How to Use the Hudu MCP in LlamaIndex

Q: How do I load Hudu tools into LlamaIndex?

Initialize a BasicMCPClient with your endpoint URL. Then wrap it in McpToolSpec and call await mcptoolspec.totoollistasync() to pass them to your FunctionAgent.

Q: Can LlamaIndex search across multiple Hudu companies?

Yes. You can loop through listcompanies and feed the IDs into listassets or listpasswords to build a multi-tenant index.

Q: How do I filter assets?

The listassets tool accepts a company ID parameter. Your agent passes this ID to restrict the query to a single client environment.

Index your Hudu IT documentation directly into LlamaIndex to build queryable RAG applications.

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Connect Hudu MCP to LlamaIndex

Create your Vinkius account to connect Hudu 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 Hudu with LlamaIndex

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Index Hudu via MCP Server

The `list_articles` and `get_article` tools feed your knowledge base directly into a vector store. Your LlamaIndex application turns static IT documentation into a semantically searchable index. Engineers stop hunting for wikis. They query the index, and the system retrieves the exact fix from your actual API data instead of hallucinating a generic response.

Ground answers in live asset data

Call `list_companies` and `list_assets` to dump client environments into your RAG pipeline. The MCP Server ensures your index always reflects the current state of the infrastructure. When a technician asks about a specific firewall, LlamaIndex pulls the exact configuration using `get_asset`. The response is factual, immediate, and tied to real hardware.

Query operational procedures

Your RAG setup ingests step-by-step guides via the `list_procedures` and `get_procedure` tools. The agent retrieves the exact recovery steps the moment an alert fires. If the fix requires authentication, the system can fetch credentials using `get_password`. You build applications where live operational data and documentation live in a unified space.

Setup guide

Set up Hudu 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 Hudu 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 Hudu tools.",
)
response = await agent.run("List recent Hudu 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 Hudu. 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 Hudu MCP in LlamaIndex

Initialize a `BasicMCPClient` with your endpoint URL. Then wrap it in `McpToolSpec` and call `await mcp_tool_spec.to_tool_list_async()` to pass them to your FunctionAgent.

Yes. You can loop through `list_companies` and feed the IDs into `list_assets` or `list_passwords` to build a multi-tenant index.

No. You must schedule calls to the tools to refresh your vector store. Live queries using `get_asset` bypass the index for real-time data.

The `list_assets` tool accepts a company ID parameter. Your agent passes this ID to restrict the query to a single client environment.

Your hardware configurations and IP layouts remain within your controlled RAG pipeline. The MCP connection operates on a zero-trust model, ensuring data only moves between the API and your local index.

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