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Cisco Modeling Labs CML

by xorrkazversion 0.40.0i★ –iRuns on your computer
Registry nameio.github.xorrkaz/cml-mcp

Install

Overview

Description from the maker (original English)

An MCP server that provides access to common Cisco Modeling Labs (CML) operations.

PopNx MCP’s three pillars

These three are never merged into one score: opinions, measurements and popularity are different things.

What you can do with it

We have not written a plain-language summary for this one yet. Below are the facts we read from the registry.

  • Connection: Runs on your computer
  • Transport: stdio
  • Category: Other
  • You need to fill in: CML_URL, CML_USERNAME, CML_PASSWORD, PYATS_PASSWORD, PYATS_AUTH_PASS

Install

Pick the AI app you use, then copy the settings.

Before you install

  • Basic checks: 1 of 1 passed
  • Runs on your computer with your user’s permissions (files, network, apps).
  • You fill in yourself: CML_URL, CML_USERNAME, CML_PASSWORD, PYATS_USERNAME, PYATS_PASSWORD, PYATS_AUTH_PASS

Values marked secret are keys to your account. Never share them or paste them into a chat.

You need

  • PyPIPython’s uv installed (for the uvx command)

Which app do you use?

Pick your app above. We remember it, so next time the button says “Install in …”.

Open Claude Desktop → Settings → Developer → Edit Config, and paste this into claude_desktop_config.json

{
  "mcpServers": {
    "cml": {
      "command": "uvx",
      "args": [
        "cml-mcp"
      ],
      "env": {
        "CML_URL": "your-value",
        "CML_USERNAME": "your-value",
        "CML_PASSWORD": "your-value",
        "PYATS_USERNAME": "your-value",
        "PYATS_PASSWORD": "your-value",
        "PYATS_AUTH_PASS": "your-value"
      }
    }
  }
}

Run this in your terminal

claude mcp add cml --env CML_URL=your-value --env CML_USERNAME=your-value --env CML_PASSWORD=your-value --env PYATS_USERNAME=your-value --env PYATS_PASSWORD=your-value --env PYATS_AUTH_PASS=your-value -- uvx cml-mcp

Fill in the empty values before running it.

Open in Cursor

Or copy the settings yourself

Paste into .cursor/mcp.json in your project, or ~/.cursor/mcp.json

{
  "mcpServers": {
    "cml": {
      "command": "uvx",
      "args": [
        "cml-mcp"
      ],
      "env": {
        "CML_URL": "your-value",
        "CML_USERNAME": "your-value",
        "CML_PASSWORD": "your-value",
        "PYATS_USERNAME": "your-value",
        "PYATS_PASSWORD": "your-value",
        "PYATS_AUTH_PASS": "your-value"
      }
    }
  }
}

Your browser asks to open the app, then the app shows the settings and asks you to confirm. Key values are left empty for you to fill in.

Open in VS Code

Or copy the settings yourself

Paste into .vscode/mcp.json in your project

{
  "servers": {
    "cml": {
      "type": "stdio",
      "command": "uvx",
      "args": [
        "cml-mcp"
      ],
      "env": {
        "CML_URL": "your-value",
        "CML_USERNAME": "your-value",
        "CML_PASSWORD": "your-value",
        "PYATS_USERNAME": "your-value",
        "PYATS_PASSWORD": "your-value",
        "PYATS_AUTH_PASS": "your-value"
      }
    }
  }
}

Your browser asks to open the app, then the app shows the settings and asks you to confirm. Key values are left empty for you to fill in.

This one runs on your computer, and ChatGPT can only connect to servers on the internet. Pick another app.

Your choice stays on this device in a cookie; no account needed.

Values you fill in

  • CML_URL required env
    URL for the CML Server
  • CML_USERNAME required env
    Username for CML authentication
  • CML_PASSWORD secret required env
    Password for CML authentication
  • PYATS_USERNAME env
    Username for authentication to devices running in CML
  • PYATS_PASSWORD secret env
    Password for authentication to devices running in CML
  • PYATS_AUTH_PASS secret env
    Enable password for authentication to devices running in CML

These settings are generated from the maker’s registry entry. If the README says otherwise, follow the README.

