Redfish

Redfish MCP Server

The Redfish MCP Server is a natural‑language interface that turns any Redfish‑enabled infrastructure into an AI‑friendly data source. By wrapping the official Python Redfish library, it exposes a rich set of tools and queries that let agents ask questions such as “List the available infrastructure components” or “Get the data of ethernet interfaces of component X”. The server removes the need for developers to write custom Redfish clients or parse JSON responses manually, enabling a seamless dialogue between an AI assistant and the underlying hardware.

Why It Matters

Managing data center resources—servers, storage arrays, network switches, and sensors—is traditionally a manual, code‑heavy process. The Redfish MCP Server solves this by providing an MCP‑compatible API that translates natural language into precise Redfish calls. Developers can therefore integrate hardware monitoring, configuration, and troubleshooting directly into AI‑driven workflows without learning the intricacies of Redfish. This accelerates automation, reduces operational overhead, and opens the door to intelligent agents that can proactively maintain infrastructure health.

Core Features

• Natural Language Queries – Agents send plain‑English prompts; the server interprets them into Redfish requests, returning structured JSON that can be consumed by downstream tools or displayed to users.
• Full Redfish Coverage – Every entity exposed by the Redfish specification—Systems, Chassis, EthernetInterfaces, Power supplies, etc.—is accessible through the server’s tool set.
• Dynamic Endpoint Discovery – Optional automatic discovery keeps the list of managed hosts current, eliminating manual reconfiguration when new hardware appears or disappears.
• MCP‑Ready Transport – The server supports standard MCP transports (stdio, SSE, streamable HTTP), allowing it to run as a local service or be exposed over the network.
• Secure, Configurable Authentication – Supports both Basic and Session authentication with optional TLS CA verification, making it suitable for production environments.

Use Cases

1. Infrastructure Health Dashboards – An AI assistant can pull real‑time sensor data and surface alerts in a conversational UI.
2. Automated Remediation – Agents can issue commands to reboot or reset components when thresholds are breached, all via natural language.
3. Capacity Planning – Query current resource utilization across multiple hosts and generate recommendations for scaling.
4. Compliance Auditing – Retrieve configuration snapshots of all managed devices and compare them against policy baselines.

Integration with AI Workflows

Because the server adheres to MCP, any client that understands the protocol—Claude, GPT‑4o, or custom agents—can invoke its tools with a single function call. The natural language layer means developers can prototype new capabilities by writing high‑level prompts, while the underlying Redfish wrapper ensures reliable, typed interactions with physical hardware. This tight coupling reduces the cognitive load on developers and accelerates the delivery of intelligent, infrastructure‑aware applications.