How to Use the Vast.ai (GPU Rental Cloud API) MCP in Google ADK

Q: How does the Google ADK manage GPU resource discovery with Vast.ai (GPU Rental Cloud API)?

The agent uses searchoffers to query Vast.ai's current listings. This provides up-to-date pricing and availability for specific GPUs, which is vital before connecting to your BigQuery data.

Q: Can the Google ADK provision GPU resources for a long-context run on Vast.ai (GPU Rental Cloud API)?

Yes. By calling rentinstance, you allocate the required compute power, allowing your agent to hold massive context windows while processing data streamed from BigQuery.

Q: What happens if I forget to clean up my resources using Vast.ai (GPU Rental Cloud API) with the Google ADK?

The listinstances tool helps you track everything, but remember that your agent must explicitly call deleteinstance. Otherwise, you'll keep paying for idle GPU time.

Q: Does the MCP Server guarantee resource availability?

It gives you current data. The searchoffers tool shows what’s available right now on Vast.ai; it doesn't reserve anything until your agent successfully calls rentinstance.

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Connect Vast.ai (GPU Rental Cloud API) MCP to Google ADK

Create your Vinkius account to connect Vast.ai (GPU Rental 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 Vast.ai (GPU Rental Cloud API) with Google ADK

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Search hardware needs with MCP Server

The `search_offers` tool lets your agent check what's available for GPU compute. You send a JSON payload specifying models, and it returns real-time offers from the Vast.ai marketplace. This step ensures that before running any heavy model training job, the agent knows exactly which hardware is within reach.

Deploy resources via Google ADK

Need to run a complex data processing pipeline? The `rent_instance` tool handles deploying the necessary GPU compute. Your agent provisions the resource and gets the connection details needed for Vertex AI. It’s perfect because your agents can automatically move from reading BigQuery data to running calculations on rented hardware.

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Your agent uses `list_instances` to get a full inventory of every active resource. It's the central point for auditing what compute capacity is currently assigned in your Google Cloud environment. When the job is done, it calls `delete_instance`. This cleans up the billing cycle and keeps your infrastructure tidy.

Setup guide

Set up Vast.ai (GPU Rental 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 Vast.ai (GPU Rental 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="Vast.ai (GPU Rental Cloud API)_agent",
    model="gemini-2.0-flash",
    instruction="You have access to Vast.ai (GPU Rental Cloud API) 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 Vast.ai. 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 Vast.ai (GPU Rental Cloud API) MCP in Google ADK

The agent uses `search_offers` to query Vast.ai's current listings. This provides up-to-date pricing and availability for specific GPUs, which is vital before connecting to your BigQuery data.

Yes. By calling `rent_instance`, you allocate the required compute power, allowing your agent to hold massive context windows while processing data streamed from BigQuery.

The `list_instances` tool helps you track everything, but remember that your agent must explicitly call `delete_instance`. Otherwise, you'll keep paying for idle GPU time.

It gives you current data. The `search_offers` tool shows what’s available right now on Vast.ai; it doesn't reserve anything until your agent successfully calls `rent_instance`.

This MCP Server deals with GPU metadata, including instance IDs, resource types (e.g., RTX 4090), and operational status.

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