Explica en lenguaje sencillo qué estás construyendo y obtén los mejores repositorios de GitHub que coincidan.
awesome-repositories.com te ayuda a encontrar el proyecto open-source adecuado en GitHub. Dile a nuestra búsqueda por IA qué quieres construir, en lenguaje sencillo, y clasificará miles de repositorios curados según su relevancia. Cada proyecto es monitoreado continuamente, organizados en categorías claras y votados por otros desarrolladores. Explora las selecciones a continuación o realiza una búsqueda para comenzar.
Lo más destacado del directorio: una selección nueva cada pocas horas.
Búsquedas comunes, organizadas en un árbol navegable.
Es un directorio curado de repositorios open-source de GitHub que puedes buscar en lenguaje natural. Describe lo que estás construyendo y una IA clasificará miles de proyectos verificados según su relevancia, incluyendo una breve nota sobre por qué encajan.
La búsqueda de GitHub coincide con las palabras clave que escribes. Aquí describes el problema en lenguaje natural y la IA interpreta tu intención, por lo que aparecerá un proyecto que resuelva tu necesidad incluso si no utiliza tus palabras exactas.
Escribe lo que quieres construir, por ejemplo: una página de estado autohospedada que haga ping a mis servicios y me avise por Discord. Obtendrás repositorios coincidentes clasificados por relevancia en lugar de por número de estrellas.
Están curados, no es una extracción bruta. Una IA analiza cada proyecto, lo clasifica en una categoría y lo ordena por relevancia bajo reglas que ajustamos y revisamos, eliminando entradas duplicadas o de baja calidad.
Sí. Buscar y navegar por el directorio es gratuito.
LLMs, agents, and the tools to build with them.
Notes, tasks, docs, and knowledge bases.
Chat, calls, photos, music, and personal files.
Databases, pipelines, and analytics.
Containers, deployment, monitoring, and automation.
Passwords, secrets, and offensive security.
Languages, CLIs, frameworks, and version control.
Courses, books, interviews, and CS foundations.
This framework provides a multi-process architecture for building desktop applications using web technologies. It manages the application lifecycle, window states, and system-level integrations through a primary entry point, while isolating web content in separate rendering processes to maintain stability and security. A secure bridge mechanism facilitates communication between these isolated contexts and the main process, ensuring that privileged system APIs remain protected. The framework distinguishes itself through a comprehensive security model that includes process sandboxing, content p
Uptime Kuma is a self-hosted monitoring platform designed to track the availability and performance of network services and websites. It functions as a centralized dashboard that executes asynchronous health checks on a scheduled interval, providing real-time visibility into infrastructure health and service uptime. The platform distinguishes itself through a dedicated notification engine that dispatches alerts across multiple third-party messaging services, alongside a public status page generator that allows users to communicate service health and historical metrics via custom domains. Its
This project is a data processing engine and AI application platform designed for building production-grade machine learning workflows. It provides a unified programming model that handles both historical batch data and live stream ingestion, enabling the development of real-time ETL pipelines and scalable data transformation workflows. The framework distinguishes itself through differential dataflow execution, which propagates only changes through a pipeline rather than recomputing entire datasets. It supports distributed state management across worker nodes and utilizes incremental stream p
Bevy is a cross-platform game engine and framework built in Rust, designed for creating interactive simulations and graphical applications. It utilizes a data-oriented entity-component-system architecture to manage game state, organizing data into contiguous memory blocks to facilitate high-performance processing and massive parallelization of entities. The engine distinguishes itself through a modular plugin architecture and a system-based task scheduler that automatically parallelizes logic by analyzing data access patterns. By employing reactive change detection and deferred command buffer