packt-netops-ai-workshop

🔧 Build Intelligent Networks with AI

Installation

Run this command in your terminal to add the MCP server to Claude Code.

Run in terminal:

Command

claude mcp add --transport stdio wcollins-packt-netops-ai-workshop node server.js \
  --env MCP_PORT="3000" \
  --env MCP_LOG_LEVEL="info" \
  --env MCP_BIND_ADDRESS="0.0.0.0"

How to use

This MCP server enables natural language-driven automation for network operations by exposing an interface that can interpret user intents and translate them into actionable automation tasks. It integrates with Ansible playbooks for network provisioning and configuration, leverages Claude Code for rapid playbook authoring, and can orchestrate AI-powered workflows for proactive monitoring and alerts using Prometheus/Grafana tooling. Users can issue natural language requests to create, run, or modify automation tasks (for example, adding a VLAN or deploying a monitoring check), and the MCP server will invoke the appropriate Ansible playbooks behind the scenes. The toolkit supports building agentic workflows that autonomously respond to conditions detected by monitoring, while allowing operators to review and customize steps as needed.

How to install

Prerequisites:

Node.js (14.x or newer) and npm installed on your system
Git to clone the repository

Installation steps:

Clone the repository: git clone https://github.com/your-org/packt-netops-ai-workshop.git cd packt-netops-ai-workshop
Install dependencies: npm install
Run the MCP server: npm run start

or, if no start script is defined, run:

node server.js
Verify the server is running locally on the configured port (default 3000) and accessible at http://localhost:3000

Optional: customize environment variables as needed before starting, such as MCPP_LOG_LEVEL, MCPP_BIND_ADDRESS, and MCPP_PORT.

Additional notes

Notes and tips:

This MCP setup is designed to invoke Ansible playbooks via natural language commands. Ensure any Ansible inventories and playbooks referenced by the automation are accessible from the environment running the MCP server.
If you’re integrating Claude Code or other AI tools, follow their authentication and API usage guidelines as indicated in their respective documentation.
Environment variables like MCP_LOG_LEVEL, MCP_BIND_ADDRESS, and MCP_PORT can help tailor logging and networking behavior for deployment.
For troubleshooting, check the server logs for errors related to command execution, missing playbooks, or Ansible inventory access. Ensure Python and Ansible dependencies used by the playbooks are installed where applicable.
If you deploy via Docker, consider mapping ports and volumes to preserve logs and configuration between restarts.

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