How to Use the Civo (Cloud-native Kubernetes Cloud Provider API) MCP in Google ADK

Q: How do I connect my Google ADK agent to the Civo (Cloud-native Kubernetes Cloud Provider API) server?

After you pip install google-adk, you'll define an McpToolset using your Vinkius URL. Pass that toolset into the LlmAgent constructor to give your Gemini agent access to all the Civo tools.

Q: How can I limit the Civo (Cloud-native Kubernetes Cloud Provider API) actions my Google ADK agent can perform?

When you create the McpToolset from Vinkius, you can use the optional toolnames filter. Just pass a list of the exact tool names you want to expose, like 'listclusters', 'getquota', and the agent won't see any others.

Connect Gemini to your Civo infrastructure using the Google ADK for enterprise-scale cloud automation.

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Connect Civo (Cloud-native Kubernetes Cloud Provider API) MCP to Google ADK

Create your Vinkius account to connect Civo (Cloud-native Kubernetes Cloud Provider API) 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 Civo (Cloud-native Kubernetes Cloud Provider API) with Google ADK

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Plan Complex Civo Deployments

Feed a long-form architecture document to a Gemini-powered agent. Thanks to its massive context window, the agent can parse the entire plan and turn it into a series of Civo actions. It'll figure out the right sequence to call `create_network`, `create_cluster`, and `create_instance` to build out the whole environment. The agent can handle dependencies, like creating a volume with `create_volume` before attaching it to an instance with `attach_volume`. This isn't just running a script; it's reasoning about a complex goal and executing it on your Civo account.

Analyze Civo Costs in BigQuery

This is where the Google ecosystem really comes together. Build an agent that uses `get_charges` to pull your hourly Civo spending report. Then, have that same agent push the data directly into a BigQuery table for analysis. You can ask your agent complex questions in natural language, like 'Chart our Civo Kubernetes spending over the last 30 days.' The agent uses Civo tools to get the data and Google Cloud tools to analyze it.

Build Civo Operators with your MCP Server

Use the Google ADK to build agents that act as automated operators for your Civo infrastructure. For example, an agent could watch for alerts from Google Cloud Monitoring and then take corrective action on Civo. It could respond to a high-CPU alert by resizing an instance with `resize_instance`. It can also handle routine maintenance. Schedule an agent to periodically `recycle_cluster_node` to keep your Kubernetes clusters fresh, or `soft_reboot_instance` on machines that need it. This gives your Google agent the tools to manage Civo directly.

Setup guide

Set up Civo (Cloud-native Kubernetes Cloud Provider API) 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 Civo (Cloud-native Kubernetes Cloud Provider API) 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="Civo (Cloud-native Kubernetes Cloud Provider API)_agent",
    model="gemini-2.0-flash",
    instruction="You have access to Civo (Cloud-native Kubernetes Cloud Provider API) tools via MCP.",
    tools=mcp_tools,
)

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Common questions about Civo (Cloud-native Kubernetes Cloud Provider API) MCP in Google ADK

After you `pip install google-adk`, you'll define an `McpToolset` using your Vinkius URL. Pass that toolset into the `LlmAgent` constructor to give your Gemini agent access to all the Civo tools.

Yes. Gemini's long-context abilities allow it to process a large spec document. The agent can then use tools like `create_cluster`, `create_network`, and `create_instance` to build the environment based on the plan.

When you create the `McpToolset` from Vinkius, you can use the optional `tool_names` filter. Just pass a list of the exact tool names you want to expose, like `['list_clusters', 'get_quota']`, and the agent won't see any others.

Yes, that's the main benefit. The Google ADK is designed to operate within the Google Cloud ecosystem, letting your agent combine Civo actions with native calls to Vertex AI, BigQuery, and other Google services.

Your agent will handle data about your Civo resources, like cluster names, instance IPs, and firewall rules. Vinkius secures the connection with a single token, and all operations run in a zero-trust environment, so your underlying Civo keys are never exposed to the agent or Google's services.

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