Drag, Drop, and Deploy: Low-Code AI Agents for Network Ops

Network operations still depend heavily on manual workflows. Engineers move between CLIs, dashboards, and scripts to answer operational questions, validate configurations, and enforce compliance across diverse network platforms. These tasks are repetitive, error-prone, and hard to scale.

This talk presents a practical AgenticOps architecture for network operations built with open source tools. It shows how low-code visual orchestration can be combined with LLM-based reasoning to automate both interactive and scheduled tasks while preserving native CLI access.

The system uses n8n for workflow orchestration, Model Context Protocol servers written in Python with FastMCP to expose network capabilities, and Cisco pyATS to execute platform-aware CLI commands across multiple device families. Operators interact through a chat interface using natural language. The LLM classifies intent, discovers device type, selects the correct commands, executes them via pyATS, and returns structured results.

The same workflows also handle automated compliance checks, report generation, and scheduled validations. The session includes a live demonstration and a GitHub repository with MCP servers, n8n workflows, and deployment examples ready to adapt to real environments.