How to Use the CatAAS MCP in Google ADK

Q: Can I filter tools when using CatAAS with Google ADK?

Use the toolnames filter during initialization. This allows you to expose only the specific functions your agent requires.

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Connect CatAAS MCP to Google ADK

Create your Vinkius account to connect CatAAS 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 CatAAS with Google ADK

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Visual content retrieval in Google ADK

Your agent triggers `get_random_cat` to pull fresh image metadata into your long-context reasoning flow. It fits right alongside your BigQuery data processing tasks. Gemini models ingest these URLs to provide context-aware responses. It turns static data into engaging visual outputs.

Structured tag management

Use `list_tags` to define valid search parameters for your agent. This keeps your Google ADK toolset constrained and predictable. Your agent verifies these tags before executing `get_cat_by_tag`. It keeps your infrastructure clean and prevents invalid queries from hitting the API.

Custom message overlays

The `get_cat_with_text` tool lets your agent generate images with specific, context-relevant strings. It is useful for automated reporting or status updates. Everything runs through the McpToolset wrapper. It connects your Google Cloud deployment to the service without blocking your main event loop.

Setup guide

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

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Common questions about CatAAS MCP in Google ADK

Initialize an McpToolset using your endpoint URL. Pass this object into your LlmAgent tool list to start executing commands.

Use the tool_names filter during initialization. This allows you to expose only the specific functions your agent requires.

Yes, the toolset supports both Stdio and HTTP transports. Pick the one that matches your specific Google Cloud environment configuration.

Only the metadata returned by the tools enters your context window. The agent processes these small strings without bloating your token count.

The service handles authentication via endpoint tokens. Your Google Cloud environment remains isolated, processing only the image references provided by the tool.

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