Intruder MCP Server for LlamaIndex 10 tools — connect in under 2 minutes
LlamaIndex specializes in data-aware AI agents that connect LLMs to structured and unstructured sources. Add Intruder as an MCP tool provider through the Vinkius and your agents can query, analyze, and act on live data alongside your existing indexes.
ASK AI ABOUT THIS MCP SERVER
Vinkius supports streamable HTTP and SSE.
import asyncio
from llama_index.tools.mcp import BasicMCPClient, McpToolSpec
from llama_index.core.agent.workflow import FunctionAgent
from llama_index.llms.openai import OpenAI
async def main():
# Your Vinkius token — get it at cloud.vinkius.com
mcp_client = BasicMCPClient("https://edge.vinkius.com/[YOUR_TOKEN_HERE]/mcp")
mcp_tool_spec = McpToolSpec(client=mcp_client)
tools = await mcp_tool_spec.to_tool_list_async()
agent = FunctionAgent(
tools=tools,
llm=OpenAI(model="gpt-4o"),
system_prompt=(
"You are an assistant with access to Intruder. "
"You have 10 tools available."
),
)
response = await agent.run(
"What tools are available in Intruder?"
)
print(response)
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.
LlamaIndex agents combine Intruder tool responses with indexed documents for comprehensive, grounded answers. Connect 10 tools through the Vinkius and query live data alongside vector stores and SQL databases in a single turn — ideal for hybrid search, data enrichment, and analytical workflows.
The Intruder MCP Server exposes 10 tools through the Vinkius. Connect it to LlamaIndex 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 LlamaIndex via MCP
Follow these steps to integrate the Intruder MCP Server with LlamaIndex.
Install dependencies
Run pip install llama-index-tools-mcp llama-index-llms-openai
Replace the token
Replace [YOUR_TOKEN_HERE] with your Vinkius token
Run the agent
Save to agent.py and run: python agent.py
Explore tools
The agent discovers 10 tools from Intruder
Why Use LlamaIndex with the Intruder MCP Server
LlamaIndex provides unique advantages when paired with Intruder through the Model Context Protocol.
Data-first architecture: LlamaIndex agents combine Intruder tool responses with indexed documents for comprehensive, grounded answers
Query pipeline framework lets you chain Intruder tool calls with transformations, filters, and re-rankers in a typed pipeline
Multi-source reasoning: agents can query Intruder, a vector store, and a SQL database in a single turn and synthesize results
Observability integrations show exactly what Intruder tools were called, what data was returned, and how it influenced the final answer
Intruder + LlamaIndex Use Cases
Practical scenarios where LlamaIndex combined with the Intruder MCP Server delivers measurable value.
Hybrid search: combine Intruder real-time data with embedded document indexes for answers that are both current and comprehensive
Data enrichment: query Intruder to augment indexed data with live information before generating user-facing responses
Knowledge base agents: build agents that maintain and update knowledge bases by periodically querying Intruder for fresh data
Analytical workflows: chain Intruder queries with LlamaIndex's data connectors to build multi-source analytical reports
Intruder MCP Tools for LlamaIndex (10)
These 10 tools become available when you connect Intruder to LlamaIndex 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 LlamaIndex
Ready-to-use prompts you can give your LlamaIndex 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 LlamaIndex
Common issues when connecting Intruder to LlamaIndex through the Vinkius, and how to resolve them.
BasicMCPClient not found
pip install llama-index-tools-mcpIntruder + LlamaIndex FAQ
Common questions about integrating Intruder MCP Server with LlamaIndex.
How does LlamaIndex connect to MCP servers?
Can I combine MCP tools with vector stores?
Does LlamaIndex support async MCP calls?
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 LlamaIndex
Get your token, paste the configuration, and start using 10 tools in under 2 minutes. No API key management needed.