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Yamaru Hardware Probe 1.1.3

npm · @yamaru-eu/hardware-probe · latest release

Verified with no proven findings
Security result
11
Observed tools
37
Version rating
100
Change risk

Independent inventory

Observed 2026-08-18T12:06:50.767Z using mcpSecurity-inventory. Protocol 2025-06-18.

ToolCategoryRisk
analyze_inference_configPerforms a deep scan for LLM inference optimization: GPU details, real memory bandwidth benchmark, ML runtimes (Ollama, Docker, WSL), and environment variables.
Input schema
{
  "type": "object",
  "properties": {},
  "required": []
}
analyze_local_systemReads the hardware specifications of the local machine: CPU, RAM, motherboard and OS. Returns a structured JSON object.
Input schema
{
  "type": "object",
  "properties": {},
  "required": []
}
analyze_performanceProvides real-time system performance: CPU load, memory usage, and top processes.
Input schema
{
  "type": "object",
  "properties": {},
  "required": []
}
analyze_ram_pressureReports current memory pressure: total/used/free/available memory, swap usage, and top processes by RSS.
Input schema
{
  "type": "object",
  "properties": {},
  "required": []
}
check_llm_compatibility(BETA) Checks if a specific LLM model can run on this machine. Returns optimal quantization and estimated tokens per second. Requires remote API connection.
Input schema
{
  "type": "object",
  "properties": {
    "model_name": {
      "type": "string",
      "description": "LLM model name (e.g., 'Llama 3.1 70B')"
    }
  },
  "required": [
    "model_name"
  ]
}
check_storage_healthReports per-disk health: type (NVMe/SSD/HDD), vendor, temperature, SMART status, and firmware.
Input schema
{
  "type": "object",
  "properties": {},
  "required": []
}
diagnose_antivirus_impactDetects running antivirus/EDR products and reads their exclusion rules. Checks dev hot paths coverage.
Input schema
{
  "type": "object",
  "properties": {},
  "required": []
}
get_inference_expert_knowledgeReturns the expert instructions and rules for optimizing LLM inference on this specific hardware. Call this to learn HOW to interpret analyze_inference_config results.
Input schema
{
  "type": "object",
  "properties": {},
  "required": []
}
get_llm_recommendations(BETA) Recommends the best LLM models that can run locally on this machine. Requires remote API connection.
Input schema
{
  "type": "object",
  "properties": {
    "use_case": {
      "type": "string",
      "enum": [
        "general",
        "coding",
        "reasoning",
        "chat"
      ],
      "description": "Use case"
    },
    "limit": {
      "type": "number",
      "description": "Max recommendations"
    }
  }
}
monitor_system_healthMonitors system metrics (CPU load, RAM usage, CPU temperature) over a configurable duration (up to 10 minutes) and returns min/max/avg statistics. Use duration_seconds to set the observation window and interval_seconds to control sampling granularity.
Input schema
{
  "type": "object",
  "properties": {
    "duration_seconds": {
      "type": "number",
      "description": "Monitoring duration in seconds (1-600)",
      "default": 10
    },
    "interval_seconds": {
      "type": "number",
      "description": "Sampling interval in seconds",
      "default": 2
    }
  }
}
thermal_profileReports current CPU and GPU thermal and frequency state: temperature, utilization, and fan speed.
Input schema
{
  "type": "object",
  "properties": {},
  "required": []
}

Resources 0

Resource templates 0

Prompts 0

Changes from previous version

Compared with initial baseline using full_baseline.

RiskChangeSubject
No material changes recorded.

Confirmed vulnerabilities

SeverityFindingAdvisory
No confirmed vulnerability is published for this version.

Provenance

Artifact SHA-256: e3fed0bac476c7879b3d3b2c72445a3ecfdceccd42be1cbd323ef7ce60810bbe

Scanner: mcp-proof-engine 0.1.0.

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