H2O.ai MCP Server for Google ADK 6 tools — connect in under 2 minutes
Google Agent Development Kit (ADK) is Google's framework for building production AI agents. Add H2O.ai as an MCP tool provider through Vinkius and your ADK agents can call every tool with full schema introspection.
ASK AI ABOUT THIS MCP SERVER
Vinkius supports streamable HTTP and SSE.
from google.adk.agents import Agent
from google.adk.tools.mcp_tool import McpToolset
from google.adk.tools.mcp_tool.mcp_session_manager import (
StreamableHTTPConnectionParams,
)
# Your Vinkius token. get it at cloud.vinkius.com
mcp_tools = McpToolset(
connection_params=StreamableHTTPConnectionParams(
url="https://edge.vinkius.com/[YOUR_TOKEN_HERE]/mcp",
)
)
agent = Agent(
model="gemini-2.5-pro",
name="h2oai_agent",
instruction=(
"You help users interact with H2O.ai "
"using 6 available tools."
),
tools=[mcp_tools],
)
* Every MCP server runs on Vinkius-managed infrastructure inside AWS - a purpose-built runtime with per-request V8 isolates, Ed25519 signed audit chains, and sub-40ms cold starts optimized for native MCP execution. See our infrastructure
About H2O.ai MCP Server
Connect your H2O.ai instance to any AI agent and take full control of your machine learning lifecycle, automated data processing, and cluster monitoring through natural conversation.
Google ADK natively supports H2O.ai as an MCP tool provider. declare Vinkius Edge URL and the framework handles discovery, validation, and execution automatically. Combine 6 tools with Gemini's long-context reasoning for complex multi-tool workflows, with production-ready session management and evaluation built in.
What you can do
- Data Frame Orchestration — List structured datasets securely loaded into H2O clusters and retrieve specific dimensional data mapping explicit frame columns natively
- Model Inventory Auditing — Iterate through tracked machine learning models previously generated inside your cloud instance to verify performance metrics and versions
- Inference Monitoring — Access detailed configuration blocks for active model architectures to verify deployment boundaries and parameters synchronously
- Training Job Oversight — Query timeline nodes tracking long-running tasks and model training jobs queued on the cluster to monitor execution progress
- Cloud Cluster Auditing — Ping root endpoints defining hardware architecture health and memory utilization within your H2O instances flawlessly
- MLOps Command Center — Verify available frames and models to orchestrate complex data science workflows and model evaluations using natural language
- Status Verification — Identify precise executing statuses of ongoing jobs to ensure your AI pipeline is operational and within resource limits securely
The H2O.ai MCP Server exposes 6 tools through the Vinkius. Connect it to Google ADK in under two minutes — no API keys to rotate, no infrastructure to provision, no vendor lock-in. Your configuration, your data, your control.
How to Connect H2O.ai to Google ADK via MCP
Follow these steps to integrate the H2O.ai MCP Server with Google ADK.
Install Google ADK
Run pip install google-adk
Replace the token
Replace [YOUR_TOKEN_HERE] with your Vinkius token
Create the agent
Save the code above and integrate into your ADK workflow
Explore tools
The agent will discover 6 tools from H2O.ai via MCP
Why Use Google ADK with the H2O.ai MCP Server
Google ADK provides unique advantages when paired with H2O.ai through the Model Context Protocol.
Google ADK natively supports MCP tool servers. declare a tool provider and the framework handles discovery, validation, and execution
Built on Gemini models, ADK provides long-context reasoning ideal for complex multi-tool workflows with H2O.ai
Production-ready features like session management, evaluation, and deployment come built-in. not bolted on
Seamless integration with Google Cloud services means you can combine H2O.ai tools with BigQuery, Vertex AI, and Cloud Functions
H2O.ai + Google ADK Use Cases
Practical scenarios where Google ADK combined with the H2O.ai MCP Server delivers measurable value.
Enterprise data agents: ADK agents query H2O.ai and cross-reference results with internal databases for comprehensive analysis
Multi-modal workflows: combine H2O.ai tool responses with Gemini's vision and language capabilities in a single agent
Automated compliance checks: schedule ADK agents to query H2O.ai regularly and flag policy violations or configuration drift
Internal tool platforms: build self-service agent platforms where teams connect their own MCP servers including H2O.ai
H2O.ai MCP Tools for Google ADK (6)
These 6 tools become available when you connect H2O.ai to Google ADK via MCP:
cloud_status
Get cloud status
get_frame
Get frame
get_model
Get model
list_frames
List frames
list_jobs
List jobs
list_models
List models
Example Prompts for H2O.ai in Google ADK
Ready-to-use prompts you can give your Google ADK agent to start working with H2O.ai immediately.
"List all machine learning models in my H2O cluster"
"What is the current status of the H2O cloud cluster?"
"Show me the last 3 training jobs"
Troubleshooting H2O.ai MCP Server with Google ADK
Common issues when connecting H2O.ai to Google ADK through the Vinkius, and how to resolve them.
McpToolset not found
pip install --upgrade google-adkH2O.ai + Google ADK FAQ
Common questions about integrating H2O.ai MCP Server with Google ADK.
How does Google ADK connect to MCP servers?
Can ADK agents use multiple MCP servers?
Which Gemini models work best with MCP tools?
Connect H2O.ai with your favorite client
Step-by-step setup guides for every MCP-compatible client and framework:
Anthropic's native desktop app for Claude with built-in MCP support.
AI-first code editor with integrated LLM-powered coding assistance.
GitHub Copilot in VS Code with Agent mode and MCP support.
Purpose-built IDE for agentic AI coding workflows.
Autonomous AI coding agent that runs inside VS Code.
Anthropic's agentic CLI for terminal-first development.
Python SDK for building production-grade OpenAI agent workflows.
Google's framework for building production AI agents.
Type-safe agent development for Python with first-class MCP support.
TypeScript toolkit for building AI-powered web applications.
TypeScript-native agent framework for modern web stacks.
Python framework for orchestrating collaborative AI agent crews.
Leading Python framework for composable LLM applications.
Data-aware AI agent framework for structured and unstructured sources.
Microsoft's framework for multi-agent collaborative conversations.
Connect H2O.ai to Google ADK
Get your token, paste the configuration, and start using 6 tools in under 2 minutes. No API key management needed.