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MCP server to provide Figma layout information to AI coding agents like Cursor
Searchable encryption for Laravel models with database or Elasticsearch indexing.
⚗️ Adds code analysis to Laravel improving developer productivity and code quality.
A powerful open-source UI framework for Laravel • Build and ship apps & admin panels fast with Livewire
FULL Augment Code, Claude Code, Cluely, CodeBuddy, Comet, Cursor, Devin AI, Junie, Kiro, Leap.new, Lovable, Manus, NotionAI, Orchids.app, Perplexity, Poke, Qoder, Replit, Same.dev, Trae, Traycer AI…
The easiest way to use Agentic RAG in any enterprise
😎Awesome GIS is a collection of geospatial related sources, including cartographic tools, geoanalysis tools, developer tools, data, conference & communities, news, massive open online course, some …
Simple static Composer repository generator - For a full private Composer repo use Private Packagist
This is little script for mass changes in wordpress visual composer database. You can change all domains, html code, scripts and etc, data that in base64 coded.
Complete API layer for private AI applications on local models: RAG, skills, tools, MCP, text-to-sql, and more. Works with any OpenAI-compatible inference server.
Cloth2Tex: A Customized Cloth Texture Generation Pipeline for 3D Virtual Try-On
Outfit Anyone: Ultra-high quality virtual try-on for Any Clothing and Any Person
Simple JSON localization file manager
laravel package to implement database transaction with ease
🇮🇹 Fastify ha una solida architettura a plugin, è altamente performante, supporta Typescript e pensa alla developer experience per rendere meno arduo lo sviluppo a noi programmatori. Ma tutto quest…
Easily anonymize sensitive data through eloquent queries
Use Ciphersweet in your Laravel project
The library lets you generate TypeScript types from your Laravel code
A dynamic table component for Laravel Livewire
On-scan events for hardware barcode scanners in vanilla JS
The elegant testing framework for PHP developers and AI agents.
Example 📓 Jupyter notebooks that demonstrate how to build, train, and deploy machine learning models using 🧠 Amazon SageMaker.
Literature references for “Designing Data-Intensive Applications”