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Yamaru Hardware Probe MCP Server

@yamaru-eu

代码仓库

基本信息

分类

AI 与智能体

传输方式

stdio

作者

yamaru-eu

提交者

erz

关于 Yamaru Hardware Probe MCP Server

Yamaru Hardware Probe gives Claude Desktop and other MCP clients real visibility into your machine. 10 expert tools: full hardware inventory, real-time performance & thermal monitoring, RAM pressure analysis, SMART storage health, antivirus impact diagnostics, and LLM compatibili

#hardware#diagnostic#monitoring#llm#performance#thermal#ram#gpu#vram#systeminformation#claude#mcp-server

Yamaru Hardware Probe MCP Server 配置

使用下面的配置,将此服务器添加到你的 MCP 客户端。

{
  "mcpServers": {
    "yamaru-probe": {
      "command": "npx",
      "args": [
        "-y",
        "@yamaru-eu/hardware-probe"
      ]
    }
  }
}

Yamaru Hardware Probe MCP Server 工具

11

Reads the hardware specifications of the local machine: CPU, RAM, motherboard and OS. Returns a structured JSON object.

Provides real-time system performance: CPU load, memory usage, and top processes.

Performs a deep scan for LLM inference optimization: GPU details, real memory bandwidth benchmark, ML runtimes (Ollama, Docker, WSL), and environment variables.

Returns the expert instructions and rules for optimizing LLM inference on this specific hardware. Call this to learn HOW to interpret analyze_inference_config results.

(BETA) Checks if a specific LLM model can run on this machine. Returns optimal quantization and estimated tokens per second. Requires remote API connection.

(BETA) Recommends the best LLM models that can run locally on this machine. Requires remote API connection.

Reports current memory pressure: total/used/free/available memory, swap usage, and top processes by RSS.

Reports per-disk health: type (NVMe/SSD/HDD), vendor, temperature, SMART status, and firmware.

Reports current CPU and GPU thermal and frequency state: temperature, utilization, and fan speed.

Detects running antivirus/EDR products and reads their exclusion rules. Checks dev hot paths coverage.

Monitors 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.

概览

What is Yamaru Hardware Probe?

Open-source MCP server that gives LLM clients real hardware diagnostics from the machine they run on. It exposes 10 expert tools covering CPU, RAM, VRAM, thermals, storage health, and more — so AI assistants provide grounded, data-driven answers instead of generic responses. Built by the Yamaru project.

How to use Yamaru Hardware Probe?

Add the server configuration to your claude_desktop_config.json with the command npx -y @yamaru-eu/hardware-probe and restart Claude Desktop. The server then exposes 10 diagnostic tools queryable through any MCP client.

Key features of Yamaru Hardware Probe

  • Deep hardware inventory — CPU, RAM, GPU, motherboard, OS
  • Real-time performance monitoring with top processes
  • Thermal and power diagnostics with throttling detection
  • SMART storage health per-disk temperature and wear
  • Antivirus and EDR impact detection on dev paths
  • LLM compatibility prediction for quantization fit (BETA)

Use cases of Yamaru Hardware Probe

  • Diagnose PC slowness during local model inference
  • Check if your machine can run a specific LLM model
  • Verify antivirus is not scanning your models folder
  • Monitor system health over time for anomaly detection
  • Tune Ollama, CUDA, or Metal inference runtime settings

常见问题

1

What makes this different from asking an LLM directly?

Instead of a generic “it depends on your configuration” response, the server lets the LLM read your actual CPU, RAM, VRAM, thermals, and storage health and give you a real, data-driven answer.

2

What runtime dependencies are required?

The server runs via npx with `@yamaru-eu/hardware-probe`. It is built on TypeScript, the MCP SDK, and the systeminformation library.

3

How does the server handle privacy?

The server is privacy-first — it automatically anonymizes unique hardware IDs before any remote call.

4

What features are in BETA status?

The LLM compatibility prediction tools (`check_llm_compatibility`, `get_llm_recommendations`, `analyze_inference_config`) are marked as BETA.

5

What license is the project under?

The project is licensed under Apache 2.0.

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