How to Use the UpGuard MCP in LangChain

Q: Can UpGuard's MCP Server handle vendor risk for LangChain?

Absolutely. You can list all vendors using listvendors and then specifically check each one's status by invoking listvendorrisks. This keeps your entire supply chain monitored within the LangChain workflow.

Q: What data does UpGuard provide for user risk in LangChain?

UpGuard offers detailed user risk data through listuserrisks. When using this with LangChain, your agent can take that raw user data and automatically cross-reference it against known identity breaches.

Q: Does UpGuard support IP monitoring for LangChain?

Yes. You use the listmonitoredips tool to see all IPs under watch. This output can then feed into a larger security audit chain built in your LangChain application.

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Connect UpGuard MCP to LangChain

Create your Vinkius account to connect UpGuard 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 UpGuard with LangChain

Ask AI about this MCP

ChatGPT

Claude

Perplexity

Sequence Risk Checks into Chains

You can start by calling `list_account_risks` to get a high-level overview. The output of this call then becomes the input for a subsequent tool, like running `get_vendor` against a specific vendor flagged as risky. This allows your agent to build deep reasoning pipelines. It doesn't just run checks; it determines *which* check comes next and in what order based on intermediate findings from the MCP Server.

Audit Identity Breaches Step-by-Step

The agent first runs `list_identity_breaches` to see recent incidents. Next, it can call `list_user_risks` using identifiers found in the breach list. This chaining mechanism ensures you get a complete picture of impact. The system processes these results sequentially, allowing your multi-step LangChain agent to form an actionable report.

Map Out All Monitored Assets

Start by using `list_vendors` to retrieve all monitored partners. Then, you can iterate through that list and call `list_vendor_risks` for each one. This systematic approach ensures full coverage of your supply chain risk. The resulting data flows into the next step in your LangChain workflow.

Setup guide

Set up UpGuard 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 UpGuard 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({
    "upguard-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 UpGuard transactions"
    })
    print(result["messages"][-1].content)

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Common questions about UpGuard MCP in LangChain

UpGuard provides structured tools that let your LangChain agent perform complex, multi-step security operations. Instead of simple queries, you build chains where the output of one check informs the next tool call.

Absolutely. You can list all vendors using `list_vendors` and then specifically check each one's status by invoking `list_vendor_risks`. This keeps your entire supply chain monitored within the LangChain workflow.

UpGuard offers detailed user risk data through `list_user_risks`. When using this with LangChain, your agent can take that raw user data and automatically cross-reference it against known identity breaches.

Yes. You use the `list_monitored_ips` tool to see all IPs under watch. This output can then feed into a larger security audit chain built in your LangChain application.

This MCP Server touches sensitive user risk data, including records from `list_user_risks`. Remember that you are building the logic for handling this information within your secure LangChain environment.

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