arXiv:2607.05975v1 Announce Type: cross 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.
The development aligns with increasing industry demand for autonomous network management and the maturation of AI agentic capabilities for complex systems.
This demonstration showcases a tangible step towards autonomous network infrastructure, significantly reducing operational costs and improving network resilience for critical digital backbones.
Network operations will evolve from manual or semi-automated processes to self-optimizing and self-healing systems, driven by AI agents.
- · Telecommunications companies
- · Cloud infrastructure providers
- · AI software developers
- · Network equipment vendors
- · Manual network operations teams
- · Legacy network management software vendors
Reduced latency and improved reliability in data transfer, enabling more robust real-time applications.
Accelerated adoption of AI-driven automation across other critical infrastructure sectors due to demonstrated success.
Potential for new network architectures and services that were previously too complex or costly to manage manually.
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Read at arXiv cs.AI