"A guide on how to deploy a web app" matching MCP servers:

A validation layer for AI coding assistants that enforces explicit LLM evaluations on plans, code diffs, and tests to ensure safer and higher-quality code.

Enables coding agents to add a bounded semantic-judgment layer for routing, ranking, extraction, verification, and escalation, returning typed signals and review recommendations.

Provides over 1,000 creative ways to decline requests across four categories (polite, humorous, professional, and creative). The MCP server wraps a REST API to help users craft professional rejections through natural language interactions.

Enables AI agents to access and manage project guidelines, documentation, and context through a structured content system with template support and workflow management.

A beginner-friendly Model Context Protocol (MCP) server that helps users understand MCP concepts, provides interactive examples, and lists available MCP servers. This server is designed to be a helpful companion for developers working with MCP. Also comes with a huge list of servers you can install.

Enables AI coding assistants to deploy websites directly to Vercel from the IDE, automating framework detection, build validation, and secure environment variable synchronization, with live status updates.

An MCP server that enables AI coding agents to deploy files to FTP/FTPS/SFTP servers, with path jail, read-only mode, and dry-run capabilities.

MCP server for deploying projects to multiple cloud platforms (Vercel, Railway, Neon, MongoDB Atlas, Docker) and running local dev servers, with orchestration for full-stack deployments.

Enables agents to deploy software via GitHub Actions only with a signed receipt, providing gated tools to resolve refs, list deployments/environments, and dispatch pipelines for a specific commit.

Enables automated deployments, environment management, snapshots, and deployment monitoring through DevOps Deploy's REST API.

Provides access to clean code guide documents and enables code quality inspection of external project files based on coding standards and best practices.

Allows AI assistants to deploy static frontend directories to Surge.sh via a single command, without requiring local Surge installation.

A server that enables interaction with Octopus Deploy through the Model Context Protocol, allowing users to manage projects, releases, and deployments across different spaces.

Enables inspecting ONNX models, probing the deployment environment, and benchmarking inference latency and FPS either locally or on remote SSH targets such as Linux workstations and Jetson devices. Benchmark results are validated against FPS, P95 latency and model-size constraints to produce PASS/FAIL deployment gates.

Enables MCP clients to connect to a streamable HTTP server with multiple tools, secured by API key authentication, rate limiting, and health checks via an nginx gateway for Docker-based deployment.

An MCP server that helps Claude design, scaffold, and validate MCP servers compatible with the mcp-deploy platform, enabling seamless creation and deployment of new MCP workers.

Enables AI assistants to manage website deployments over SFTP/FTPS by listing sites, testing connections, comparing files, previewing changes with approval tokens, creating SHA-256 verified backups, and executing authorized uploads.

Enables one-click deployment of static websites and HTML files to IPFS through Pinme. Automatically detects common build directories (build, dist, out, .next), uploads to IPFS, and provides ENS URLs for accessing deployed sites.

Provides comprehensive design principles and best practices to help LLMs generate modern, accessible web pages through guidance on layouts, colors, and typography. It enables users to review design approaches and access expert recommendations for responsive design, component structure, and current industry trends.

Enables searching and retrieving content, module information, and Twig template snippets from a-blog cms via its GET API.