Results for “server”

Qwik is a resumable web framework that delivers instant-loading applications by eliminating hydration. It serializes application state on the server and lazily loads JavaScript on interaction, making it ideal for edge deployment.

CLI interface for igf (Grapefruit) dynamic instrumentation server. Use to enumerate Frida devices, list apps, run hooks, query logs, access device file systems, inspect classes, dump memory, and perform mobile app security analysis.

Use this when reviewing whether an app, service, worker, CLI, or serverless system is ready for its target environment with respect to config, secrets, migrations, dependencies, observability, rollback, and runtime constraints.

Deploy trained machine learning models as production-ready services using REST APIs, containers, serverless functions, and orchestration platforms. Use when the user requests model deployment or provides relevant inputs for this workflow.

ATC REST API source generator and CLI for producing server endpoints, C# clients, and TypeScript clients from OpenAPI specifications. Use when the user asks to generate a REST API from an OpenAPI spec, scaffold server handlers, create typed HTTP clients, generate TypeScript clients with React Query hooks, configure API security or rate limiting, set up caching or resilience, version an API, generate webhooks, merge multi-part OpenAPI specs, or migrate from the old atc-rest-api-generator CLI.

React and Next.js performance optimization guidelines from Vercel Engineering. Use this skill when writing, reviewing, or refactoring React/Next.js code. Apply it proactively whenever working on React components, Next.js pages, API routes, data fetching (server or client), bundle size, rendering performance, re-renders, server actions, hydration, animations, or JavaScript optimizations. If the code involves React or Next.js, use this skill — even if performance isn't the stated goal, these patterns prevent issues before they arise.

Run state-of-the-art machine learning models directly in JavaScript/TypeScript across browsers and server-side runtimes using Transformers.js.

Organizes 70+ React and Next.js performance optimization rules across 8 priority categories for use when writing, reviewing, or refactoring code.

Query, inspect, and manage Redis databases from the command line using redis-cli, covering connection, data operations, scanning, and server diagnostics.

Measure and optimize .NET build performance by establishing baselines, enabling MSBuild Server, using artifacts output, and trimming dependency graphs.

Build, configure, scaffold, and deploy OCI Functions from a local machine using a dependency-first, Fn-context-guided flow with structured confirmations.

Create, modify, review, and harden configuration for the Adobe Dispatcher Apache HTTP Server module and Apache HTTPD in AEM 6.5 LTS environments only.

Automate Benchmark Email marketing tasks through Composio's Rube MCP integration, including contact management, campaign creation, and email sending.

Automates college football data operations through Composio's College Football Data toolkit via Rube MCP, with tool discovery and connection management.

Generates images and conducts conversations through the Gemini website (gemini.google.com) using MCP tools, scripts, or a managed browser as a fallback.

Gather competitive intelligence on companies by searching SEC filings, recent news, federal contracts, and comprehensive profiles through an MCP server.

React and Next.js performance optimization from Vercel Engineering. Use when building React components, optimizing performance, eliminating waterfalls, reducing bundle size, reviewing code for performance issues, or implementing server/client-side optimizations.

AI agent integration layer for the Pump SDK — agent instruction files, .well-known discovery, LLM context documents, 15+ skill files, MCP server prompts, and terminal management rules for GitHub Copilot and Gemini.

基于 Modular RAG MCP Server 项目生成定制化简历项目经历。结合项目技术亮点与用户业务场景，按简历编写原则输出高质量项目描述（中英文）。Use when user says '写简历', 'resume', '简历', 'write resume', '项目经历', 'project experience', '简历项目', or asks to generate resume content based on this project.

Trigger: empty list state, loader skeleton, error boundary layout, offline indicator, system fallback UI. Scope: UI fallback layouts, skeleton placeholders, client recovery views. Boundary: Excludes server-side API error status coding.

Trigger: form inputs, wizards, checkout forms, multistep forms, validation UI, input focus. Scope: User-friendly forms design, input constraints, progressive disclosure. Boundary: Excludes backend database schemas or server-side API validation.

React 18/19 patterns including hooks discipline, server/client component boundaries, Suspense + error boundaries, form actions, data fetching, state management decision trees, and accessibility-first composition. Use when writing or reviewing React components.

Access macOS native data (Messages, Contacts, Reminders, Calendar) via MCP server with iMCP. Use when: building AI assistants that access Apple data, querying contacts/reminders from Claude Desktop, integrating macOS apps with AI agents.

Use this when the team needs to design or refine a backend service, API-facing domain module, internal service, or runtime-specific server component in Python, Node.js, or another backend environment.

Use when modifying a Genie-backed Pharo project through the live MCP server on localhost:8087; includes project ownership, image read/change/test/save workflow, and first steps for new user projects.

Amazon SQS managed message queue service. Covers standard and FIFO queues, dead-letter queues, and integration patterns. Use for AWS-native serverless and microservices architectures. USE WHEN: user mentions "sqs", "aws queues", "fifo queue", "lambda trigger", "sns to sqs", asks about "aws messaging", "serverless queues", "standard queue", "visibility timeout" DO NOT USE FOR: event streaming - use `kafka` or AWS Kinesis; Azure-native - use `azure-service-bus`; GCP-native - use `google-pubsub`; on-premise - use `rabbitmq` or `activemq`; complex routing - use `rabbitmq`

Interact with MCP servers from the command line to discover, inspect, and call tools for external systems like GitHub, filesystems, databases, and APIs.

Generate comprehensive rollout plans with preflight checks, step-by-step deployment, verification signals, rollback procedures, and communication plans for infrastructure and application changes.

Creates a declarative agent for Microsoft 365 Copilot by integrating an MCP server with authentication, tool selection, and configuration.

Test web applications for path traversal vulnerabilities that allow reading or writing arbitrary files on the server by manipulating file path parameters.

Provides idiomatic Kotlin implementation patterns including coroutine concurrency, Flow stream handling, multiplatform architecture, Compose UI construction, Ktor server setup, and type-safe DSL design.

Production patterns and non-obvious traps for Prisma ORM in TypeScript backends, covering schema design, query optimization, transactions, pagination, and serverless connection handling.

Diagnoses Linux server issues across CPU, memory, disk, I/O, and network, and manages systemd services, SSH, and Fail2Ban on Ubuntu, Debian, and AlmaLinux.

Run GGUF models locally with llama.cpp, including finding the right file on the Hugging Face Hub, installing, quantizing, serving, and using Python bindings.

Integrates with the Brighty banking API to open accounts, issue Mastercard cards, trade crypto, and send SEPA/SWIFT payments from a bot or automation.

Run Python code in the cloud with serverless containers, GPUs, and autoscaling. Use when deploying ML models, running batch processing jobs, scheduling compute-intensive tasks, or serving APIs that require GPU acceleration or dynamic scaling.