"Design Resources and Prototyping Best Practices" matching MCP servers:

AI-powered Odoo engineering platform providing static analysis, domain knowledge, and 14 MCP tools for code review, model exploration, and security auditing of Odoo modules.

Enables Claude to interact with R package development workflows, including CRAN metadata lookup, dependency checking, testing, documentation validation, and release automation.

Monitor failing GitHub Actions workflows, auto-fix them with OpenCode, and retry the run — driven by a workflow_run webhook, coordinated through an MCP server.

Enables AI assistants to summarize Playwright test runs, identify flaky tests, heuristically triage failures, generate Playwright test stubs, and retrieve recent GitHub CI status through MCP tool calls.

Verifies AI agent completion claims by checking that claimed output files exist and are fresh, acting as a lightweight physical telemetry gate.

A feature-complete TypeScript project template for rapidly developing Model Context Protocol tools with integrated best practices for code quality, testing, and automated deployment.

An MCP server that automates CI/CD pipeline creation, analysis, and security enforcement. It generates production-ready pipelines from templates and enforces DevSecOps best practices.

A code quality MCP server with 22 tools for deterministic linting, formatting, security scanning, and AI-assisted improvements, designed to reduce cloud LLM costs and enforce best practices.

An MCP server that enforces development discipline and workflow best practices, guiding users through a structured process of coding, testing, documenting, committing, and releasing.

AI code review against your team's own rules from your repository, before the pull request: two tools, review_changes and get_team_rules. Closed-source binary distributed via GitHub Releases; published in the official MCP Registry as dev.reviewgate/reviewgate.

An MCP server that lets AI assistants manage KubeAid GitOps clusters, inspecting ArgoCD apps, pods, events, and resources, with optional write operations like syncing apps and scaling deployments through your own kubeconfig credentials.

Enables AI assistants to deploy and manage SnapDeploy containers and resources—including builds, logs, environment variables, databases, and custom domains—directly through natural language.

An MCP server designed for React Native and Expo development that provides specialized tools for project scaffolding, architectural best practices, and troubleshooting. It enables AI assistants to guide users through setup, navigation configuration, and CI/CD processes using modern stacks like NativeWind and Zustand.

An MCP server that lets coding agents take a SwiftUI iOS subscription app from idea to the App Store, covering research and validation, design, code scaffolding, Supabase backend, App Store Connect and RevenueCat setup, localization, analytics, ASO, screenshots and TestFlight, with approval gates on irreversible actions and human-only submission.

Enables management of Railway.app infrastructure through natural language, including deploying services, managing environment variables, monitoring deployments, and controlling project resources.

Enforces disciplined programming practices by requiring AI assistants to audit their work and produce verified outputs at each phase of development, following structured workflows for refactoring, feature development, and testing.

An MCP (Model Context Protocol) server that integrates with the ArgoCD API, enabling AI assistants and large language models to manage ArgoCD applications and resources through natural language interactions.

Enables real-time assessment of GitHub repository health by exposing tools and resources for repository metadata, open issues, recent commits, and GitHub Actions workflow runs, plus prompts for health reports and issue triage.

An MCP server implementing a 7-stage agentic frontend workflow—from design audit to PR review—including AI-driven component generation, browser validation, E2E testing, and CI self-healing.

Enables AI assistants to inspect, query, and diagnose problems within Octopus Deploy instances. Provides read-only access to deployments, releases, projects, environments, and other DevOps resources to transform AI into your ultimate DevOps wingmate.

Enables AI assistants to interact with Argo CD through its REST API, providing tools to triage application status, sync, roll back, inspect drift, read logs, and manage ApplicationSets, clusters, projects, and repositories. Supports read-only safeguards, curated GitOps resources, and workflow prompts for safe operations.

An MCP server that enables AI-powered IDEs to implement a structured development workflow from requirements gathering to code implementation, guiding users through goal collection, requirements specification, design documentation, task planning, and execution.

Enables interaction with a self-hosted Woodpecker CI v3.20.1 REST API through official /api JSON, covering system status, repositories, pipelines, and related resources. Supports read operations plus gated write actions such as triggering, canceling, and managing pipelines and secrets.

Enterprise-grade MCP server exposing Ansible Automation Platform 2.x as a complete AI interface for LLMs, enabling natural language management of automation resources.

Automates GitHub issue-to-PR workflows using specialized AI agents (analyst, architect, developer, tester, reviewer) that analyze requirements, design solutions, implement code, generate tests, and perform code reviews with HIPAA compliance checks.

A Python MCP server that wraps the GitHub CLI (gh) to provide structured tools for searching, reading, and managing GitHub resources like repos, issues, PRs, releases, and workflows, with write commands disabled by default.

MCP server for Laravel Cloud to manage projects, environments, deployments, and other resources.

Enables AI assistants to interact with and manage Google Cloud Platform resources including Artifact Registry, BigQuery, Cloud Build, Compute Engine, Cloud Run, Cloud Storage, and monitoring services through a standardized MCP interface.

A Model Context Protocol server that enables AI assistants to interact with Azure DevOps resources including projects, work items, repositories, pull requests, branches, and pipelines through a standardized protocol.

An MCP server for Infrastructure as Code that enables AI assistants to manage cloud resources through Ansible and Terraform operations. It supports executing playbooks, managing AWS services, and running Terraform commands with optional LocalStack integration.

Enables management of App Store Connect resources including app reviews, TestFlight crashes, analytics reports, and Xcode Cloud workflows through natural language or AI agents.

A Model Context Protocol server that provides tools and resources for Java CI/CD workflows and GitLab CI template management.

Enables programmatic management of Koyeb resources including apps, services, deployments, and instances via the Model Context Protocol. It allows users to query build and runtime logs and perform resource lifecycle operations through the Koyeb API.

Enables AI agents to create, deploy, and manage Netlify projects and resources using natural language via the Netlify API and CLI.

Provides complete control over Dokploy infrastructure with 463 tools for managing projects, applications, databases, and Docker containers. It enables users to deploy and configure their self-hosted PaaS resources directly through natural language.

MCP server plugin for the tsdevstack CLI, enabling AI agents to manage infrastructure, deployment, and project state with 54 tools and 12 resources.

Enables AI assistants to interact with Bitbucket repositories, pull requests, and related resources through the Bitbucket Cloud and Server APIs. It supports operations such as listing repositories, retrieving repository details, and fetching or creating pull requests.

Karpenter is a Kubernetes Node Autoscaler built for flexibility, performance, and simplicity.

A production-ready template for building Model Context Protocol (MCP) servers in Python, using Docker Compose for containerized development and CI/CD.

Enables AI assistants to interact with Bitbucket Cloud and Server APIs, including listing and retrieving repositories, fetching pull requests, creating pull requests, and managing related resources safely without DELETE operations.