How to Use the Veracode MCP in LangChain

Q: What is the best way to manage users with Veracode and LangChain?

You can use listveracodeusers to retrieve a list of authorized identity users. This allows your agent to build out role-based access control (RBAC) logic, ensuring that subsequent security actions are performed under the correct permissions.

Q: What happens if I delete an application profile with Veracode and LangChain?

Be careful; deleteapplication is irreversible. Before you run this, always use listapplications to verify the GUID of the target app. You don't want your agent running a destructive action on the wrong container.

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Connect Veracode MCP to LangChain

Create your Vinkius account to connect Veracode 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 Veracode with LangChain

Ask AI about this MCP

ChatGPT

Claude

Perplexity

Map out the full application landscape.

Need to know what apps you’re dealing with? `list_applications` returns a list of all your Veracode AppSec applications, each with a unique GUID. This GUID is required whenever you want to look up specific sub-resources for later steps in your chain.

Analyze compliance and risk scores.

When you call `get_application_details`, your agent gets the full picture of an application. It returns status details, including the Veracode compliance policy status, business criticality rating, deployment state, and risk scores. This data lets the next tool in your chain decide if the app is ready for production.

Pinpoint exact vulnerability remediation.

The `get_finding_details` tool gives you surgical precision on flaws. It doesn't just say 'vulnerability found'; it explains the CWE type, points to the affected source file and code path, and offers direct remediation guidance. Use this output in your chain to automatically generate a ticket for development.

Setup guide

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

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Common questions about Veracode MCP in LangChain

The MCP Server lets the agent treat every tool call as a step in its logic. For instance, you can first use `list_applications` to find an app GUID, then feed that ID into `get_application_details` to check its risk score before proceeding.

You can use `list_veracode_users` to retrieve a list of authorized identity users. This allows your agent to build out role-based access control (RBAC) logic, ensuring that subsequent security actions are performed under the correct permissions.

Absolutely. When you retrieve unified security findings using `list_security_findings`, those results become context. Your agent can then reference that data in subsequent steps, maintaining state across the entire complex reasoning chain.

Be careful; `delete_application` is irreversible. Before you run this, always use `list_applications` to verify the GUID of the target app. You don't want your agent running a destructive action on the wrong container.

This MCP Server handles sensitive application profile status, including deployment state and risk scores. Your AI client only sees the data you prompt it to use in a specific chain step.

Use it with your favorite AI tools

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

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