Best for
- AI agents that need to access hardware information in natural language
- Core developers who need quick insight into system resources
- Users managing scientific HPC workloads
C
CLIO Node Hardware
Community
Comprehensive hardware monitoring and system analysis
GitHub source repository ↗
57FMRS · C
CLIO Node Hardware is part of CLIO Kit and provides comprehensive hardware monitoring tools, suitable for AI agents in HPC environments for system management and troubleshooting. It provides reliable information via stdio.
CLIO Node Hardware (originally io.github.iowarp/node-hardware-mcp) is an MCP server that provides comprehensive hardware monitoring and system analysis capabilities for LLMs. It runs over stdio and offers detailed information on CPU, memory, disk, network, GPU, sensors, processes, and real-time performance, with support for remote node monitoring via SSH.
Tools
get_cpu_info
Get CPU specifications, core counts, frequencies, and per-core usage.
get_memory_info
Get RAM and swap capacity, usage percentages, and availability.
get_system_info
Get OS details, hostname, uptime, and active users.
get_disk_info
Get disk partitions, usage statistics, and I/O counters.
get_network_info
Get network interfaces, IP addresses, and I/O statistics.
get_gpu_info
Get GPU model, memory, temperature, and utilization via nvidia-smi/rocm-smi.
get_sensor_info
Get temperature, fan speed, and battery sensor readings.
get_process_info
Get running processes with CPU, memory, and status details.
get_performance_info
Get real-time CPU, memory, disk, and network performance metrics.
get_remote_node_info
Collect hardware info from a remote node via SSH. Supports component filtering.
health_check
Verify server health and hardware monitoring capability status.
Setup
- Install uv package manager: curl -LsSf https://astral.sh/uv/install.sh | sh or pip install uv. 2. Install clio-kit: uv tool install 'clio-kit==2.4.3' and run uv tool update-shell. 3. Configure the MCP server in your client, for example: {"mcpServers":{"node-hardware":{"command":"clio-kit","args":["mcp-server","node-hardware"]}}}
claude_desktop_config.json
{
"mcpServers": {
"node-hardware": {
"command": "clio-kit",
"args": [
"mcp-server",
"node-hardware"
]
}
}
}
Fit and risk
Not for
- Detailed benchmarking or low-level hardware raw data (beyond this server's scope)
- Performance monitoring on remote machines where SSH is not possible
- Monitoring systems that require advanced aggregation across multiple nodes (only single remote node fetching is provided here)
Required permissions
- Read CPU, memory, disk, network, GPU, sensor, and process information
- Execute read-only commands locally (such as nvidia-smi/rocm-smi)
- SSH access to collect remote node information
Risks and side effects
- Process and system information may contain sensitive data if exposed to the AI agent
- GPU queries may fail due to driver or hardware issues
- Remote monitoring requires valid SSH credentials and may pose security risks
Troubleshooting
- Ensure clio-kit is installed via uv tool install and update-shell has been run
- Check MCP client configuration for correct command and arguments
- Verify that GPU tools (nvidia-smi or rocm-smi) are available and executable on the system
- For remote nodes, check SSH connectivity, credentials, and firewall settings
Use cases
Get hardware specs and status of the current node
Monitor hardware health of remote nodes
Collect performance metrics for system tuning
Supported clients
Claude DesktopFull support
CursorFull support
VS CodeFull support