Redfish MCP Server

Overview

The Redfish MCP Server is a natural language interface designed for agentic applications to efficiently manage infrastructure that exposes Redfish API for this purpose. It integrates seamlessly with MCP (Model Content Protocol) clients, enabling AI-driven workflows to interact with structured and unstructured data of the infrastructure. Using this MCP Server, you can ask questions like:

• "List the available infrastructure components"
• "Get the data of ethernet interfaces of the infrastructure component X"

Features

• Natural Language Queries: Enables AI agents to query the data of infrastrcuture components using natural language.
• Seamless MCP Integration: Works with any MCP client for smooth communication.
• Full Redfish Support: It wraps the Python Redfish library

Tools

This MCP Server provides tools to manage the data of infrastructure via the Redfish API.

• list_endpoints to query the Redfish API endpoints that are configured for the MCP Server.
• get_resource_data to read the data of a specific resource (e.g. System, EthernetInterface, etc.)

Installation

Follow these instructions to install the server.

# Clone the repository
git clone 
cd mcp-redfish

# Install dependencies using uv
uv venv
source .venv/bin/activate
uv sync

Configuration

The Redfish MCP Server uses environment variables for configuration. The server includes comprehensive validation to ensure all settings are properly configured.

Environment Variables

Name	Description	Default Value	Required
REDFISH_HOSTS	JSON array of Redfish endpoint configurations	[{"address":"127.0.0.1"}]	Yes
REDFISH_PORT	Default port for Redfish API (used when not specified per-host)	443	No
REDFISH_AUTH_METHOD	Authentication method: basic or session	session	No
REDFISH_USERNAME	Default username for authentication	""	No
REDFISH_PASSWORD	Default password for authentication	""	No
REDFISH_SERVER_CA_CERT	Path to CA certificate for server verification	None	No
REDFISH_DISCOVERY_ENABLED	Enable automatic endpoint discovery	false	No
REDFISH_DISCOVERY_INTERVAL	Discovery interval in seconds	30	No
MCP_TRANSPORT	Transport method: stdio, sse, or streamable-http	stdio	No
MCP_REDFISH_LOG_LEVEL	Logging level: DEBUG, INFO, WARNING, ERROR, CRITICAL	INFO	No

REDFISH_HOSTS Configuration

The REDFISH_HOSTS environment variable accepts a JSON array of endpoint configurations. Each endpoint can have the following properties:

[
  {
    "address": "192.168.1.100",
    "port": 443,
    "username": "admin",
    "password": "password123",
    "auth_method": "session",
    "tls_server_ca_cert": "/path/to/ca-cert.pem"
  },
  {
    "address": "192.168.1.101",
    "port": 8443,
    "username": "operator",
    "password": "secret456",
    "auth_method": "basic"
  }
]

Per-host properties:

• address (required): IP address or hostname of the Redfish endpoint
• port (optional): Port number (defaults to global REDFISH_PORT)
• username (optional): Username (defaults to global REDFISH_USERNAME)
• password (optional): Password (defaults to global REDFISH_PASSWORD)
• auth_method (optional): Authentication method (defaults to global REDFISH_AUTH_METHOD)
• tls_server_ca_cert (optional): Path to CA certificate (defaults to global REDFISH_SERVER_CA_CERT)

Configuration Methods

Configuration Methods

There are several ways to set environment variables:

1. Using a .env File (Recommended):
   Place a .env file in your project directory with key-value pairs for each environment variable. This is secure and convenient, keeping sensitive data out of version control.

   # Copy the example configuration
   cp .env.example .env
   
   # Edit the .env file with your settings
   nano .env

   Example .env file:

   # Redfish endpoint configuration
   REDFISH_HOSTS='[{"address": "192.168.1.100", "username": "admin", "password": "secret123"}, {"address": "192.168.1.101", "port": 8443}]'
   REDFISH_AUTH_METHOD=session
   REDFISH_USERNAME=default_user
   REDFISH_PASSWORD=default_pass
   
   # MCP configuration
   MCP_TRANSPORT=stdio
   MCP_REDFISH_LOG_LEVEL=INFO

2. Setting Variables in the Shell:
   Export environment variables directly in your shell before running the application:

   export REDFISH_HOSTS='[{"address": "127.0.0.1"}]'
   export MCP_TRANSPORT="stdio"
   export MCP_REDFISH_LOG_LEVEL="DEBUG"

