Yamaru Hardware Probe
OfficialRelated Servers
Alternatives to Yamaru Hardware Probe
No user-submitted related servers found.
Related Servers
- AlicenseNot gradedqualityDmaintenanceEnables real-time monitoring of system resources including CPU, GPU (NVIDIA, Apple Silicon, AMD/Intel), memory, disk, network, and processes across Windows, macOS, and Linux platforms through natural language queries.3MIT
- FlicenseNot gradedqualityCmaintenanceA real-time system diagnostics MCP server that gives AI agents live access to CPU, RAM, disk, network, processes, and hardware health metrics, with zero cloud dependency.7-
- AlicenseCqualityDmaintenanceProvides AI agents with real-time system monitoring and control for creative workstations, enabling thermal management and process prioritization to prevent crashes.101MIT
- AlicenseAqualityCmaintenanceHardware probe MCP server that provides deep hardware inventory and live sensor telemetry for AI agents, including CPU, memory, disk, GPU, and sensor data across platforms.6MIT
- AlicenseNot gradedqualityDmaintenanceComprehensive system diagnostics and monitoring server providing detailed hardware information, performance metrics, and optimization recommendations.MIT
- AlicenseAqualityNot gradedmaintenanceProvides comprehensive system diagnostics and hardware analysis through 10 specialized tools for troubleshooting and environment monitoring. Offers targeted information gathering for CPU, memory, network, storage, processes, and security analysis across Windows, macOS, and Linux platforms.10MIT
TDQS
Scored across 11 tools
Several tools overlap in purpose: analyze_ram_pressure, analyze_performance, and monitor_system_health all deal with CPU/memory metrics, causing potential confusion. Additionally, system specs are split across analyze_local_system and analyze_inference_config, adding ambiguity.
Tool names mostly follow a verb_noun pattern but use a mix of verbs (analyze, check, get, diagnose, monitor) without uniform style. Some compound nouns are inconsistent in format, making the set moderately predictable.
With 11 tools, the count is well within the 3-15 optimal range. Each tool serves a distinct purpose related to hardware probing and LLM inference, without being excessive.
The set covers hardware specs, storage health, thermal, performance, and LLM inference utilities, but lacks basic metrics like disk usage and network info. The inclusion of antivirus impact is niche, while GPU info is only available in inference context.