What it can do

Runs on your computer; the tool list appears in your AI app after you install it.

Basic checksi

We check information anyone can see; we have not read the code. Checks that do not apply are left out of the count. · Checked Nov 8, 2026

  • ✓ Pass

    Maker matches the repo

    The registry name was verified with the GitHub account xorrkaz, which owns the repo

  • … Not checked yet

    Still maintained

    We have not read this repo from GitHub yet

  • … Not checked yet

    Has a licence

    We have not read this repo from GitHub yet

  • – Not applicable

    Endpoint responds

    This one runs on your computer; there is no internet endpoint

  • – Not applicable

    Sign-in with OAuth

    Runs on your computer and uses local settings instead

  • … Not checked yet

    No hidden instructions in tool descriptions

    Runs on your computer; we can only read tool lists from internet endpoints

Compared with others in Otheri

  • More stars than 0% of the other 18397 servers in this category
  • Published to the registry more recently than 90% of the other 18397 servers in this category
  • Basic checks equal to or better than 100% of the other 18397 servers in this category

Compared with every active server in this category in the registry. Stars count only when the publisher owns the repo.

Common questions

Is Cisco Modeling Labs CML safe?

It passed 1 of 1 applicable basic checks. We have not read the code. Before adding a key or token, see what access the server asks for and use a key with only the permissions you need.

What keys or codes does it need?

You need to fill in: CML_URL, CML_USERNAME, CML_PASSWORD, PYATS_PASSWORD, PYATS_AUTH_PASS

Does it run on my computer or in the cloud?

It runs on your computer. Your AI app starts it when needed, and data does not pass through the maker’s servers (unless it calls an online service itself).

Is it still maintained?

The GitHub repo last changed –, and the latest version (0.40.0) reached the registry 4 days ago.

Which apps can use it?

Apps that support MCP, such as Claude Desktop, Claude Code, Cursor and VS Code. You also need Python (uv) on your computer.

What can I use instead?

In the same category: Spec Driven Development, Remote Desktop Commander, alalanet — check before you pay

Alternatives

Servers in the same category from other makers, sorted by stars.

Reading a card:★ GitHub starsiThree pillars: reviews · checks · usageiUpdated = latest version published to the registryi

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Runs on your computer★ 440MITUpdated 14 months ago
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Remote Desktop Commander

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Remote Desktop Commander: use files, terminal and processes on your own computers from any AI app.

Runs in the cloud★ 211Updated 2 days ago
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README from the maker

Open the README

Copied from the maker’s repo as written. PopNx MCP has not reviewed or endorsed it. HTML, images and scripts are removed. Links lead off this site.

Model Context Protocol (MCP) Server for Cisco Modeling Labs (CML)

mcp-name: io.github.xorrkaz/cml-mcp

Overview

cml-mcp brings the power of AI assistants to your network lab! This tool allows you to interact with Cisco Modeling Labs (CML) using natural language through AI applications like Claude Desktop, Claude Code, and Cursor.

Instead of clicking through menus or writing scripts, simply tell the AI what you want to do in plain English—like "Create a new lab with two routers and configure OSPF" or "Show me the running config on Router1"—and watch it happen automatically.

This is accomplished through the Model Context Protocol (MCP), a standard way for AI applications to interact with external tools and services. Think of it as giving your AI assistant a direct connection to your CML server.

Features

  • Create Lab Topologies: Tools to create new labs and define network topologies from scratch or using full topology definitions.
  • Query Status: Tools to retrieve detailed status information for labs, nodes, links, annotations, and the CML server itself.
  • Control Labs and Nodes: Tools to start, stop, and wipe labs or individual nodes as needed.
  • Manage CML Users and Groups: Tools to list, create, and delete local users and groups (requires admin privileges).
  • Visual Annotations: Add visual elements (text, rectangles, ellipses, lines) to lab topologies for documentation and organization.
  • Link Management: Connect nodes, configure link conditioning (bandwidth, latency, jitter, loss), and control link states.
  • Packet Capture: Start, stop, and retrieve packet captures (PCAP) from network links for traffic analysis with Wireshark or other tools.
  • Node Configuration: Configure node startup configurations and send CLI commands to running devices.
  • Run Commands on Devices: Using PyATS, MCP clients can execute commands on virtual devices within CML labs.
  • Console Log Access: Retrieve console logs from running nodes for troubleshooting and monitoring, with support for selecting specific serial console ports.
  • Modular Architecture: Tools are organized into logical modules (labs, nodes, links, pcap, etc.) for maintainability and extensibility.
  • Access Control Lists (HTTP Mode): When running in HTTP transport mode, you can restrict which users can access which tools using a YAML-based ACL configuration file.
  • Observability: Optional OpenTelemetry tracing exports spans for every tool call to any OTLP-compatible backend (Jaeger, Grafana Tempo, Datadog, etc.).

