How to Use the Beagle Security MCP in LangChain

Q: Can a LangChain ReAct agent automatically stop a failing Beagle Security test?

Yes. The agent calls getteststatus to monitor the run, and if it detects issues, it invokes stoptest immediately.

Trigger security tests and parse vulnerability data directly inside your LangChain chains.

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Connect Beagle Security MCP to LangChain

Create your Vinkius account to connect Beagle Security 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 Beagle Security with LangChain

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Run automated penetration tests inside LangChain pipelines

The `start_test` tool lets your LangChain agent kick off an active vulnerability scan on your application. Your agent monitors the run using `get_test_status` inside a ReAct loop, deciding when to proceed based on the actual completion state. LangSmith traces every step of this execution, capturing token usage and the raw JSON payload of your test. You get a clear view of how your chain interacts with Beagle Security without guessing.

Map vulnerabilities to your LangChain agent workflows

With the `get_vulnerabilities` tool, your LangChain chain pulls the exact security flaws found during the latest scan. Your agent feeds this raw list into a custom parser to format tickets or alert engineering teams. By coupling this with `get_test_results`, your pipeline makes decisions on whether to block a release or pass the build. You write the logic, and the MCP Server supplies the live security context.

Audit your Beagle Security assets with MCP Server tools

Using the `list_projects` tool, your agent fetches your configured security targets directly into your agent's context. Your LangChain agent can map these projects to `list_applications` to verify that every endpoint has active monitoring. If a project lacks a recent test, the chain triggers a new one or flags the gap. This keeps your security posture visible inside your existing Python or TypeScript codebase.

Setup guide

Set up Beagle Security 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 Beagle Security 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({
    "beagle-security-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 Beagle Security 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 Beagle Security. 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 Beagle Security MCP in LangChain

You initialize the MCP adapter, connect to the Vinkius endpoint, and pass the tools directly to your LangChain agent. The agent uses tools like `list_projects` and `start_test` to manage your security tests.

Yes. The agent calls `get_test_status` to monitor the run, and if it detects issues, it invokes `stop_test` immediately.

LangSmith logs every single tool call, showing you exactly when `get_vulnerabilities` or `get_application_details` was executed. You see the latency and exact payloads for each run.

Your chain receives the structured vulnerability list and can execute conditional logic, like routing high-severity items to a PagerDuty integration.

Vinkius runs the server in an ephemeral V8 sandbox, meaning your vulnerability lists and test results are never stored on the platform. The data passes directly to your LangChain client and is wiped instantly.

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