mcp-redfish
Overview
The mcp-redfish server is a Model Context Protocol (MCP) server that enables AI assistants and agents to interact directly with systems that expose the Redfish API, the industry-standard RESTful interface for out-of-band hardware management. It allows AI-driven workflows to inspect server hardware, firmware, power state, and health information without switching tools or manually navigating vendor-specific management consoles.
This server is especially useful for data center operations, hardware monitoring, infrastructure troubleshooting, and AI-assisted systems management workflows.
Transport
stdio
Tools
Key Capabilities
- Hardware visibility — Explore servers, chassis, components, and management controllers programmatically.
- Health and status insight — Retrieve power, thermal, and overall system health information.
- Vendor-neutral management — Work across Redfish-compatible hardware regardless of manufacturer.
- Out-of-band operations context — Reason about infrastructure state independently of the host OS.
- Operational decision support — Enable AI assistants to answer questions like “is this server healthy?” or “what hardware is installed?”
How It Works
The mcp-redfish server runs as an MCP service and connects to Redfish-enabled management endpoints using configured credentials and connection details. AI clients communicate with the server over the MCP protocol to request hardware and management context as part of broader reasoning workflows.
The server mediates access to the Redfish API, handling authentication, request execution, and response normalization. Results are returned in structured formats that AI assistants can reason over directly, while respecting the permissions and capabilities exposed by the underlying management controller.
By exposing Redfish through MCP, the server enables AI-driven workflows such as hardware inventory analysis, health checks, and infrastructure troubleshooting — bringing physical systems management into the same AI-assisted workflows used for cloud, Kubernetes, and application-level operations.