How to Use the Hudu MCP in LangChain

Q: How do I connect Hudu to LangChain?

Use MultiServerMCPClient with the HTTP transport URL. Call client.gettools() and pass the resulting list into your createagent setup.

Q: Can LangChain agents read Hudu passwords?

Yes. The getpassword tool returns the exact credential details. You control which agents have access to this tool in your chain.

Q: Does the server support creating records?

The server exposes createcompany and createasset for write operations. Your agent requires specific parameters like the asset name and company ID to execute these.

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Connect Hudu MCP to LangChain

Create your Vinkius account to connect Hudu to LangChain 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 LangChain

Ask AI about this MCP

ChatGPT

Claude

Perplexity

Chain Hudu lookups in LangChain

The `list_companies` and `get_company` tools let your LangChain agent pull client environments into memory instantly. It maps out the infrastructure before deciding what to do next. Pass that context into a ReAct agent. It calls `list_assets` to find specific hardware, then pulls the exact credentials using `get_password` without breaking the chain.

Automate incident response pipelines

Your agent invokes `get_procedure` to read step-by-step recovery guides during an active outage. LangSmith tracks the exact latency and token usage of every single MCP Server call. You build pipelines where the output of an infrastructure query dictates the next step. If a server is down, the agent checks `list_articles` to find the known fix and executes it.

Provision environments via MCP

Connect your provisioning scripts directly to `create_company` to register new clients the second their contract is signed. Your multi-step reasoning pipeline handles the setup without human intervention. Once the tenant exists, the agent fires `create_asset` to document the assigned firewalls and switches. The entire onboarding process happens in the background.

Setup guide

Set up Hudu MCP in LangChain

Prerequisites

Python 3.10+ installed
langchain-mcp-adapters + langgraph packages
Active Vinkius subscription with a valid endpoint token

1

Install dependencies
Run pip install langchain-mcp-adapters langgraph langchain-openai. The MCP adapters package converts MCP tools into native LangChain BaseTool objects.
2

Connect via HTTP transport
Use MultiServerMCPClient with "transport": "http" pointing to your Vinkius endpoint. Replace [YOUR_TOKEN_HERE] with your token from cloud.vinkius.com.
3

Create a ReAct agent
Pass the discovered tools to create_react_agent() from LangGraph. The agent automatically routes Hudu tool calls through the MCP protocol.
4

Run with any LLM
Swap ChatOpenAI for ChatAnthropic, ChatGoogleGenerativeAI, or any LangChain-compatible model. The MCP tools work identically across all providers.

agent.py

from langchain_mcp_adapters.client import MultiServerMCPClient
from langgraph.prebuilt import create_react_agent
from langchain_openai import ChatOpenAI

async with MultiServerMCPClient({
    "hudu-alternative-mcp": {
        "transport": "http",
        "url": "https://edge.vinkius.com/[YOUR_TOKEN_HERE]/mcp",
    }
}) as client:
    tools = client.get_tools()

    agent = create_react_agent(
        ChatOpenAI(model="gpt-4o"),
        tools,
    )
    result = await agent.ainvoke({
        "messages": "List recent Hudu transactions"
    })
    print(result["messages"][-1].content)

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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 LangChain

Use `MultiServerMCPClient` with the HTTP transport URL. Call `client.get_tools()` and pass the resulting list into your `create_agent` setup.

Yes. The `get_password` tool returns the exact credential details. You control which agents have access to this tool in your chain.

LangSmith traces will show latency spikes if you hit limits. You need to build retry logic into your ReAct agent loops to handle throttling.

The server exposes `create_company` and `create_asset` for write operations. Your agent requires specific parameters like the asset name and company ID to execute these.

The MCP connection routes your vault credentials straight to your isolated LangChain environment. Vinkius runs the server in an ephemeral V8 Isolate Sandbox, meaning no third party stores your IT infrastructure secrets.

Use it with your favorite AI tools

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