network-mcp

Give AI direct access to your network devices. 35 MCP tools, multi-vendor, one interface.

Stop writing Netmiko scripts. Connect Claude, ChatGPT, or any MCP-compatible AI to your routers, switches, and firewalls — and let it run show commands, check health, calculate subnets, discover topology, and manage configs through natural language.

You: "Check the health of all my devices"
Claude: [calls health_check_all] → 6 devices healthy, Switch-R2 has 2 interfaces down

What is this?

An MCP (Model Context Protocol) server that gives AI assistants real-time access to network devices. Built for network engineers who want to automate without writing boilerplate.

Supported platforms:

• Cisco IOS-XE (routers, switches)
• Nokia SR Linux
• FRRouting (FRR)
• Juniper Junos
• Aruba AOS-CX
• Linux hosts

Quick Start

1. Install

git clone https://github.com/E-Conners-Lab/MCP-DEMO-LAB.git
cd network-mcp
python -m venv .venv && source .venv/bin/activate
pip install -r requirements.txt

2. Configure devices

cp .env.example .env
# Edit .env with your device IPs and credentials

3. Try it instantly (no lab required)

# Demo mode returns realistic mock data — no devices needed
DEMO_MODE=true python network_mcp_server.py

4. Connect to Claude Desktop

Add to ~/Library/Application Support/Claude/claude_desktop_config.json:

{
  "mcpServers": {
    "network": {
      "command": "/path/to/network-mcp/.venv/bin/python",
      "args": ["/path/to/network-mcp/network_mcp_server.py"]
    }
  }
}

Restart Claude Desktop. You now have 35 network tools available.

5. Try with a real lab (5 minutes)

# Spin up 2 FRR routers with containerlab
cd quickstart && sudo containerlab deploy -t topology.clab.yml

Tools

Device Operations

Network Intelligence

Calculators (no devices needed)