Skip to main content
ClaudeWave

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

MCP ServersRegistry oficial70 estrellas42 forksPythonBSD-2-ClauseActualizado today
ClaudeWave Trust Score
100/100
Verified
Passed
  • Open-source license (BSD-2-Clause)
  • Actively maintained (<30d)
  • Clear description
  • Topics declared
  • Mature repo (>1y old)
  • Documented (README)
Last scanned: 8/27/2026
Install in Claude Code / Claude Desktop
Method: UVX (Python) · cml-mcp
Claude Code CLI
claude mcp add cml-mcp -- uvx cml-mcp
claude_desktop_config.json (Claude Desktop)
{
  "mcpServers": {
    "cml-mcp": {
      "command": "uvx",
      "args": ["cml-mcp"]
    }
  }
}
1. Run the command above in your terminal (Claude Code), or paste the JSON config into claude_desktop_config.json (Claude Desktop).
2. Replace any <placeholder> values with your API keys or paths.
3. Restart Claude. The MCP server and its tools appear automatically.
💡 Package name inferred from the repository name. Verify it exists on PyPI, or clone https://github.com/xorrkaz/cml-mcp and follow its README.
Casos de uso

Resumen de MCP Servers

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

[![MCP Toplist](https://mcptoplist.com/badge/io.github.xorrkaz%2Fcml-mcp.svg)](https://mcptoplist.com/server/io.github.xorrkaz%2Fcml-mcp)

[![Ask DeepWiki](https://deepwiki.com/badge.svg)](https://deepwiki.com/xorrkaz/cml-mcp)

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)](https://www.cisco.com/c/en/us/products/cloud-systems-management/modeling-labs/index.html) 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)](https://modelcontextprotocol.io/docs/getting-started/intro), 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](https://developer.cisco.com/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.

## 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:

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

**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"`** (as shown above). 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](https://github.com/xorrkaz/cml-mcp/blob/main/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 51 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 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 Deskt
cisco-modeling-labscmlmcp-server

Lo que la gente pregunta sobre cml-mcp

¿Qué es xorrkaz/cml-mcp?

+

xorrkaz/cml-mcp es mcp servers para el ecosistema de Claude AI. A Model Context Protocol (MCP) Server for Cisco Modeling Labs (CML) Tiene 70 estrellas en GitHub y su última actualización registrada es del 2026-08-26.

¿Cómo se instala cml-mcp?

+

Puedes instalar cml-mcp clonando el repositorio (https://github.com/xorrkaz/cml-mcp) o siguiendo las instrucciones del README en GitHub. ClaudeWave también te ofrece bloques de instalación rápida en esta misma página.

¿Es seguro usar xorrkaz/cml-mcp?

+

Nuestro agente de seguridad ha analizado xorrkaz/cml-mcp y le ha asignado un Trust Score de 100/100 (tier: Verified). Revisa el desglose completo de comprobaciones superadas y flags en esta página.

¿Quién mantiene xorrkaz/cml-mcp?

+

xorrkaz/cml-mcp es mantenido por xorrkaz. La última actividad registrada en GitHub es del 2026-08-26, con 1 issues abiertos.

¿Hay alternativas a cml-mcp?

+

Sí. En ClaudeWave puedes explorar mcp servers similares en /categories/mcp, ordenados por popularidad o actividad reciente.

Despliega cml-mcp en tu cloud

Lleva este repo a producción en minutos. Cada plataforma genera su propio entorno con variables de entorno editables.

¿Mantienes este repo? Añade un badge a tu README

Pega el badge en tu README de GitHub para mostrar que está auditado por ClaudeWave. Cada badge enlaza de vuelta a esta página y muestra el Trust Score actual.

Featured on ClaudeWave: xorrkaz/cml-mcp
[![Featured on ClaudeWave](https://claudewave.com/api/badge/xorrkaz-cml-mcp)](https://claudewave.com/repo/xorrkaz-cml-mcp)
<a href="https://claudewave.com/repo/xorrkaz-cml-mcp"><img src="https://claudewave.com/api/badge/xorrkaz-cml-mcp" alt="Featured on ClaudeWave: xorrkaz/cml-mcp" width="320" height="64" /></a>

Más MCP Servers

Alternativas a cml-mcp