Intruder MCP Server for LangChain 10 tools — connect in under 2 minutes
LangChain is the leading Python framework for composable LLM applications. Connect Intruder through the Vinkius and LangChain agents can call every tool natively — combine them with retrievers, memory, and output parsers for sophisticated AI pipelines.
ASK AI ABOUT THIS MCP SERVER
Vinkius supports streamable HTTP and SSE.
import asyncio
from langchain_mcp_adapters.client import MultiServerMCPClient
from langchain_openai import ChatOpenAI
from langgraph.prebuilt import create_react_agent
async def main():
# Your Vinkius token — get it at cloud.vinkius.com
async with MultiServerMCPClient({
"intruder": {
"transport": "streamable_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,
)
response = await agent.ainvoke({
"messages": [{
"role": "user",
"content": "Using Intruder, show me what tools are available.",
}]
})
print(response["messages"][-1].content)
asyncio.run(main())
* Every MCP server runs on Vinkius-managed infrastructure inside AWS - a purpose-built runtime with per-request V8 isolates, Ed25519 signed audit chains, and sub-40ms cold starts optimized for native MCP execution. See our infrastructure
About Intruder MCP Server
Empower your AI agents to manage your cybersecurity posture with Intruder.io. This MCP server allows you to list security targets, track vulnerability scans, retrieve identified issues, and monitor cloud integrations directly through the Intruder API. Ideal for automating DevSecOps workflows and security auditing.
LangChain's ecosystem of 500+ components combines seamlessly with Intruder through native MCP adapters. Connect 10 tools via the Vinkius and use ReAct agents, Plan-and-Execute strategies, or custom agent architectures — with LangSmith tracing giving full visibility into every tool call, latency, and token cost.
The Intruder MCP Server exposes 10 tools through the Vinkius. Connect it to LangChain in under two minutes — no API keys to rotate, no infrastructure to provision, no vendor lock-in. Your configuration, your data, your control.
How to Connect Intruder to LangChain via MCP
Follow these steps to integrate the Intruder MCP Server with LangChain.
Install dependencies
Run pip install langchain langchain-mcp-adapters langgraph langchain-openai
Replace the token
Replace [YOUR_TOKEN_HERE] with your Vinkius token
Run the agent
Save the code and run python agent.py
Explore tools
The agent discovers 10 tools from Intruder via MCP
Why Use LangChain with the Intruder MCP Server
LangChain provides unique advantages when paired with Intruder through the Model Context Protocol.
The largest ecosystem of integrations, chains, and agents — combine Intruder MCP tools with 500+ LangChain components
Agent architecture supports ReAct, Plan-and-Execute, and custom strategies with full MCP tool access at every step
LangSmith tracing gives you complete visibility into tool calls, latencies, and token usage for production debugging
Memory and conversation persistence let agents maintain context across Intruder queries for multi-turn workflows
Intruder + LangChain Use Cases
Practical scenarios where LangChain combined with the Intruder MCP Server delivers measurable value.
RAG with live data: combine Intruder tool results with vector store retrievals for answers grounded in both real-time and historical data
Autonomous research agents: LangChain agents query Intruder, synthesize findings, and generate comprehensive research reports
Multi-tool orchestration: chain Intruder tools with web scrapers, databases, and calculators in a single agent run
Production monitoring: use LangSmith to trace every Intruder tool call, measure latency, and optimize your agent's performance
Intruder MCP Tools for LangChain (10)
These 10 tools become available when you connect Intruder to LangChain via MCP:
get_account
Use to verify identity and account settings. Gets your Intruder account details
get_issue
Returns detailed descriptions, remediation advice, and affected targets. Essential for investigating and fixing security flaws. Retrieves details for a specific issue
get_scan
Returns the list of targets included, scan duration, and a summary of findings. Use this to audit the results of a specific security assessment. Retrieves details for a specific scan
get_target
Returns metadata and associated tags. Use this to deep-dive into the security status of a specific asset. Retrieves details for a specific target
list_cloud_integrations
Essential for auditing how Intruder discovers new targets in the cloud infrastructure. Lists all configured cloud integrations (AWS, Azure, Google Cloud)
list_issues
Returns issue titles, severity levels (Low, Medium, High, Critical), and status. Use this as the primary tool for security posture auditing. Lists all identified vulnerability issues
list_licences
Useful for verifying subscription status and capacity. Lists all account licences
list_scans
Includes scan types, timestamps, and IDs. Essential for tracking scan frequency and monitoring ongoing security checks. Lists all vulnerability scans
list_targets
Returns target names, IDs, and types. Use this to identify which assets are being scanned for vulnerabilities. Lists all infrastructure and application targets
list_teams
Useful for understanding organizational access controls. Lists all organization teams
Example Prompts for Intruder in LangChain
Ready-to-use prompts you can give your LangChain agent to start working with Intruder immediately.
"List all active targets in my Intruder account."
"Show me the latest vulnerability issues found."
"Check the status of my recent scans."
Troubleshooting Intruder MCP Server with LangChain
Common issues when connecting Intruder to LangChain through the Vinkius, and how to resolve them.
MultiServerMCPClient not found
pip install langchain-mcp-adaptersIntruder + LangChain FAQ
Common questions about integrating Intruder MCP Server with LangChain.
How does LangChain connect to MCP servers?
langchain-mcp-adapters to create an MCP client. LangChain discovers all tools and wraps them as native LangChain tools compatible with any agent type.Which LangChain agent types work with MCP?
Can I trace MCP tool calls in LangSmith?
Connect Intruder with your favorite client
Step-by-step setup guides for every MCP-compatible client and framework:
Anthropic's native desktop app for Claude with built-in MCP support.
AI-first code editor with integrated LLM-powered coding assistance.
GitHub Copilot in VS Code with Agent mode and MCP support.
Purpose-built IDE for agentic AI coding workflows.
Autonomous AI coding agent that runs inside VS Code.
Anthropic's agentic CLI for terminal-first development.
Python SDK for building production-grade OpenAI agent workflows.
Google's framework for building production AI agents.
Type-safe agent development for Python with first-class MCP support.
TypeScript toolkit for building AI-powered web applications.
TypeScript-native agent framework for modern web stacks.
Python framework for orchestrating collaborative AI agent crews.
Leading Python framework for composable LLM applications.
Data-aware AI agent framework for structured and unstructured sources.
Microsoft's framework for multi-agent collaborative conversations.
Connect Intruder to LangChain
Get your token, paste the configuration, and start using 10 tools in under 2 minutes. No API key management needed.