The Linux Foundation’s CAMARA project, an open source community addressing telco industry API interoperability, has announced the release of a new white paper, “In Concert: Bridging AI Systems & Network Infrastructure through MCP: How to Build Network-Aware Intelligent Applications.”
The paper describes how AI applications and agents can integrate with telecom network infrastructure by exposing CAMARA network capabilities to AI systems through the Model Context Protocol (MCP), enabling AI to consume real-time, policy-compliant network context to improve digital experiences and application outcomes.
CAMARA exists to help developers “write once” against operator-agnostic network APIs, reducing fragmentation and enabling consistent access to network capabilities such as Quality on Demand (QoD), Device Location, Edge Discovery, and anti-fraud signals. The new paper outlines how an MCP server can act as a translator, turning CAMARA APIs into MCP “tools” that AI applications can discover and call, which bridges the historical isolation between AI systems and the networks that power modern digital services. By adopting MCP, AI agents gain immediate access to the latest API capabilities as they are released, eliminating the bottleneck of continuous code refactoring. This seamless integration ensures that users always experience the full potential of the technology the moment it becomes available
“AI agents increasingly shape the digital experiences people rely on every day, yet they operate disconnected from network capabilities – intelligence, control, and real-time source of truth,” said Herbert Damker, CAMARA TSC Chair and Lead Architect, Infrastructure Cloud at Deutsche Telekom. “CAMARA and MCP bring AI and network infrastructure into concert, securely and consistently across operators.”
The paper includes practical example scenarios for “network-aware” intelligent applications/agents, including:
Intelligent video streaming with AI-powered quality optimization
Banking fraud prevention using network-verified security context
Local/edge-optimized AI deployment informed by network and edge resource conditions
In addition to the architecture and use cases, the paper outlines CAMARA’s objectives for supporting MCP, which include covering areas such as security guidelines; standardized MCP tooling for CAMARA APIs; and quality requirements and success factors needed for production-grade implementations. The white paper is available for download on the CAMARA website.
Collaboration with the Agentic AI Foundation
The release of this work aligns with a major ecosystem milestone: MCP now lives under the Linux Foundation’s newly formed Agentic AI Foundation (AAIF), a sister initiative that provides neutral, open governance for key agentic AI building blocks. The Linux Foundation announced AAIF on December 9, 2025, with founding project contributions including Anthropic’s MCP, Block’s goose, and OpenAI’s AGENTS.md. AAIF’s launch emphasizes MCP’s role as a broadly adopted standard for connecting AI models to tools, data, and applications, with more than 10,000 published MCP servers cited by the Linux Foundation and Anthropic.
“With MCP now under the Linux Foundation’s Agentic AI Foundation, developers can invest with confidence in an open, vendor-neutral standard,” said Arpit Joshipura, general manager, Networking, Edge and IoT at the Linux Foundation. “CAMARA’s work demonstrates how MCP can unlock powerful new classes of network-aware AI applications.”
“The Agentic AI Foundation calls for trustworthy infrastructure. CAMARA answers that call. As AI shifts from conversation to orchestration, agentic workflows demand synchronization with reality,” said Nick Venezia, CEO and Founder, Centillion.AI, CAMARA End User Council Representative to the TSC. “We provide the contextual lens that allows AI to verify rather than infer, moving from guessing to knowing.”
