Enable intelligent insights with Red Hat Satellite MCP Server

Enable intelligent insights with Red Hat Satellite MCP Server Instructions Configure a Foreman token in Satellite Install and run the MCP server Configure your chat client Install Ollama Pull a model Install Goose CLI First step towards autonomous troubleshooting Get started with AI for enterprise: A beginner’s guide About the author Matthew Yee More like this AI quickstart: Protecting inference with F5 Distributed Cloud and Red Hat AI Scaling Enterprise Federated AI with Flower and Open Cluster Management Technically Speaking | Build a production-ready AI toolbox Technically Speaking | Platform engineering for AI agents Keep exploring Browse by channel Automation Artificial intelligence Open hybrid cloud Security Edge computing Infrastructure Applications Virtualization Share Red Hat Satellite manages Red Hat Enterprise Linux (RHEL) systems at scale across the cloud and on-premises. Last year, a model context protocol (MCP) server for Red Hat Satellite was released as a Technology Preview feature to enable more intelligent and automated management of Satellite and RHEL systems through your favourite large language model (LLM). LLMs make it possible to perform highly automated and sophisticated tasks. An LLM can enable automatic, unsupervised problem solving, simulating the acts of perception, learning, and reasoning. Tools such as MCPs make it possible for LLMs to orchestrate operations on systems, using specialized domains of knowledge. MCP enables an LLM to incorporate natural language context. Specifically, an MCP server provides specialized knowledge specific to an operating system, helping an LLM offer more relevant information about your systems. The MCP server for Red Hat Satellite adds value by integrating Satellite-specific data with LLMs. It provides API tools that enable LLMs to query the Satellite database for information regarding the RHEL systems under its management. The combination of these three tools enables systems administrators to use natural language to perform specialized tasks to manage a RHEL environment such as identifying and troubleshooting problems with your systems. This blog demonstrates how to set up and use the MCP server for Red Hat Satellite with Goose CLI (an LLM chat client) and Ollama (LLM model management). To try the demonstration yourself, you must have a properly installed and configured Satellite 6.18 server.