Claude-Modeling-Labs MCP Server

A comprehensive, modular toolkit for interacting with Cisco Modeling Labs (CML) through the Model Context Protocol (MCP) interface. This server enables automated lab creation, topology management, device configuration, and network testing for educational and development purposes.

Features

Core Capabilities

Lab Management: Create, start, stop, and delete CML labs
Topology Building: Add routers, switches, and create network links
Device Configuration: Apply and retrieve device configurations
Console Access: Execute commands on network devices
Network Discovery: Inspect lab topologies, nodes, and interfaces

Key Benefits

Modular Architecture: Clean separation of concerns across handlers
Educational Focus: Perfect for networking students and instructors
Automation Ready: Designed for agentic AI tutoring systems
Windows Compatible: Modular design resolves previous Windows compatibility issues

Installation

Prerequisites

Python 3.8 or higher
Access to a Cisco Modeling Labs server
Valid CML credentials

Quick Start

Clone or download this repository
Install dependencies:
pip install -r requirements.txt
Run the MCP server:
python claude_modeling_labs_modular.py

Development Installation

pip install -e .[dev]

Usage

Initialize Connection

# First, initialize the client with your CML server details
initialize_client(
    base_url="https://your-cml-server.com",
    username="your-username", 
    password="your-password",
    verify_ssl=True  # Set to False for self-signed certificates
)

Basic Lab Operations

# Create a new lab
lab = create_lab("My Network Lab", "Learning OSPF routing")

# Create network devices  
router1 = create_router(lab["lab_id"], "R1", x=100, y=100)
router2 = create_router(lab["lab_id"], "R2", x=300, y=100) 
switch1 = create_switch(lab["lab_id"], "SW1", x=200, y=200)

# Connect devices
link_nodes(lab["lab_id"], router1["node_id"], router2["node_id"])
link_nodes(lab["lab_id"], router1["node_id"], switch1["node_id"])

# Start the lab
start_lab(lab["lab_id"])
wait_for_lab_nodes(lab["lab_id"], timeout=120)

Device Configuration

# Apply configuration to a router
ospf_config = """
hostname Router1
interface GigabitEthernet0/0
 ip address 10.1.1.1 255.255.255.0
 no shutdown
router ospf 1
 network 10.1.1.0 0.0.0.255 area 0
"""
configure_node(lab["lab_id"], router1["node_id"], ospf_config)

# Retrieve current configuration
current_config = get_node_config(lab["lab_id"], router1["node_id"])

Console Commands

# Execute commands on devices
send_console_command(lab["lab_id"], router1["node_id"], "show ip route")
check_interfaces(lab["lab_id"], router1["node_id"])

# Send multiple commands
commands = [
    "show version",
    "show ip interface brief", 
    "show running-config"
]
send_multiple_commands(lab["lab_id"], router1["node_id"], commands)

Architecture

The modular design separates functionality into focused handlers:

src/
├── client/           # CML API authentication and HTTP client
├── handlers/         # Modular tool handlers
│   ├── lab_management.py    # Lab CRUD operations
│   ├── topology.py          # Node and link management  
│   ├── configuration.py     # Device configuration
│   └── console.py           # Console session management
├── utils/            # Common utilities and helpers
└── server.py         # Main MCP server entry point

Key Design Principles

Separation of Concerns: Each handler focuses on one aspect of CML management
Clean Dependencies: Minimal coupling between modules
Error Handling: Consistent error handling across all operations
Windows Compatibility: Modular structure avoids file size limitations

Available Tools

Lab Management

initialize_client() - Authenticate with CML server
list_labs() - List all available labs
create_lab() - Create a new lab
get_lab_details() - Get detailed lab information
delete_lab() - Delete a lab
start_lab() - Start lab execution
stop_lab() - Stop lab execution
wait_for_lab_nodes() - Wait for nodes to initialize
list_node_definitions() - List available device types

Topology Management

get_lab_nodes() - List nodes in a lab
add_node() - Add a device to a lab
create_router() - Create a router (iosv)
create_switch() - Create a switch (iosvl2)
get_node_interfaces() - List node interfaces
get_physical_interfaces() - Get physical interfaces only
create_interface() - Create new interface on a node
get_lab_links() - List all links in a lab
create_link_v3() - Create link between specific interfaces
link_nodes() - Automatically link two nodes
delete_link() - Remove a link
get_lab_topology() - Get complete topology summary

Configuration Management

configure_node() - Apply configuration to a device
get_node_config() - Retrieve device configuration

Console Operations

open_console_session() - Open console access to device
close_console_session() - Close console session
send_console_command() - Execute single command
send_multiple_commands() - Execute multiple commands
check_interfaces() - Check interface status
get_diagnostic_recommendations() - Get troubleshooting suggestions

Educational Use Cases

This toolkit is designed to support networking education through:

Automated Lab Creation

Dynamic topology generation based on learning objectives
Pre-configured scenarios for specific networking concepts
Rapid iteration and experimentation

AI-Powered Tutoring

Agentic systems can create custom labs for individual students
Real-time guidance and troubleshooting assistance
Adaptive learning paths based on student progress

Curriculum Integration

Support for various networking topics (OSPF, BGP, VLAN, STP, etc.)
Scalable from basic connectivity to complex enterprise scenarios
Integration with existing learning management systems

Contributing

This project follows a modular architecture to support easy extension and maintenance:

Adding New Tools: Create new functions in the appropriate handler module
New Handler Categories: Add new handler files and register them in server.py
Testing: Each module can be tested independently
Documentation: Update both code comments and this README

License

MIT License - see LICENSE file for details.

Support

For issues, questions, or contributions, please refer to the project repository or documentation.

Version: 2.0.0
Authors: Claude AI Assistant
Purpose: Educational networking automation and AI-powered tutoring

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A comprehensive toolkit that enables automated interaction with Cisco Modeling Labs (CML) for creating network topologies, configuring devices, and managing lab environments.

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