How to Use the ContentGroove MCP in Google ADK

Feed AI-generated video highlights directly into your Google Cloud data pipeline using Google ADK.

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Connect ContentGroove MCP to Google ADK

Create your Vinkius account to connect ContentGroove 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.

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Setup ContentGroove with Google ADK

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Ingest video files directly from Google Cloud storage

Connect your enterprise video library to your Gemini models. Your agent uses `create_media_from_url` to import files stored in Cloud Storage, or runs `create_direct_upload` to generate an upload link for raw video files. This MCP Server allows your Google ADK agents to process hours of footage. Because Gemini handles massive context windows, your agent can read the complete output of `list_media` and analyze trends across your entire video catalog in a single run.

Query video clip metadata for BigQuery analysis

Sync your video performance data with your data warehouse. Your agent can run `list_all_clips` and `get_clip_details` to gather highlight timestamps and scores, then feed that structured data directly into BigQuery. Using the Google ADK, you can build a pipeline where Gemini analyzes which video segments perform best. The agent pulls the metadata using `get_media_details` and writes SQL queries to join this with your existing marketing metrics.

Monitor enterprise video processing at scale with this MCP Server

Keep tabs on massive batch-processing jobs without leaving your terminal. Your agent polls `get_media_status` to watch the pipeline progress, then triggers downstream tasks using `get_media_clips` once the AI finishes cutting the highlights. Google ADK lets you restrict which tools are exposed. You can use the tool names filter to ensure your background workers only have access to status checking and clip listing tools, keeping your enterprise security tight.

Setup guide

Set up ContentGroove 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 ContentGroove 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="ContentGroove_agent",
    model="gemini-2.0-flash",
    instruction="You have access to ContentGroove tools via MCP.",
    tools=mcp_tools,
)

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Common questions about ContentGroove MCP in Google ADK

Install the Google ADK package and define the toolset pointing to your Vinkius HTTP URL. Pass that toolset to your agent constructor, and Gemini will automatically detect the video slicing capabilities.

Yes. Your agent can pull the full transcript and clip data using the clip details tool, then use the ADK's native BigQuery integration to write that data into a table for sentiment analysis.

Gemini can ingest massive amounts of metadata. Your agent can call the clip lister to retrieve hundreds of highlight records and analyze the entire batch at once to spot editing patterns.

This server supports both standard Stdio and Streamable HTTP transports. When running on Google Cloud Run or Kubernetes, the HTTP transport is ideal for handling concurrent video requests.

Your video metadata and project statuses are isolated. This MCP Server keeps your video metadata isolated, and Vinkius manages the authentication tokens securely, ensuring that your Google ADK agents access endpoints without exposing API keys in your cloud logs.

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