81 boosters for "cloud" — open source, verified from GitHub, ready to install
A specialized security expert agent that performs threat modeling, vulnerability assessment, and secure code review to help developers build secure applications and cloud infrastructure. Ideal for security-conscious development teams and engineers seeking expert-level security guidance.
Backend Architect is an AI agent that provides expert guidance on scalable system design, database architecture, API development, and cloud infrastructure. It's ideal for developers and teams building robust, secure server-side applications and microservices.
A specialized agent that guides users through designing, building, and operating scalable data pipelines and lakehouse architectures. Data engineers, analytics engineers, and platform teams use this to architect reliable ETL/ELT systems and cloud data infrastructure.
DevOps Automator is an expert agent that automates infrastructure, CI/CD pipelines, and cloud operations to help engineering teams reduce manual toil and ship faster. It's ideal for teams seeking to streamline deployments and improve system reliability.
Streamlines Cloudflare deployments by guiding users through Workers, Pages, and platform services with decision trees and authentication verification. Developers building on Cloudflare benefit from consolidated, quick-start deployment guidance.
render-deploy automates deployment to Render's cloud platform by analyzing codebases and generating render.yaml Blueprints with Dashboard deeplinks. Developers building applications on Render will find this essential for streamlined deployments.
Train object detection, image classification, and SAM/SAM2 segmentation models on managed cloud GPUs. No local GPU setup required—results are automatically saved to the Hugging Face Hub. Use this skill when users want to: Helper scripts use PEP 723 inline dependencies. Run them with :
Provides the Hugging Face Hub CLI (`hf`) tool for downloading, uploading, and managing models, datasets, and Spaces directly from Claude Code. Essential for developers integrating Hugging Face resources into AI workflows.
Train language models using TRL (Transformer Reinforcement Learning) on fully managed Hugging Face infrastructure. No local GPU setup required—models train on cloud GPUs and results are automatically saved to the Hugging Face Hub. Use this skill when users want to: Use Unsloth () instead of standard
Run any workload on fully managed Hugging Face infrastructure. No local setup required—jobs run on cloud CPUs, GPUs, or TPUs and can persist results to the Hugging Face Hub. Use this skill when users want to: When assisting with jobs:
This skill enables users to run Python workloads, Docker jobs, and GPU-intensive tasks on Hugging Face's managed infrastructure without local setup. It's valuable for ML engineers, data scientists, and developers needing cloud compute for training, inference, and batch processing.
A skill for fine-tuning and training language models on Hugging Face's cloud GPU infrastructure using TRL, supporting SFT, DPO, GRPO methods and GGUF conversion for local deployment. Developers and ML engineers working with cloud-based model training benefit from this comprehensive guidance.
Enables developers to interact with Hugging Face Hub directly from Claude Code using the `hf` CLI—downloading models/datasets, uploading files, creating repositories, and managing cache without leaving the coding environment.
IntentKit is an open-source, self-hosted cloud agent cluster that manages a collaborative team of AI agents for you.
Use to stream-read from archive:
Heuristic scoring (no AI key configured).
"description": "Cloud-backed persistent memory powered by Deeplake — read, write, and share memory across Claude Code sessions and agents", "version": "0.7.104", "name": "Activeloop",
Retrieve current documentation and code examples for any library using the Context7 CLI. Make sure the CLI is up to date before running commands: Or run directly without installing:
This rule provides a guide to understanding the structure and core functionalities of the MCP Boilerplate project. It's designed to help you navigate and extend the boilerplate effectively. The project is a Cloudflare Worker that implements an MCP (Model Context Protocol) server with built-in suppor
"name": "@_davideast/stitch-mcp", "description": "Stitch MCP CLI helper. Automates Google Cloud authentication. Generates MCP config for your client. Sets up a proxy server.", "stitch-mcp": "./bin/stitch-mcp.js"
Unified guide for working with MongoDB (document-oriented) and PostgreSQL (relational) databases. Choose the right database for your use case and master both systems. Database utility scripts in :
This booster enables developers to manage Alibaba Cloud CDN operations—including domain onboarding, cache management, and certificate updates—directly through an AI coding assistant with OpenAPI/SDK integration. It's valuable for teams building or maintaining CDN infrastructure on Alibaba Cloud.
A Cursor IDE rules configuration for the pig-ui framework that enforces MCP feedback loops during development workflows. Beneficial for teams using Spring Boot 3.5, Spring Cloud, and Vue with role-based access control requirements.
