How to Use the ZooAnimals MCP in Google ADK

Q: How do I handle the MCP Server connection using Google ADK?

You use McpToolset(serverparams=StreamableHttpServerParameters(...)) and pass that toolset to your LlmAgent. It supports standard HTTP endpoints for connectivity.

Q: Can I limit which tools are exposed when using ZooAnimals with Google ADK?

Yep. You can use the optional toolnames filter parameter to restrict exactly which functions your agent sees, keeping its scope tight and focused.

Q: If my workflow requires getting a specific animal record using ZooAnimals with Google ADK, what's the best tool?

Use getanimalbyid. It takes one simple parameter—the ID—and returns all associated data. This is highly efficient for single-record lookups.

Act on animal data in BigQuery with your Google ADK agent.

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Setup ZooAnimals with Google ADK

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Perplexity

Look up animals by specific ID.

The `get_animal_by_id` tool lets your agent query a record using its unique identifier. When the LLM Agent needs data, it calls this function through the MCP Server. Since you're running enterprise agents on Google Cloud, integrating structured lookups like this keeps your reasoning grounded in facts, not assumptions.

Query species groups (Mammal, Bird, etc.).

You can ask the agent to pull records using `get_animals_by_type`, filtering by categories like 'Reptile' or 'Bird'. This is better than writing a massive SQL query for simple grouping. It allows your agent to segment data easily, which pairs well with BigQuery’s native filtering capabilities.

Fetch random animal samples.

Need quick examples? `get_random_animals` returns up to 10 species records instantly. This is perfect for testing agent logic or seeding initial data points. It keeps the conversation flowing without forcing you to know specific IDs upfront, making your Gemini-powered agents more flexible.

Setup guide

Set up ZooAnimals 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 ZooAnimals 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="ZooAnimals_agent",
    model="gemini-2.0-flash",
    instruction="You have access to ZooAnimals 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 ZooAnimals. 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 ZooAnimals MCP in Google ADK

Yes. Because you're using Gemini models with 1M+ token capacity, your agent can hold massive amounts of conversation and data retrieved from multiple MCP Server calls simultaneously.

The server provides animal classification records. The data types are IDs, species names, and biological categories like 'Mammal' or 'Reptile'. It’s clean, structured database output.

You use `McpToolset(server_params=StreamableHttpServerParameters(...))` and pass that toolset to your LlmAgent. It supports standard HTTP endpoints for connectivity.

Yep. You can use the optional `tool_names` filter parameter to restrict exactly which functions your agent sees, keeping its scope tight and focused.

Use `get_animal_by_id`. It takes one simple parameter—the ID—and returns all associated data. This is highly efficient for single-record lookups.

Use it with your favorite AI tools

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

OpenAI Agents SDK sdk-python

Google ADK sdk-python