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How to Use the Bannerbear (Image Gen) MCP in Google ADK

Turn BigQuery datasets into thousands of personalized graphics using Google ADK.

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Connect Bannerbear (Image Gen) MCP to Google ADK

Create your Vinkius account to connect Bannerbear (Image Gen) 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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Connect the Bannerbear MCP Server

Enterprise teams store massive amounts of user data in Google Cloud. Connecting your Gemini-powered agent to your design system turns those raw tables into personalized visual assets. It's easy for the agent to grab a specific layout using `get_template` to understand the required text layers. Because Gemini handles massive token contexts, you feed it thousands of rows from BigQuery to map directly into those template variables.

High-volume image creation

Generating personalized ads for an entire customer base requires serious automation. Manual API calls break down when dealing with enterprise scale, which is why an MCP architecture makes sense. Your LlmAgent triggers `create_image` for individual graphics or `create_collection` for full ad sets. Passing the `McpToolset` through the HTTP transport guarantees these high-volume requests execute reliably against your Vinkius endpoint.

Automated video personalization

Video marketing usually involves expensive rendering pipelines. Letting an autonomous system handle the heavy lifting cuts production time to zero. Triggering `create_video` instructs the system to render motion graphics using Vertex AI-generated copy. The agent then runs `get_image` to verify completion and log the final MP4 URLs back to your database.

Setup guide

Set up Bannerbear (Image Gen) 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. 1

    Install Google ADK

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

  2. 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. 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. 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 Bannerbear (Image Gen) 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="Bannerbear (Image Gen)_agent",
    model="gemini-2.0-flash",
    instruction="You have access to Bannerbear (Image Gen) tools via MCP.",
    tools=mcp_tools,
)

Independent Platform Disclaimer: Vinkius is an independent platform and is not affiliated with, endorsed by, sponsored by, verified by, or otherwise authorized by Bannerbear. 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 Bannerbear (Image Gen) MCP in Google ADK

Install `google-adk` via pip. Initialize a `McpToolset` with your endpoint URL and attach it to your LlmAgent.
Your setup executes `list_templates` to view all available designs in your project. It reads the layer requirements to format the data correctly.
Native toolsets give Gemini direct agency over the generation process. It decides when to create an image based on your existing BigQuery triggers.
Yes. You dump massive lists of product descriptions into the prompt, and the agent iterates through them to generate hundreds of graphics.
Customer names and product strings pass through a sandbox that drops all data after processing. Vinkius manages the authentication without ever logging the payload contents sent to the render engine.

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