How to Use the GAN.ai MCP in Google ADK

Q: Can Google ADK filter which GAN.ai tools the agent sees?

You can pass a toolnames list to restrict access. If you only want the agent to check stats, just expose getvideostats and hide the generation endpoints.

Q: How does Google ADK handle GAN.ai video project lists?

The agent calls listvideoprojects to read available templates. It maps those IDs to your Vertex AI workflows. No hardcoding required.

Q: Does the MCP Server support single video creation here?

Yes. The agent uses generatesinglevideo for targeted outreach. It works perfectly for triggering custom videos based on specific BigQuery events.

Feed BigQuery data into GAN.ai video campaigns using Google ADK.

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Connect GAN.ai MCP to Google ADK

Create your Vinkius account to connect GAN.ai 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 GAN.ai with Google ADK

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Gemini-Powered Video Campaigns

Your Gemini agent pulls lead lists from BigQuery and feeds them directly into `generate_personalized_videos`. It reads the required schema via `get_project_metadata` to ensure every variable matches your database columns exactly. You bypass manual CSV uploads entirely. For massive datasets, the agent checks `get_workspace_info` first to confirm account limits. It then triggers the batch. Gemini long context window means it can hold the entire campaign strategy in memory while executing the render jobs.

Native MCP Server Tracking

The agent hits `get_generation_status` to monitor the render queue and track batch completion. It knows exactly when a batch finishes and when to alert your team. It then pulls `get_video_stats` to measure engagement. Since this runs on Google Cloud, your agent can write those view metrics straight back into BigQuery. You write campaign attribution data directly to your warehouse without building custom ETL pipelines.

Validate Landing Pages and Webhooks

Before sending traffic, the agent runs `verify_api_connection` to check the network. It uses `list_landing_templates` to confirm the destination pages exist and match the video content. It also audits your routing by calling `list_configured_webhooks`. If a webhook is missing, the agent flags it before the campaign goes live. You catch infrastructure errors before you burn rendering credits.

Setup guide

Set up GAN.ai 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 GAN.ai 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="GAN.ai_agent",
    model="gemini-2.0-flash",
    instruction="You have access to GAN.ai 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 GAN.ai. 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 GAN.ai MCP in Google ADK

Install google-adk and set up a McpToolset with your URL. Pass it to the LlmAgent tools array. It supports both Stdio and HTTP transports natively.

You can pass a tool_names list to restrict access. If you only want the agent to check stats, just expose `get_video_stats` and hide the generation endpoints.

The agent calls `list_video_projects` to read available templates. It maps those IDs to your Vertex AI workflows. No hardcoding required.

Yes. The agent uses `generate_single_video` for targeted outreach. It works perfectly for triggering custom videos based on specific BigQuery events.

The integration handles raw text variables and target email addresses for personalization. Vinkius operates on a zero-trust architecture. The connection authenticates via a single endpoint token, and the container terminates the moment the response is delivered.

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