Configuration Validation

The server performs comprehensive validation on startup:

• JSON Syntax: REDFISH_HOSTS must be valid JSON
• Required Fields: Each host must have an address field
• Port Ranges: Ports must be between 1 and 65535
• Authentication Methods: Must be basic or session
• Transport Types: Must be stdio, sse, or streamable-http
• Log Levels: Must be DEBUG, INFO, WARNING, ERROR, or CRITICAL

If validation fails, the server will:

1. Log detailed error messages
2. Show a deprecation warning about falling back to legacy parsing
3. Attempt to continue with basic configuration parsing

Note: The legacy fallback is deprecated and will be removed in future versions. Please ensure your configuration follows the validated format.

Transports

This MCP server can be configured to handle requests locally, running as a process and communicating with the MCP client via stdin and stdout. This is the default configuration. The sse and streamable-http transport is also configurable so the server is available over the network. Configure the MCP_TRANSPORT variable accordingly.

export MCP_TRANSPORT="sse"

Then start the server.

uv run src/main.py

Test the server:

curl -i http://127.0.0.1:8000/sse
HTTP/1.1 200 OK

Integrate with your favorite tool or client. The VS Code configuration for GitHub Copilot is:

"mcp": {
    "servers": {
        "redfish-mcp": {
            "type": "sse",
            "url": "http://127.0.0.1:8000/sse"
        },
    }
},

Integration with Claude Desktop

Manual configuration

You can configure Claude Desktop to use this MCP Server.

1. Retrieve your uv command full path (e.g. which uv)
2. Edit the claude_desktop_config.json configuration file
   • on a MacOS, at ~/Library/Application\ Support/Claude/

{
    "mcpServers": {
        "redfish": {
            "command": "<full_path_uv_command>",
            "args": [
                "--directory",
                "<your_mcp_server_directory>",
                "run",
                "src/main.py"
            ],
            "env": {
                "REDFISH_HOSTS": "[{\"address\": \"192.168.1.100\", \"username\": \"admin\", \"password\": \"secret123\"}]",
                "REDFISH_AUTH_METHOD": "session",
                "MCP_TRANSPORT": "stdio",
                "MCP_REDFISH_LOG_LEVEL": "INFO"
            }
        }
    }
}

Troubleshooting

You can troubleshoot problems by tailing the log file.

tail -f ~/Library/Logs/Claude/mcp-server-redfish.log

Integration with VS Code

To use the Redfish MCP Server with VS Code, you need:

1. Enable the agent mode tools. Add the following to your settings.json:

{
  "chat.agent.enabled": true
}

2. Add the Redfish MCP Server configuration to your mcp.json or settings.json:

// Example .vscode/mcp.json
{
  "servers": {
    "redfish": {
      "type": "stdio",
      "command": "<full_path_uv_command>",
      "args": [
        "--directory",
        "<your_mcp_server_directory>",
        "run",
        "src/main.py"
      ],
      "env": {
        "REDFISH_HOSTS": "[{\"address\": \"192.168.1.100\", \"username\": \"admin\", \"password\": \"secret123\"}]",
        "REDFISH_AUTH_METHOD": "session",
        "MCP_TRANSPORT": "stdio"
      }
    }
  }
}

// Example settings.json
{
  "mcp": {
    "servers": {
      "redfish": {
        "type": "stdio",
        "command": "<full_path_uv_command>",
        "args": [
          "--directory",
          "<your_mcp_server_directory>",
          "run",
          "src/main.py"
        ],
        "env": {
          "REDFISH_HOSTS": "[{\"address\": \"192.168.1.100\", \"username\": \"admin\", \"password\": \"secret123\"}]",
          "REDFISH_AUTH_METHOD": "session",
          "MCP_TRANSPORT": "stdio"
        }
      }
    }
  }
}

For more information, see the VS Code documentation.

Testing

You can use the MCP Inspector for visual debugging of this MCP Server.

npx @modelcontextprotocol/inspector uv run src/main.py

Example Use Cases

• AI Assistants: Enable LLMs to fetch infrastructure data via Redfish API .
• Chatbots & Virtual Agents: Retrieve data, and personalize responses.