How to Use the Akash Network (Decentralized GPU & Cloud API) MCP in Google ADK

Q: Can I filter tools when using the Akash Network (Decentralized GPU & Cloud API) with Google ADK?

You can. Use the toolnames filter in your toolset configuration to restrict which functions your agent is allowed to invoke.

Connect Google ADK agents to decentralized compute using the Akash Network (Decentralized GPU & Cloud API) MCP Server.

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Connect Akash Network (Decentralized GPU & Cloud API) MCP to Google ADK

Create your Vinkius account to connect Akash Network (Decentralized GPU & Cloud 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 Akash Network (Decentralized GPU & Cloud API) with Google ADK

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Provision infrastructure from Google ADK

Send your SDL files to `create_deployment` to spin up decentralized GPU clusters. It integrates directly into your agent's toolset. Check on your active tasks with `list_deployments`. You get a clear view of what is running across the network.

Control spending on Akash Network (Decentralized GPU & Cloud API)

Use `update_deployment` to modify your resources on the fly. You gain precise control over your compute footprint through your Google ADK agent. Keep your escrow balance topped off with `add_deposit`. It prevents accidental shutdowns by maintaining sufficient funds for your lease.

Analyze provider performance in Google ADK

Query `list_providers` to see which nodes are currently accepting work. You can then pull deep metrics on any node using `get_provider`. Accept bids using `create_lease` to lock in the best hardware for your task. The process happens entirely within your agent's decision loop.

Setup guide

Set up Akash Network (Decentralized GPU & Cloud 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 Akash Network (Decentralized GPU & Cloud 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="Akash Network (Decentralized GPU & Cloud API)_agent",
    model="gemini-2.0-flash",
    instruction="You have access to Akash Network (Decentralized GPU & Cloud API) tools via MCP.",
    tools=mcp_tools,
)

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Common questions about Akash Network (Decentralized GPU & Cloud API) MCP in Google ADK

You initialize an McpToolset with your server URL. Then, you pass this toolset to your LlmAgent to give it access to all 13 cloud management functions.

You can. Use the tool_names filter in your toolset configuration to restrict which functions your agent is allowed to invoke.

The server supports HTTP transports natively. This works perfectly with the StreamableHttpServerParameters class in your setup.

The manifest is treated as a transient object. It exists only for the duration of the API call to your deployment service.

All tool invocations are logged by your agent framework. You can track every call to `close_deployment` or `create_lease` in your local logs.

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