Mplify's Kylie SDK Aims to Bridge AI and Autonomous Networks

LOS ANGELES, CA – March 24, 2026 – Mplify Alliance today announced a significant step toward the long-sought goal of autonomous networking with the launch of its Kylie SDK release. The new software development kit introduces critical support for the Model Context Protocol (MCP) across its widely adopted Lifecycle Service Orchestration (LSO) APIs, creating a standardized bridge for artificial intelligence agents to directly interact with and control complex network infrastructure.

This release is designed to empower service providers to automate, monetize, and scale their digital services in an increasingly interconnected and AI-driven global ecosystem. By translating standardized LSO APIs into an AI-ready framework, Mplify aims to enable intelligent automation across multi-domain and multi-provider environments, addressing a key bottleneck that has historically slowed innovation.

“This release marks an important milestone in Mplify's mission to simplify collaboration across network, cloud, and cybersecurity ecosystems,” said Pascal Menezes, CTO of Mplify. “By combining standardized LSO APIs with MCP support, Mplify enables AI agents and large language models (LLMs) to interact more directly with networking infrastructure, helping providers reduce service complexity, accelerate decision-making, and move closer to autonomous operations.”

Unlocking Network Control for AI

The core innovation of the Kylie SDK is the integration of the Model Context Protocol. MCP functions as a crucial translation layer, allowing AI agents to safely discover and use tools, data, and network resources by understanding their meaning and context, rather than just interacting with raw API endpoints. This enables developers to describe their intent in natural language, which MCP then translates into structured, precise actions for the network to execute.

This integration is realized through several key features in the Kylie release:

• AI-Native LSO APIs: Full MCP support is now embedded across the entire LSO portfolio, enabling seamless integration with advanced AI-driven orchestration and diagnostic tools.
• Streamlined Business and Operations: The release includes updated LSO Business APIs (Sonata and Cantata) to automate inter-provider processes like quoting and ordering, alongside enhanced LSO Operational APIs (Allegro, Interlude, and Legato) for robust service provisioning, performance monitoring, and fault management.
• Standardized Schemas: To ensure interoperability, Mplify has published standardized product schemas for IP and Carrier Ethernet, which support a wide range of product, service, and operational payloads.

A major highlight is the new LSO API Blending Tool. This utility allows users to combine LSO APIs with specific product payloads, including not only established standards like Carrier Ethernet but also emerging services such as data center AI exchange cross-connects, CAMARA Quality on Demand, and SD-WAN. The tool can automatically generate Mplify MCP servers with full payload support, creating a seamless, end-to-end conversion from high-level AI commands into executable LSO API calls. This dramatically reduces integration complexity for service providers looking to deploy AI-enabled operations.

Addressing Industry Challenges and Driving Value

For service providers, the Kylie SDK arrives at a critical time. The industry has long struggled with a widening automation gap, where the complexity of 5G, IoT, and distributed AI workloads has outpaced the ability to manage networks efficiently. Many providers still rely on fragmented systems, proprietary APIs, and manual processes, which are unsustainable in an era demanding real-time, on-demand services.

By championing a standardized, automated interface between enterprises and service providers, Mplify's LSO framework aims to replace these inefficient digital workflows. The integration of MCP is the next logical step, specifically addressing the need for networks to become active, intelligent participants in service delivery rather than passive transport layers. This move is essential for realizing the full potential of Network-as-a-Service (NaaS), a model that promises cloud-like agility for network resources.

While Mplify faces a competitive landscape with major players like Amdocs, Ciena's Blue Planet, and Nokia all offering sophisticated AI and network automation platforms, its strategic advantage lies in its role as a global standardization body. By defining the blueprint for interoperability, Mplify enables a cohesive ecosystem where services can be orchestrated across different vendors and network domains without friction, a key differentiator that competitors building proprietary solutions cannot easily match.

A Blueprint for the Autonomous Future

The Kylie release is not an endpoint but a foundational component of Mplify's ambitious roadmap toward fully autonomous networking. The alliance has already showcased the potential of this technology at MWC26 Barcelona, where it collaborated with Colt Technology Services, Orange, and Google Cloud to demonstrate how agentic AI, combined with standardized APIs, can enable closed-loop orchestration for use cases like connected vehicles.

The next major milestone is the Lana release, scheduled for late 2026, which promises to introduce an expanded set of AI-driven assets and capabilities across the LSO ecosystem. This forward-looking strategy is built on the vision of creating networks for AI, not just using AI for networks.

Mplify's long-term vision positions the network as a cognitive platform and a foundational coordination layer for the coming era of agentic AI, where swarms of intelligent agents collaborate to orchestrate complex workflows. This future requires a secure, automated, and programmable infrastructure that can deliver high performance at scale. The standardization work being done today with releases like Kylie is laying the critical groundwork for that AI-native future, ensuring the underlying network infrastructure can keep pace with the rapid evolution of artificial intelligence.