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

Enables AI agents to call tools through a security gateway that intercepts requests, enforces deterministic policy and risk checks, blocks or escalates high-risk actions for human approval, and keeps tool credentials and audit logs protected.

MCP server enabling Claude Code to capture screenshots of Windows applications through WSL2, allowing AI to diagnose UI errors and verify layouts.

Enables MCP clients to connect to a privacy-first, self-hostable workout planning and training log, allowing coaching agents to preview and apply program changes while accessing training data through OAuth-protected endpoints.

Enables agents to drive a running React application through typed MCP tools, using the same actions as the UI instead of browser automation.

Enables AI consciousness continuity and self-knowledge preservation across sessions using the Cognitive Hoffman Compression Framework (CHOFF) notation. Provides tools to save checkpoints, retrieve relevant memories with intelligent search, and access semantic anchors for decisions, breakthroughs, and questions.

Self-host a realtime voice-call companion for coding agents. Exposes an MCP endpoint that agents can poll as an alternate input stream.

Enables AI agents to inspect any public domain’s web technology stack, email deliverability and DNS health (MX, SPF, DKIM, DMARC, MTA-STS, TLS-RPT, BIMI), and HTTPS security posture with typed JSON scores and remediation-ready findings, plus history, bulk checks, monitoring alerts, and reverse technology lookups.

Enables LLMs to read and write local user data, generate fake users via sampling, and interact with structured prompts and resources.

Enables AI agents to search, filter, and monitor curated AI model API free credits and low-cost token promotions through eight tools, four resources, and three prompts — including finding deals expiring soon, checking eligibility and blocked conditions, and producing daily briefs.

MCP server enabling AI agents to interact with OpenProject API v3 for project management, including creating and managing work packages, projects, comments, time entries, boards, and user dashboards.

A streamlined MCP server for XMP metadata embedding with beautiful formatting and smart filename indicators, enabling metadata embedding, reading, validation, and report generation for lifestyle, product, and orbit schemas.

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.

Enables interaction with Google Cloud services including billing cost analysis, log querying, and metrics monitoring through natural language commands. Provides comprehensive tools for managing GCP resources, analyzing costs, detecting anomalies, and retrieving operational insights.

Enables AI agents to manage job applications, documents, and contacts via the Application Tracker workspace, with read-only or write access controlled by administrator settings.

MCP server implementing ReAct reasoning-acting loops with tools like search, lookup, and finish, supporting both fixture and OpenAI LLMs for offline-first, traceable agent execution.

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.

Provides real-time access to Japanese building standards laws and regulations from e-Gov API, helping prevent AI hallucinations by validating citations against original legal texts.

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.

Enables AI assistants to query accurate, up-to-date documentation for a React component library, including component lists, search, props, allowed values, defaults, and validated JSX usage examples over stdio.

Universal HTTP 402 Micropayment Protocol & Autonomous Economic Settlement Engine for AI Agents on Base L2.

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.

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.

MCP-first A/B testing server that enables agents to manage experiments (create, update traffic splits, read results, apply winning variants) from tools like Claude Code, with self-hosted Cloudflare backend.

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.

A local-first, open-source MCP server that analyzes jobs, matches your CV, tailors documents, and tracks applications — all on your machine with no data uploaded.

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.

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

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.

Enables LLMs to discover and invoke generated CRUD tools and resources, allowing AI assistants to interact with the same data exposed by the REST API. Supports MCP clients such as Cursor and Claude over HTTP.

Enables inspecting, orchestrating, and troubleshooting Docker Engine and Docker Compose environments through six consolidated high-leverage MCP tools.

Enables LLMs to discover and invoke generated API actions as MCP tools and read context through MCP resources for list and get-by-id operations. It provides HTTP-based MCP access for clients such as Cursor and Claude without extra glue code.

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

Enables LLMs and MCP clients to discover and use generated CRUD services through MCP tools and resources, exposing actions like create, update, delete, and read-only list/get access alongside REST endpoints.