How to Use the Easelly MCP in Google ADK

Q: How do I register Easelly tools in the Google ADK?

Instantiate McpToolset with the HTTP transport URL provided by Vinkius. Pass this toolset directly into your LlmAgent constructor.

Q: Can I restrict which Easelly tools the Google ADK agent sees?

Yes. Use the toolnames filter in your McpToolset configuration to expose only specific tools like updateinfographic.

Q: How does Google ADK handle Easelly layout updates?

The framework passes the schema from generatejson directly to the Gemini model. This MCP Server works with both transport layers, though HTTP is recommended for cloud-deployed Gemini agents.

Connect Gemini's million-token context to Easelly via the Google ADK to turn BigQuery data into visual assets.

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Connect Easelly MCP to Google ADK

Create your Vinkius account to connect Easelly 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 Easelly with Google ADK

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Map BigQuery data directly using Google ADK

The `create_infographic` tool acts as the visual entry point for your Google ADK enterprise pipelines. Your Gemini-powered agent reads massive datasets from BigQuery and maps them directly to a fresh visual layout. By loading this MCP Server into your `LlmAgent`, you let the model decide when to initialize new assets. The agent processes complex data patterns and translates them into visual structures without intermediate step-by-step programming.

Feed long-context insights into visual updates

The `update_infographic` tool modifies existing visual layouts using the deep context window of Gemini models. Your Google ADK agent parses thousands of pages of research reports and extracts the exact metrics needed for the update. The agent queries `generate_json` to understand the current layout coordinates before pushing changes. This ensures that the updated text blocks fit perfectly within the established design boundaries.

Export print-ready assets inside Vertex AI pipelines

The `generate_pdf` tool renders high-resolution documents directly from your Google ADK automated workflows. You can trigger this export as the final step of a Vertex AI data pipeline. To keep track of your visual assets, the agent uses `list_infographics` to audit your account library. If a specific graphic is missing, the agent runs `generate_image` to build the required visual elements on the fly.

Setup guide

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

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Common questions about Easelly MCP in Google ADK

Instantiate `McpToolset` with the HTTP transport URL provided by Vinkius. Pass this toolset directly into your `LlmAgent` constructor.

Yes. Use the `tool_names` filter in your `McpToolset` configuration to expose only specific tools like `update_infographic`.

The framework passes the schema from `generate_json` directly to the Gemini model. This MCP Server works with both transport layers, though HTTP is recommended for cloud-deployed Gemini agents.

Yes. The toolset configuration allows you to define either transport layer depending on whether your agent runs locally or in a cloud environment.

Your PDF exports and image assets are generated on demand. Vinkius uses ephemeral MCP execution environments, meaning your design files are never cached or stored on our servers after delivery.

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