Quick Start

Installation

The easiest way to get started is using uvx with Claude Desktop (or other MCP-compatible clients). The uvx tool automatically downloads and runs the server without manual installation steps.

Configuration: Find and edit your Claude Desktop configuration file (claude_desktop_config.json). Add the following:

{

"mcpServers": { "Cisco Modeling Labs CML": { "type": "stdio", "command": "uvx", "args": [ "cml-mcp" ], "env": { "CML_URL": "{CML_URL}", "CML_USERNAME": "{CML_USERNAME}", "CML_PASSWORD": "{CML_PASSWORD}!", "CML_VERIFY_SSL": "true" } } } }

Important: Replace the placeholder values with your actual CML server details:

  • CML_URL: Your CML server address (e.g., https://cml.example.com or https://10.10.20.50)
  • CML_USERNAME and CML_PASSWORD: Your CML login credentials
  • CML_VERIFY_SSL: TLS certificate verification now defaults to "true". CML ships with a self-signed certificate out of the box, so most users need to set this to `"false"`. Leave it at "true" only if you have installed a CA-signed certificate on your CML server (or point CA_BUNDLE at a file containing your self-signed certificate).

[!TIP]

"Command not found" for `uvx`? MCP clients like Claude Desktop run in a restricted environment that does not always inherit your shell's PATH. If uvx can't be found, use its full path in the "command" field. To find it, run which uvx in a terminal on macOS/Linux, or where uvx in Command Prompt on Windows (e.g., "/Users/alice/.local/bin/uvx" on macOS, "C:\Users\alice\.local\bin\uvx.exe" on Windows). The same applies to uv, npx, or any other command used in MCP configurations.

Need more capabilities?

  • For device CLI command execution, use cml-mcp[pyats] instead of cml-mcp in the args
  • For Docker, Windows (WSL), or HTTP server mode, see INSTALLATION.md

Where to find your configuration file:

  • macOS: ~/Library/Application Support/Claude/claude_desktop_config.json
  • Windows: %APPDATA%\Claude\claude_desktop_config.json
  • Linux: ~/.config/Claude/claude_desktop_config.json
Requirements
  • Python 3.12, 3.13, or 3.14
  • Cisco Modeling Labs (CML) 2.9 or later
  • [uv](https://docs.astral.sh/uv/) - Python package manager

Available MCP Tools

The server provides 52 MCP tools organized into the following categories:

