Deployment AI Agent Skills

Universal Deployment Tracker for AI Assistants Track deployments across all platforms directly in your AI conversation. No more context-switching. No more dashboard hunting. Watch Full Demo · Live Badge Demo ───────────────────────── Get started in under 30 seconds: That's it! The server is now running and ready to be configured in your AI assistant. ───────────────────────── deploy-mcp supports m

Orchestrate end-to-end backend feature development from requirements to deployment. Use when coordinating multi-phase feature delivery across teams and services.

Design multi-stage CI/CD pipelines with approval gates, security checks, and deployment orchestration. Use when architecting deployment workflows, setting up continuous delivery, or implementing GitOps practices.

Build end-to-end MLOps pipelines from data preparation through model training, validation, and production deployment. Use when creating ML pipelines, implementing MLOps practices, or automating model training and deployment workflows.

Backend: Node.js with Express.js

Claude Code plugins for AWS development with specialized knowledge and MCP server integrations, including CDK, serverless architecture, cost optimization, and Bedrock AgentCore for AI agent deployment. Shared AWS agent skills including AWS Documentation MCP configuration for querying up-to-date AWS knowledge. - AWS MCP server configuration guide - Documentation MCP setup for querying AWS knowledge

Archive session learnings, debugging solutions, and deployment logs to .archive/yyyy-mm-dd/ as indexed markdown with searchable tags. Use when completing a significant task, resolving a tricky bug, deploying, or when the user says \"archive this\". Maintains .archive/MEMORY.md index for cross-session knowledge reuse.

kubectl-mcp-server Control your entire Kubernetes infrastructure through natural language conversations with AI. Talk to your clusters like you talk to a DevOps expert. Debug crashed pods, optimize costs, deploy applications, audit security, manage Helm charts, and visualize dashboards—all through natural language. - What Can You Do? - Why kubectl-mcp-server? - Live Demos - Installation - Quick St

� Migrate to MCP Platform • 💬 Discord Community • � Legacy Docs Zero-configuration deployment of production-ready MCP servers with Docker containers, comprehensive CLI tools, and intelligent caching. Focus on AI integration, not infrastructure setup. That's it! Your MCP server is running at http://localhost:8080 Perfect for: AI developers, data scientists, DevOps teams building with MCP. Deploy M

Deploy applications and websites to Vercel. Use when the user requests deployment actions like "deploy my app", "deploy and give me the link", "push this live", or "create a preview deployment".

Batch process books through the complete pipeline - generate cropped images for split pages, OCR all pages, then translate with context. Use when asked to process, OCR, translate, or batch process one or more books.

A Model Context Protocol (MCP) server implementation for 4EVERLAND Hosting enabling instant deployment of AI-generated code to decentralized storage networks like Greenfield, IPFS, and Arweave. The 4EVERLAND Hosting MCP Server enables users to leverage AI-driven workflows to deploy code instantly to decentralized storage networks such as Greenfield, IPFS, and Arweave. Upon deployment, it provides

mcp-k8s-eye is a tool that can manage kubernetes cluster and analyze workload status. - [x] Connect to a Kubernetes cluster - [x] Generic Kubernetes Resources management capabilities - Support all navtie resources: Pod, Deployment, Service, StatefulSet, Ingress... - Support CustomResourceDefinition resources - Operations include: list, get, create, update, delete - [x] Pod management capabilities

A Model Context Protocol (MCP) server that allows interacting with the CipherTrust RestFul Data Protection (CRDP) service. This MCP server enables AI applications and LLMs to securely protect and reveal sensitive data through the CipherTrust CRDP service. It supports both individual and bulk protect and reveal operations with versioning support. - Video 1: [https://youtu.be/O2pQRoykaaU] - Deployme

A remote Model Context Protocol (MCP) server that connects AI assistants to your crash reporting and real user monitoring data in Raygun through natural language conversations. 📚 Tool Reference • 🚀 Quick Start • 🔑 Get API Token - 🐛 Error Management - Investigate, resolve, and track application errors and crashes with full stack traces and context - 🚀 Deployment Tracking - Monitor releases and

A Postgres MCP server with index tuning, explain plans, health checks, and safe sql execution. Overview • Quick Start • Technical Notes • Related Projects • Postgres MCP Pro is an open source Model Context Protocol (MCP) server built to support you and your AI agents throughout the entire development process—from initial coding, through testing and deployment, and to production tuning and maintena

Master end-to-end testing with Playwright and Cypress to build reliable test suites that catch bugs, improve confidence, and enable fast deployment. Use when implementing E2E tests, debugging flaky tests, or establishing testing standards.

You are a configuration management expert specializing in validating, testing, and ensuring the correctness of application configurations. Create comprehensive validation schemas, implement configurat

Execute database migrations across ORMs and platforms with zero-downtime strategies, data transformation, and rollback procedures. Use when migrating databases, changing schemas, performing data transformations, or implementing zero-downtime deployment strategies.

A comprehensive security operations platform that integrates multiple security tools into a unified interface. This platform provides a centralized way to run various security scanning and testing tools. - Unified Interface: Single entry point for multiple security tools - Docker Support: Easy deployment using Docker - JSON Output: Consistent JSON output format across all tools - Error Handling: R

Master Django 5.x with async views, DRF, Celery, and Django

Build GitLab CI/CD pipelines with multi-stage workflows, caching, and distributed runners for scalable automation. Use when implementing GitLab CI/CD, optimizing pipeline performance, or setting up automated testing and deployment.

Act as an expert senior Elixir engineer.