Hardware Probe

Name: Hardware Probe
Author: yamaru-eu

by yamaru-euversion 1.1.2i★ –iRuns on your computer

Registry nameio.github.yamaru-eu/hardware-probe

Install

Overview

Description from the maker (original English)

Hardware probe for performance diagnostics, thermal monitoring, and LLM optimization.

PopNx MCP’s three pillars

These three are never merged into one score: opinions, measurements and popularity are different things.

User voiceiNo reviews yetReviews open together with accounts in a later step
Our basic checksi1 of 1 passedChecked from public information; code not scanned yet
UsageiNot measured yet★ –

What you can do with it

We have not written a plain-language summary for this one yet. Below are the facts we read from the registry.

Connection: Runs on your computer
Transport: stdio
Category: Search & AI memory

Install

Pick the AI app you use, then copy the settings.

Before you install

Basic checks: 1 of 1 passed
Runs on your computer with your user’s permissions (files, network, apps).
You fill in yourself: REMOTE_API_URL

You need

npmNode.js installed (for the npx command)

Which app do you use?

ClaudeClaude CodeCursorVS CodeChatGPT

Pick your app above. We remember it, so next time the button says “Install in …”.

Open Claude Desktop → Settings → Developer → Edit Config, and paste this into claude_desktop_config.json

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

Run this in your terminal

claude mcp add hardware-probe --env REMOTE_API_URL=your-value -- npx -y @yamaru-eu/hardware-probe

Fill in the empty values before running it.

Open in Cursor

Or copy the settings yourself

Paste into .cursor/mcp.json in your project, or ~/.cursor/mcp.json

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

Your browser asks to open the app, then the app shows the settings and asks you to confirm. Key values are left empty for you to fill in.

Open in VS Code

Or copy the settings yourself

Paste into .vscode/mcp.json in your project

{
  "servers": {
    "hardware-probe": {
      "type": "stdio",
      "command": "npx",
      "args": [
        "-y",
        "@yamaru-eu/hardware-probe"
      ],
      "env": {
        "REMOTE_API_URL": "your-value"
      }
    }
  }
}

Your browser asks to open the app, then the app shows the settings and asks you to confirm. Key values are left empty for you to fill in.

This one runs on your computer, and ChatGPT can only connect to servers on the internet. Pick another app.

Your choice stays on this device in a cookie; no account needed.

Values you fill in

REMOTE_API_URL env
URL of the remote recommendation API

These settings are generated from the maker’s registry entry. If the README says otherwise, follow the README.

What it can do

Runs on your computer; the tool list appears in your AI app after you install it.

Basic checksi

We check information anyone can see; we have not read the code. Checks that do not apply are left out of the count. · Checked Nov 7, 2026

✓ Pass
Maker matches the repo
The registry name was verified with the GitHub account yamaru-eu, which owns the repo
… Not checked yet
Still maintained
We have not read this repo from GitHub yet
… Not checked yet
Has a licence
We have not read this repo from GitHub yet
– Not applicable
Endpoint responds
This one runs on your computer; there is no internet endpoint
– Not applicable
Sign-in with OAuth
Runs on your computer and uses local settings instead
… Not checked yet
No hidden instructions in tool descriptions
Runs on your computer; we can only read tool lists from internet endpoints

Compared with others in Search & AI memoryi

More stars than 0% of the other 7257 servers in this category
Published to the registry more recently than 10% of the other 7257 servers in this category
Basic checks equal to or better than 100% of the other 7257 servers in this category

Compared with every active server in this category in the registry. Stars count only when the publisher owns the repo.

Common questions

Is Hardware Probe safe?

It passed 1 of 1 applicable basic checks. We have not read the code. Before adding a key or token, see what access the server asks for and use a key with only the permissions you need.

What keys or codes does it need?

The registry does not list a required key, though some servers ask you to sign in on first use.

Does it run on my computer or in the cloud?

It runs on your computer. Your AI app starts it when needed, and data does not pass through the maker’s servers (unless it calls an online service itself).

Is it still maintained?

The GitHub repo last changed –, and the latest version (1.1.2) reached the registry 7 months ago.

