How to Use the H2O.ai MCP in LlamaIndex

Build RAG apps with LlamaIndex using live H2O.ai model data as your searchable knowledge base.

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Connect H2O.ai MCP to LlamaIndex

Create your Vinkius account to connect H2O.ai to LlamaIndex 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 H2O.ai with LlamaIndex

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Index your model metadata

Transform your H2O.ai model registry into a queryable index. By running `list_models`, your agent gathers current model states and injects them directly into your LlamaIndex vector store. This turns static API data into a searchable asset. You can ask your agent about specific model versions, and it will pull data grounded in the actual H2O.ai registry.

Query training job history

Use LlamaIndex to keep track of past experiments. Your agent iterates through `list_jobs` to identify successful training runs and index their parameters for future retrieval. This creates a searchable history of your development work. You no longer have to guess which model performed best on a specific dataset because the history is now part of your knowledge base.

Ground answers in live cluster data

Stop relying on hallucinations for infrastructure status. The agent calls `cloud_status` to fetch current cluster health and indexes that information for real-time reporting. When you query your index, the agent provides answers based on the current cluster load. This keeps your documentation accurate and updated with the latest system state.

Setup guide

Set up H2O.ai MCP in LlamaIndex

Prerequisites

Python 3.10+ installed
llama-index-tools-mcp package
Active Vinkius subscription with a valid endpoint token

1

Install dependencies
Run pip install llama-index-tools-mcp llama-index-llms-openai. The MCP tools package provides BasicMCPClient and McpToolSpec.
2

Connect with BasicMCPClient
Point BasicMCPClient to your Vinkius endpoint URL. Replace [YOUR_TOKEN_HERE] with your token from cloud.vinkius.com. Supports SSE and Streamable HTTP transports.
3

Convert to LlamaIndex tools
Call mcp_tool_spec.to_tool_list_async() to convert all H2O.ai MCP tools into native FunctionTool objects that any LlamaIndex agent can use.
4

Run with any LLM
Create a FunctionAgent with the tools and your preferred LLM. Swap OpenAI for Anthropic, Gemini, or any LlamaIndex-supported provider.

agent.py

from llama_index.tools.mcp import BasicMCPClient, McpToolSpec
from llama_index.core.agent.workflow import FunctionAgent
from llama_index.llms.openai import OpenAI

# Connect to the MCP
mcp_client = BasicMCPClient(
    "https://edge.vinkius.com/[YOUR_TOKEN_HERE]/mcp"
)
mcp_tool_spec = McpToolSpec(client=mcp_client)

# Convert MCP tools to LlamaIndex tools
tools = await mcp_tool_spec.to_tool_list_async()

# Create and run the agent
agent = FunctionAgent(
    tools=tools,
    llm=OpenAI(model="gpt-4o"),
    system_prompt="You have access to H2O.ai tools.",
)
response = await agent.run("List recent H2O.ai data")

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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 H2O.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 H2O.ai MCP in LlamaIndex

Initialize the MCP client and pass the tool spec to your FunctionAgent. This allows the system to index the outputs of your H2O.ai queries.

No, because the agent retrieves the actual model list using `list_models`. The answers are grounded in the live data returned by the server.

Absolutely. Once the job list is retrieved and indexed, your agent can perform semantic searches across your entire training history.

The MCP server acts as a secure bridge. Only the metadata authorized for your queries touches the LlamaIndex vector store.

It processes model registry records and job metadata. We ensure this data is encrypted in transit and only accessed via your authenticated endpoint.

Use it with your favorite AI tools

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

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