GpuScanner

A comprehensive GPU monitoring and blog automation system that tracks GPU availability and pricing across multiple cloud providers while generating automated blog content.

https://gpufindr.com

Overview

GpuScanner is a multi-component Go application that:

• Scans and monitors GPU resources across cloud providers (AWS Lambda, RunPod, TensorDock, Vast.ai)
• Provides a web API and frontend for GPU search and monitoring
• Automatically generates and publishes blog content about GPU market trends
• Integrates with MCP (Model Context Protocol) for AI-powered interactions

Architecture

The project is organized into several key components:

Core Applications

• cmd/api/ - Web API server with frontend interface
• cmd/blog/ - Blog content generation and management system
• cmd/scan/ - GPU scanning service across multiple providers

Key Features

• Multi-Provider GPU Scanning: Monitors GPU availability across Lambda, RunPod, TensorDock, and Vast.ai
• REST API: Provides endpoints for GPU data retrieval and search
• Web Frontend: HTML interface for searching and viewing GPU information
• Automated Blogging: Daily blog post generation using AI
• MCP Integration: Model Context Protocol support for AI interactions

Components

GPU Scanning (cmd/scan/)

• lambdaGetter.go - AWS Lambda GPU monitoring
• runpodGetter.go - RunPod GPU tracking
• tensordockGetter.go - TensorDock integration
• vastGetter.go - Vast.ai monitoring
• scan.go - Main scanning orchestrator

API Server (cmd/api/)

• main.go - HTTP server and routing
• gpu.go - GPU-related API endpoints
• blog.go - Blog management API
• mcp.go - MCP protocol implementation
• static.go - Static file serving
• frontend/ - HTML templates and UI

Blog System (cmd/blog/)

• main.go - Blog generation entry point
• write.go - Content creation and publishing
• upload.go - Media and asset management
• types.go - Data structures

Installation

1. Clone the repository:

git clone https://github.com/ShayManor/GpuScanner.git
cd GpuScanner

2. Install dependencies:

go mod tidy

3. Set up environment variables:

export SUPABASE_URL="example"
export SUPABASE_SERVICE_KEY="example"
export OPENAI_API_KEY="example"
... GPU provider keys

Usage

Running API

go run ./cmd/api

Manual GPU scan

go run ./cmd/scan

Generate Article for Blog

go run ./cmd/blog

Automation

The project includes GitHub Actions workflow (.github/workflows/blog.yaml) that:

• Runs daily at midnight
• Automatically generates articles
• Publishes to Supabase

API Documentation

• OpenAPI specification: cmd/api/openapi.yaml
• Swagger documentation: docs/swagger.json