Which apps can use it?

Apps that support MCP, such as Claude Desktop, Claude Code, Cursor and VS Code. You also need Node.js on your computer.

What can I use instead?

In the same category: Context7, Codebase Memory, Exa

Alternatives

Servers in the same category from other makers, sorted by stars.

Reading a card:★ GitHub starsiThree pillars: reviews · checks · usageiUpdated = latest version published to the registryi

Context7

by upstash

Feeds AI the latest docs for libraries and frameworks before it answers, so code it writes does not use outdated, removed functions.

Computer or cloud★ 64,224MITUpdated today

Install

Codebase Memory

by DeusData

Codebase knowledge graph for AI agents — 162 languages, sub-ms queries, 99% fewer tokens.

Runs on your computer★ 48,148MITUpdated 20 days ago

Install

Exa

by exa-labs

Connect AI agents to Exa for web search, content fetching, and multi-step research.

Runs in the cloud★ 5,213MITUpdated last month

Install

README from the maker

Open the README

Copied from the maker’s repo as written. PopNx MCP has not reviewed or endorsed it. HTML, images and scripts are removed. Links lead off this site.

Yamaru Hardware Probe (MCP)

Expert system hardware probe and performance diagnostic engine for AI, Gaming, and High-Performance workflows. This is a Model Context Protocol (MCP) server that provides deep system insights beyond simple specifications.

Key Features

🔍 Deep Hardware Inventory: Comprehensive analysis of CPU, RAM, GPU (VRAM/Bandwidth), Storage, and OS topology.
⚡ Real-time Performance Monitoring: Live tracking of system load and identification of resource-hogging processes.
🧊 Thermal & Power Diagnostics: Detects thermal throttling and frequency clipping to resolve unexpected slowness.
🤖 AI/LLM Optimization: Specialized tools for predicting LLM performance, calculating quantization fit, and optimizing runtimes (Ollama, CUDA, Metal).
🛡️ Privacy-First: Automatic anonymization of unique hardware identifiers before any remote transmission.

Installation

For Gemini CLI Users

gemini extension install @yamaru-eu/hardware-probe

For Manual MCP Setup

Add this to your MCP settings file (e.g., npx-config.json or claude_desktop_config.json):

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

Available Tools

analyze_local_system: Full hardware inventory.
analyze_performance: Real-time performance metrics and top processes.
analyze_ram_pressure: Detailed memory pressure and RSS analysis for deep RAM troubleshooting.
check_storage_health: Disk SMART health, firmware, and I/O bottleneck analysis.
thermal_profile: Real-time CPU/GPU thermal states, fan speeds, and frequency throttling detection.
diagnose_antivirus_impact: Detects EDR/Antivirus conflicts and exclusion coverage on dev paths.
monitor_system_health: Statistical health report (CPU load, RAM usage, temperature) with min/max/avg over a configurable time window (up to 10 minutes).
check_llm_compatibility (BETA): Predicts performance for a specific LLM model via remote API.
get_llm_recommendations (BETA): Recommends the best local models via remote API.
analyze_inference_config: Deep-dive into AI runtimes and environment variables.

Skills Integration

When used with Gemini CLI, this extension provides the following expert skills:

hardware-performance-expert: Global protocol for system health and troubleshooting.
local-inference-optimizer: Specialized logic for fine-tuning local LLM runs.

Development

npm install        # Install dependencies

npm run build # Compile TypeScript → dist/ npm run test # Run test suite npm run inspector # Test tools in the MCP Inspector

License

Apache 2.0 - Part of the Yamaru Project.

Hardware Probe

Overview

PopNx MCP’s three pillars

What you can do with it

Install

Before you install

Values you fill in

What it can do

Basic checksi

Maker matches the repo

Still maintained

Has a licence

Endpoint responds

Sign-in with OAuth

No hidden instructions in tool descriptions

Compared with others in Search & AI memoryi

Common questions

Alternatives

Context7

Codebase Memory

Exa

README from the maker

Yamaru Hardware Probe (MCP)

Key Features

Installation

For Gemini CLI Users

For Manual MCP Setup

Available Tools

Skills Integration

Development

License