools=mcp_tools,
)

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 YouTube. 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 YouTube 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 YouTube MCP in Google ADK

You use the `get_channel` tool first. The resulting statistics are then passed into a Gemini model within your agent for advanced, multi-step reasoning against data stored in BigQuery.

Yes, call `search_videos`. It provides the titles and descriptions. You can then filter this list within your agent workflow before running deeper analysis on GCP infrastructure.

You use `list_comments` to get recent or relevant comments for a video. Your agent treats these unstructured text inputs as data points, analyzing sentiment alongside the structured metadata.

It handles core public statistics: channel details via `get_channel`, video metadata via `get_video`, and comment threads. This works perfectly for enterprise-level audits.

The server touches YouTube public metadata, including channel statistics, video titles/descriptions, and user-generated comment content. All of this is available for BigQuery ingestion.

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