How to Use the Viesus MCP in Google ADK

Q: How do I handle image data in Viesus with Google ADK?

You upload files using uploadimagetoviesus, which gets the binary data into the MCP Server. The agent then processes this input before creating an output.

Q: Can I check Viesus API status with Google ADK?

Absolutely. Use checkapihealth to verify that the entire system is up and running. This simple call confirms readiness for your complex, long-context reasoning tasks.

Q: How do I check my quota limits with Viesus and Google ADK?

Run getaccountcreditbalance to see your remaining API credits. This ensures the agent doesn't hit a spending limit halfway through a massive data run.

Q: What is the recommended way to use Viesus and Google ADK?

It’s best practice to first list available settings using listenhancementpresets. This ensures your agent uses an approved configuration for maximum stability within your cloud environment.

Run complex image processing within Google ADK agents using Viesus's MCP Server.

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Connect Viesus MCP to Google ADK

Create your Vinkius account to connect Viesus 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 Viesus with Google ADK

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Perplexity

Batch process and enhance images.

Your agent starts by uploading files via `upload_image_to_viesus`. After the upload, calling `enhance_image_ai` runs the AI adjustments. This setup lets you handle large datasets that already live in your cloud infrastructure.

Manage job lifecycle and status.

To track large batches of work, use `get_enhancement_job_status`. You can also review the full scope of past tasks using `list_processing_history`. This makes monitoring entire data pipelines reliable.

Retrieve detailed image information.

After processing, you can use `get_image_metadata` to pull technical details about the original file. Similarly, `get_image_metadata` lets you check the final output's properties too.

Setup guide

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

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Common questions about Viesus MCP in Google ADK

You upload files using `upload_image_to_viesus`, which gets the binary data into the MCP Server. The agent then processes this input before creating an output.

Absolutely. Use `check_api_health` to verify that the entire system is up and running. This simple call confirms readiness for your complex, long-context reasoning tasks.

The server primarily handles image binary data during processing. It also deals with structured records containing job IDs and enhancement parameters.

Run `get_account_credit_balance` to see your remaining API credits. This ensures the agent doesn't hit a spending limit halfway through a massive data run.

It’s best practice to first list available settings using `list_enhancement_presets`. This ensures your agent uses an approved configuration for maximum stability within your cloud environment.

Use it with your favorite AI tools

Connect this server to Cursor, Claude, VS Code, and more.

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