Tele-LLM-Hub: Building Context-Aware Multi-Agent LLM Systems for Telecom Networks

Pranshav Gajjar, Cong Shen, Vijay K Shah

Keywords: AI, LLM, MCP, 5G, Telecom

Abstract: This paper introduces Tele-LLM-Hub, a user friendly low-code solution for rapid prototyping and deployment of context aware multi-agent (MA) Large Language Model (LLM) systems tailored for 5G and beyond. As telecom wireless networks become increasingly complex, intelligent LLM applications must share a domain-specific understanding of network state. We propose TeleMCP, the Telecom Model Context Protocol, to enable structured and context-rich communication between agents in telecom environments. Tele-LLM-Hub actualizes TeleMCP through a low-code interface that supports agent creation, workflow composition, and interaction with software stacks such as srsRAN. Key components include a direct chat interface, a repository of pre-built systems, an Agent Maker leveraging fine-tuning with our RANSTRUCT framework, and an MA-Maker for composing MA workflows. The goal of Tele-LLM-Hub is to democratize the design of context-aware MA systems and accelerate innovation in next-generation wireless networks.

Submission Number: 64