"Building and Deploying a React Application with Docker and a Postgres Backend" matching MCP servers:

A FastAPI-based MCP server orchestrated with Docker Compose, integrating Redis caching and TimescaleDB for time-series data management.

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.

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.

Relays a result screenshot to Slack so you can review a coding agent's output without opening the app.

Enables AI assistants to explore a PostgreSQL database, run bounded read-only SQL, inspect query plans, test hypothetical indexes, find slow queries, and check database health with compact CSV output.

MCP server providing backend access to PostgreSQL, Storage (Supabase/S3), Iceberg data lake, and SQL seeds. It offers 32 tools for database queries, storage operations, seed management, and more.

Enables AI agents to break down complex tasks into manageable pieces using a structured JSON format with task tracking, context preservation, and progress monitoring capabilities.

A wrapper for mcp-remote that provides secure authentication for protected MCP servers using Adobe IMS or Okta OAuth flows. It features automated token management, validation, and background refreshing for seamless access to remote resources.

It enables AI assistants to discover and invoke CRUD operations as MCP tools and read application data through MCP resources, allowing natural-language interaction with the generated backend.

An MCP Server that provides a conversational interface to the UK Open Banking account information API, allowing agents to interact with bank account data through natural language commands.

Wraps the Docker Engine API as MCP tools for container and image management. Reduces token consumption by providing typed tools with default summaries and field selection.

MCP server providing AI coding assistants with documentation and source code for @gaddario98 React packages, including tools for listing packages, retrieving docs and types, and searching source.

A Postgres MCP server with index tuning, explain plans, health checks, and safe SQL execution for AI agents.

An MCP server that runs parallel AI agents to analyze React components for performance issues, including unnecessary re-renders, memoization errors, bundle size problems, and profiling concerns.

Postgres 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 maintenance.

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.

Allows Claude and other AI assistants to interact with Docker through the MCP protocol, enabling container and image management including listing, running, stopping, and pulling Docker resources.

Provides AI agents with accurate, version-aware documentation for React Native, Expo, React Navigation, and Ignite by automatically detecting project dependencies and fetching matching documentation.

Enables an AI agent to run and inspect containers, build and pull images, manage volumes and networks, drive Compose projects, clean up, and run self-checking practice labs. Startup modes restrict it to read-only, labs-only, or full Docker control with confirmation before dangerous operations.

Connects AI agents to a running React Native app so they can see the screen, tap and type, and inspect logs, network traffic, and state without any SDK or code changes. Composite tools let an agent run a whole interaction flow in a single call instead of one round trip per tap.

A powerful Model Context Protocol (MCP) server for Docker operations, enabling seamless container and compose stack management through Claude AI.

An MCP server that connects to your React Native application debugger

Provides AI agents with visibility into React applications by exposing tools to inspect component state, props, and performance metrics. It enables debugging and state analysis for both web and React Native applications through the Model Context Protocol.

Enables LLMs to search Docker Hub repositories, discover container images, and manage Docker Hub repositories and tags through natural language queries. Supports both public content access and authenticated operations with Docker Personal Access Tokens.

Enables LLM clients such as Cursor and Claude to discover and use generated REST services through MCP tools for create, update, and delete actions and MCP resources for list and get-by-id context. Services generated in one command are exposed simultaneously as REST endpoints and MCP tools and resources.

A Docker-managed MCP server for analyzing React codebases and generating component documentation from mounted workspaces. It enables users to scan projects, analyze JSX/TSX strings directly, and generate Markdown docs while ensuring safe path handling.

Enables AI assistants to manage Docker containers, deploy stacks, and monitor services across multiple Docker hosts from one centralized location. Supports container lifecycle management, Docker Compose operations, and infrastructure orchestration through natural language commands.

Enables read-only inspection and narrowly scoped maintenance of a local Docker Desktop environment, covering containers, images, logs, stats, Compose status, and Scout vulnerability/SBOM data, plus limited actions such as image pulls, container restarts, dangling-image pruning, and allowlisted Compose redeploys, all without exposing the raw Docker socket to the client.

Enables AI assistants to interact with generated REST APIs by discovering and using CRUD tools and read-only data resources.

Enables AI assistants to discover and invoke CRUD tools and read-only resources over the Model Context Protocol for generated API services.

A Model Context Protocol server that provides tools for interacting with Docker images, containers, and registries, enabling AI assistants to search, analyze, and manage Docker resources through a standardized interface.

A comprehensive MCP toolkit for Java backend developers, providing 35 tools across 5 servers for database analysis, JVM diagnostics, migration assistance, Spring Boot monitoring, and Redis diagnostics.

Enables AI agents to inspect why React components re-rendered, replay recorded browser interactions as performance scenarios in headless Chrome, and verify fixes against performance budgets.

Enables AI assistants to interact directly with generated REST APIs by exposing CRUD operations as MCP tools and read-only data as resources.

Enables read-only, SELECT-only querying of any Postgres database through MCP-compatible clients like Claude, with schema introspection and guarded SQL execution.

Enables retrieval of compact APG pattern cards, such as button, modal, and dialog, through an MCP tool so clients can consult accessibility guidance.

Exposes generated CRUD services to LLM clients over the Model Context Protocol, providing tools for create, update, and delete actions plus read-only resources for listing and fetching records by id. It lets assistants like Claude, ChatGPT, and Cursor discover and manipulate the same data served by the project's REST endpoints without any extra glue code.

Exposes every generated CRUD service to LLM clients such as Claude, ChatGPT, or Cursor through discoverable MCP tools for create, update, and list actions plus read-only resources, so models can query and manipulate data without raw HTTP calls. It runs alongside the same codebase's REST endpoints, letting clients and AI share one data layer.

Enables LLMs to discover and invoke generated CRUD operations as MCP tools and read data through MCP resources, alongside standard REST endpoints, using one codebase.