Abstract
This demo presents an MCP-enabled agentic AI architecture for autonomous control of vendor-agnostic IPoDWDM networks. We demonstrate live end-to-end lifecycle multi-layer automation and closed-loop control using GNPy and telemetry, validated on a real testbed.
Key Technologies
- MCP (Multi-Channel Processing): Utilizes MCP architecture for intelligent network management.
- GNPy: A tool for network design and analysis that supports multi-layer automation.
- Closed-loop Control: Ensures reliability and efficiency through real-time data feedback.
Results and Applications
The outcomes of this research have been accepted for demo presentation at the European Conference on Optical Communication (ECOC 2026), showcasing the practical application potential of MCP-driven agentic AI in network lifecycle management.
Blogger's Review: This paper presents an innovative application of MCP-driven agentic AI in IPoDWDM networks, offering a solution to automation challenges in complex network environments. Its validation in real-world settings underscores its feasibility and lays the groundwork for future advancements in network automation.