How to Use the Videco MCP in Google ADK

Q: Can I check Videco status with Google ADK?

Yes. You can call the checkvidecostatus tool at the start of any workflow. This confirms API connectivity and ensures your enterprise agents don't fail halfway through a mission.

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Connect Videco MCP to Google ADK

Create your Vinkius account to connect Videco 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 Videco with Google ADK

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Video Asset Management

Your agent uses `list_videos` to pull every asset record. It can then get specific details for any video using the `get_video` tool. You'll also find performance metrics via `get_video_analytics`. Need a new piece of content? Call `create_video` and let your agent handle the generation process.

Campaign Creation & Review

The system lets you list all active campaigns with `list_campaigns`. You can also pull detailed information on a single campaign using `get_campaign`. This makes it simple to audit your marketing history. To start fresh, simply call `create_campaign` and let the agent build out the initial structure.

Lead Data Access

The agent gets a full list of leads using `list_leads`. When you need specifics on one contact, it calls `get_lead`. This data integrates cleanly with BigQuery for deep analysis. This gives your team instant access to the freshest lead records, making them immediately ready for follow-up.

Setup guide

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

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

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Common questions about Videco MCP in Google ADK

The MCP Server exposes all tools as a callable set within your agent's context. Your agent treats them like native functions, allowing you to run marketing workflows directly from the Gemini ecosystem.

The server manages contact and campaign attribution details through tools like `list_leads` and `get_lead`. This structured data is ready to flow into BigQuery for complex, long-context analysis.

Yes. You can call the `check_videco_status` tool at the start of any workflow. This confirms API connectivity and ensures your enterprise agents don't fail halfway through a mission.

It does. Your agent can retrieve detailed performance data by calling `get_video_analytics`. This means you get metrics on viewership and campaign impact right alongside your other cloud data.

The server touches lead records, which include contact information and attribution details. Because the agent runs within Google Cloud infrastructure, this data benefits from BigQuery's enterprise-grade security models.

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