Lab Management
  • get_cml_labs - Retrieve labs for a specific user or current user
  • create_empty_lab - Create a new empty lab with optional metadata
  • create_full_lab_topology - Create a complete lab from a topology definition
  • modify_cml_lab - Update lab properties (title, description, notes)
  • set_cml_lab_permissions - Configure group/user access (LAB_ADMIN, LAB_EDIT, LAB_EXEC, LAB_VIEW)
  • start_cml_lab - Start all nodes in a lab
  • stop_cml_lab - Stop all nodes in a lab
  • wipe_cml_lab - Wipe all node data/configurations (prompts for confirmation if client supports it)
  • delete_cml_lab - Delete a lab (prompts for confirmation if client supports it)
  • get_cml_lab_by_title - Find a lab by its title
  • download_lab_topology - Download lab topology as YAML file
  • clone_cml_lab - Clone a lab with optional new title
Node Management
  • get_cml_node_definitions - List available node types
  • get_node_definition_detail - Get detailed info about a specific node type
  • add_node_to_cml_lab - Add a node to a lab
  • get_nodes_for_cml_lab - Get all nodes in a lab with operational data
  • configure_cml_node - Set node startup configuration
  • start_cml_node - Start a specific node
  • stop_cml_node - Stop a specific node
  • wipe_cml_node - Wipe node data (prompts for confirmation if client supports it)
  • delete_cml_node - Delete a node (prompts for confirmation if client supports it)
  • get_console_log - Get console output history for a node; optional console index selects the serial port (default 0; Docker-based nodes often use both 0 and 1)
  • send_cli_command - Execute exec/operational-mode CLI commands on running nodes (requires PyATS); optional console index selects which serial port to use
  • send_cli_config_command - Execute configuration-mode CLI commands on running nodes (requires PyATS); optional console index selects which serial port to use
Interface & Link Management
  • add_interface_to_node - Add an interface to a node. Returns a list of created interfaces (a single slot request may add multiple interfaces depending on the node type)
  • get_interfaces_for_node - Get all interfaces for a node
  • connect_two_nodes - Create a link between two interfaces
  • get_all_links_for_lab - Get all links in a lab
  • apply_link_conditioning - Configure network conditions (bandwidth, latency, jitter, loss)
  • start_cml_link - Enable connectivity on a link
  • stop_cml_link - Disable connectivity on a link
Annotations (Visual Elements)
  • get_annotations_for_cml_lab - Get all visual annotations in a lab
  • add_text_annotation - Add a text annotation
  • add_rectangle_annotation - Add a rectangle annotation
  • add_ellipse_annotation - Add an ellipse annotation
  • add_line_annotation - Add a line annotation
  • delete_annotation_from_lab - Delete an annotation (prompts for confirmation if client supports it)
Packet Capture (PCAP)
  • start_packet_capture - Start capturing packets on a link
  • stop_packet_capture - Stop an active packet capture
  • check_packet_capture_status - Check capture status and packet count
  • get_captured_packet_overview - Get summary of captured packets
  • get_packet_capture_data - Download full PCAP file (base64-encoded for Wireshark/tcpdump)
User & Group Management
  • get_cml_users - List all CML users
  • create_cml_user - Create a new user (requires admin)
  • delete_cml_user - Delete a user (requires admin, prompts for confirmation if client supports it)
  • get_cml_groups - List all CML groups
  • create_cml_group - Create a new group (requires admin)
  • delete_cml_group - Delete a group (requires admin, prompts for confirmation if client supports it)
System Information
  • get_cml_information - Get CML server version and configuration
  • get_cml_status - Get system health indicators
  • get_cml_statistics - Get resource usage and lab/node/link counts
  • get_cml_licensing_details - Get licensing information and limits

Usage

Once configured, restart your MCP client (e.g., Claude Desktop) and start chatting! The AI assistant now has direct access to your CML server and can help you build and manage network labs through natural conversation.

What Can You Do?

Here are some example prompts to try:

Getting Started:

  • "Show me all my CML labs"
  • "What node types are available in CML?"
  • "Tell me about my CML server status and licensing"

Building Labs:

  • "Create a new lab called 'OSPF Test Lab'"
  • "Add two CSR1000v routers and an external connector to my lab"
  • "Connect Router1's GigabitEthernet1 to Router2's GigabitEthernet1"

Configuration & Testing:

  • "Configure OSPF area 0 on both routers"
  • "Start all nodes in the lab"
  • "Show me the OSPF neighbors on Router1"
  • "Start a packet capture on the link between the routers"

Complete Workflow Example:

Here's a sequence of prompts that demonstrates building and testing a complete lab:

  1. "Create a new CML lab called 'My Network Lab'"
  2. "Add two IOL routers, an unmanaged switch, and an external connector to this lab"
  3. "Connect the two IOL routers to the unmanaged switch and connect the switch to the external connector"
  4. "Configure the routers so that their connected interfaces have IPs in the 192.0.2.0/24 subnet and configure OSPF on them"
  5. "Start the lab and validate that OSPF is working correctly"
  6. "Add a green box annotation around the two IOL routers with the label 'OSPF Area 0'"

Here's a demo showing it working in Claude Desktop:

![Animated demonstration showing Claude Desktop creating a network topology in Cisco Modeling Labs through natural language commands. The sequence shows a user typing prompts to create a lab, add network devices including

Only the beginning is shown; read the rest in the repo

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