PAN-OS MCP Server for LlamaIndex 8 tools — connect in under 2 minutes

Name: PAN-OS
Availability: InStock
Author: Vinkius

docs.llamaindex.ai/en/stable/module_guides/tools/mcp

Built by Vinkius GDPR 8 Tools Framework

LlamaIndex specializes in data-aware AI agents that connect LLMs to structured and unstructured sources. Add PAN-OS as an MCP tool provider through Vinkius and your agents can query, analyze, and act on live data alongside your existing indexes.

Get MCP Server for AI Agents

ASK AI ABOUT THIS MCP SERVER

Open in ChatGPT Open in Claude Open in Perplexity

Vinkius supports streamable HTTP and SSE.

python

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 PAN-OS. "
            "You have 8 tools available."
        ),
    )

    response = await agent.run(
        "What tools are available in PAN-OS?"
    )
    print(response)

asyncio.run(main())

Fully ManagedVinkius Servers

60%Token savings

High SecurityEnterprise-grade

IAMAccess control

EU AI ActCompliant

DLPData protection

V8 IsolateSandboxed

Ed25519Audit chain

<40msKill switch

Stream every event to Splunk, Datadog, or your own webhook in real-time

* 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 PAN-OS MCP Server

Connect PAN-OS to any AI agent via MCP.

How to Connect PAN-OS to LlamaIndex via MCP

Follow these steps to integrate the PAN-OS 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 8 tools from PAN-OS

Why Use LlamaIndex with the PAN-OS MCP Server

LlamaIndex provides unique advantages when paired with PAN-OS through the Model Context Protocol.

Data-first architecture: LlamaIndex agents combine PAN-OS tool responses with indexed documents for comprehensive, grounded answers

Query pipeline framework lets you chain PAN-OS tool calls with transformations, filters, and re-rankers in a typed pipeline

Multi-source reasoning: agents can query PAN-OS, a vector store, and a SQL database in a single turn and synthesize results

Observability integrations show exactly what PAN-OS tools were called, what data was returned, and how it influenced the final answer

PAN-OS + LlamaIndex Use Cases

Practical scenarios where LlamaIndex combined with the PAN-OS MCP Server delivers measurable value.

Hybrid search: combine PAN-OS real-time data with embedded document indexes for answers that are both current and comprehensive

Data enrichment: query PAN-OS 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 PAN-OS for fresh data

Analytical workflows: chain PAN-OS queries with LlamaIndex's data connectors to build multi-source analytical reports

PAN-OS MCP Tools for LlamaIndex (8)

These 8 tools become available when you connect PAN-OS to LlamaIndex via MCP:

commit

This validates the config and activates it. Returns the commit job ID and status. Use this after making configuration changes to activate them. Commit the candidate configuration to running configuration

get_active_sessions

Use this to monitor real-time activity, identify heavy users, or debug connection issues. List all active network sessions on the firewall

get_nat_rules

Use this to audit NAT configurations or troubleshoot connectivity issues. List all NAT rules configured on the firewall

get_pending_changes

Use this to verify if the running configuration matches the candidate configuration before committing. Check if there are uncommitted configuration changes

get_security_rules

Use this to audit firewall policies, review access controls, or analyze rule usage. List all security rules configured on the firewall

get_system_info

Use this to verify firewall health, check software versions, or confirm connectivity. Get system information and status of the PAN-OS firewall

get_threat_logs

Contains source/dest IPs, threat names, severity, actions taken, and PCAP availability. Use this to investigate security incidents or analyze attack vectors. Retrieve recent threat logs from the firewall

get_traffic_logs

Optional limit parameter controls number of logs returned. Use this to analyze traffic patterns, identify blocked connections, or troubleshoot network issues. Retrieve recent traffic logs from the firewall

Troubleshooting PAN-OS MCP Server with LlamaIndex

Common issues when connecting PAN-OS to LlamaIndex through the Vinkius, and how to resolve them.

BasicMCPClient not found

Install: pip install llama-index-tools-mcp

PAN-OS + LlamaIndex FAQ

Common questions about integrating PAN-OS MCP Server with LlamaIndex.

How does LlamaIndex connect to MCP servers?

Use the MCP client adapter to create a connection. LlamaIndex discovers all tools and wraps them as query engine tools compatible with any LlamaIndex agent.

Can I combine MCP tools with vector stores?

Yes. LlamaIndex agents can query PAN-OS tools and vector store indexes in the same turn, combining real-time and embedded data for grounded responses.