Tenable 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 Tenable 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 Tenable. "
"You have 10 tools available."
),
)
response = await agent.run(
"What tools are available in Tenable?"
)
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 Tenable MCP Server
Connect your Tenable (Tenable.io) environment to any AI agent and bring your enterprise vulnerability management directly into your IDE or chat via natural conversation.
LlamaIndex agents combine Tenable 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.
What you can do
- Scans & Assessments — List configured vulnerability scans, retrieve detailed run analytics, and even manually trigger immediate evaluations
- Asset Intelligence — Browse your entire host and cloud inventory, retrieving deep telemetry like OS fingerprints, IPs, and tags
- Vulnerability Triage — Pinpoint explicit security findings (Workbench) and CVEs affecting specific assets without navigating complex dashboards
- Topology Oversight — See how your network spaces overlap and track organizational logical folders
- Scanner Health — Check the operational status and plugin health of your internal enterprise scanning fleet
The Tenable 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 Tenable to LlamaIndex via MCP
Follow these steps to integrate the Tenable 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 Tenable
Why Use LlamaIndex with the Tenable MCP Server
LlamaIndex provides unique advantages when paired with Tenable through the Model Context Protocol.
Data-first architecture: LlamaIndex agents combine Tenable tool responses with indexed documents for comprehensive, grounded answers
Query pipeline framework lets you chain Tenable tool calls with transformations, filters, and re-rankers in a typed pipeline
Multi-source reasoning: agents can query Tenable, a vector store, and a SQL database in a single turn and synthesize results
Observability integrations show exactly what Tenable tools were called, what data was returned, and how it influenced the final answer
Tenable + LlamaIndex Use Cases
Practical scenarios where LlamaIndex combined with the Tenable MCP Server delivers measurable value.
Hybrid search: combine Tenable real-time data with embedded document indexes for answers that are both current and comprehensive
Data enrichment: query Tenable 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 Tenable for fresh data
Analytical workflows: chain Tenable queries with LlamaIndex's data connectors to build multi-source analytical reports
Tenable MCP Tools for LlamaIndex (10)
These 10 tools become available when you connect Tenable to LlamaIndex via MCP:
get_asset_details
Retrieves detailed metadata, networking, and risk profile for a specific asset
get_asset_vulnerabilities
Retrieves explicit security findings (Workbench) for a specific asset
get_scan_results
Retrieves runtime analytics and vulnerability summaries for a specific scan
launch_scan
Returns the newly created scan run ID. Manually triggers an immediate execution of a configured scan
list_asset_tags
g. "Critical", "Production", "External"). Lists organizational tags mapped to assets
list_assets
Lists host and cloud assets discovered in Tenable.io
list_logical_networks
Lists Tenable logical routing networks
list_scan_folders
g. "My Scans", "PCI Quarters"). Lists operational scan folders
list_scanners
Lists Nessus scanners managed by Tenable.io
list_scans
Lists vulnerability assessment scans from Tenable.io
Example Prompts for Tenable in LlamaIndex
Ready-to-use prompts you can give your LlamaIndex agent to start working with Tenable immediately.
"Find the status and schedule of the 'Weekly PCI Scan'."
"Retrieve all extreme vulnerabilities on asset ID 1383da-xxx."
"Launch the scan with ID a981bf93 immediately."
Troubleshooting Tenable MCP Server with LlamaIndex
Common issues when connecting Tenable to LlamaIndex through the Vinkius, and how to resolve them.
BasicMCPClient not found
pip install llama-index-tools-mcpTenable + LlamaIndex FAQ
Common questions about integrating Tenable 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 Tenable 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 Tenable to LlamaIndex
Get your token, paste the configuration, and start using 10 tools in under 2 minutes. No API key management needed.