How to Use the Claid AI MCP in Google ADK

Q: How do I connect Claid AI to my Google ADK agent?

You instantiate an McpToolset in your Python code, pointing it to your Vinkius server URL. Pass that toolset to your LlmAgent and the Google ADK will automatically expose the Claid AI tools to your Gemini model.

Edit product images stored in Google Cloud with a Gemini agent using the Google ADK and this Claid AI server.

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Connect Claid AI MCP to Google ADK

Create your Vinkius account to connect Claid 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 Claid AI with Google ADK

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Process Images in Your GCP Workflow

The `enhance_image` tool gives your Google ADK agent a direct way to modify images. You can combine operations like AI upscaling, background removal, and HDR adjustments into one command. This is ideal for batch-processing product catalogs that live in Google Cloud Storage. Since Gemini models can handle huge contexts, your agent can reason about a large list of images from BigQuery, then use `upscale_image_resolution` and `remove_image_background` on each one. It connects your data directly to the action.

Build Resource-Aware Gemini Agents

An enterprise agent needs to manage its own resources. With the `get_claid_account_info` tool, your agent can check your Claid AI API quota before starting a massive job. It prevents unexpected failures or cost overruns. This MCP Server also exposes tools for managing asynchronous jobs and configurations. Your agent can use `get_processing_task_details` to check on long-running enhancements and `list_claid_webhooks` to understand the notification flow.

Discover Claid AI Capabilities with this MCP Server

You don't have to hardcode your agent's abilities. The `list_available_ai_operations` tool lets the agent ask the Claid AI MCP what edits are possible at any given time. Your Google ADK agent can also find its place in a larger system by using `list_claid_collections`. This lets it see existing image collections, so it can decide whether to create a new one or add to an existing set.

Setup guide

Set up Claid 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 Claid 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="Claid AI_agent",
    model="gemini-2.0-flash",
    instruction="You have access to Claid 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 Claid 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.

Why Choose Vinkius

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Connect your favorite tools to your AI and see exactly what's happening — every request, every response, in real time.

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Common questions about Claid AI MCP in Google ADK

You instantiate an `McpToolset` in your Python code, pointing it to your Vinkius server URL. Pass that toolset to your `LlmAgent` and the Google ADK will automatically expose the Claid AI tools to your Gemini model.

Yes, that's a perfect use case. Your agent can query BigQuery to get a list of image URIs, then loop through them, calling tools like `enhance_image` on each one via the MCP Server.

The server is designed for async work. Your agent can kick off a job, get a task ID, and then use the `get_processing_task_details` tool to check the status later without blocking.

No. Vinkius handles all the authentication. Your single MCP endpoint token is all that's needed to give your Google ADK agent access to the tools.

Your image data is sent over a secure connection for processing. Vinkius isolates each request in a dedicated V8 sandbox, meaning one user's process is completely separate from another's. The image data is only used for the requested operation.

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