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

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.

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

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.

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 querying documents through a Langflow backend using natural language questions, providing an interface to interact with Langflow document Q\&A flows.

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.

* analyze your react projects locally * consistent output w/ AST parsing + AI * create markdown docs, llm.txt for your react code at once

A minimal MCP server that enables searching through pre-scraped React documentation using a hybrid approach combining DuckDB full-text search and transformer-based reranking.

Provides AI coding assistants with access to ITK Dev Docker documentation and project analysis tools, enabling template listing, project detection, and comparison.

A Python-based MCP server that enables document-based question answering by processing PDF, TXT, and Markdown files through OpenAI's API. It provides hallucination-free responses based strictly on document content using semantic search and includes a web interface for management.

Enables document-based question answering using OpenAI's GPT-4 with semantic search and embeddings. Upload PDF, TXT, or Markdown files and get answers strictly based on document content with source attribution and confidence scores.

Enables AI-powered semantic search over React Hook Form documentation, allowing users to query and retrieve relevant documentation pages without an API key, running locally with offline support.

Enables AI agents to perform semantic search over React Native documentation, retrieve specific pages, and manage doc versions locally without API keys.

Provides component information, usage guidelines, and code generation for AWS Cloudscape Design System in React, with search and pattern library capabilities.

Indexes the locally-installed @trussworks/react-uswds package and helps code assistants discover components, inspect props, generate correct imports and usage snippets, and suggest appropriate components for UI use cases.

Provides comprehensive documentation search for Next.js 15+ and Tailwind CSS 3+, along with 27 production-ready Catalyst UI components and 13 design patterns for building modern web applications.

Enables intelligent access to React Native Godot documentation, examples, API references, and troubleshooting guides through searchable tools optimized for LLM workflows.

Provides AI assistants offline fuzzy search, precise section retrieval, and section listing over bundled mobile-development documentation, enabling natural-language lookups of components, hooks, guides, and best practices.

Enables AI assistants to search and retrieve documentation, component specs, theme guides, and CLI commands for the Meta Astryx Design System, providing structured tools and guidelines for coding agents.

Enables users to search and navigate over 22,500 indexed sections across 16 Canadian building codes and user guides. It supports keyword searches, hierarchy navigation, and optional full-text extraction from user-provided PDF documents.

Provides access to developer roadmap content from roadmap.sh, allowing users to list available roadmaps and fetch detailed Markdown content for specific career paths.

Provides AI assistants with access to OpenAPI specifications, enabling API discovery, schema retrieval, and direct API execution with support for OAuth 2.0 and other authentication methods.

MCP server that enables AI assistants to drive systematic literature review workflows, including screening, downloading, converting, and reviewing papers through natural language conversation.

An HTTP MCP server that indexes large documents into exact-line-numbered sections, enabling AI models to locate, read, summarize, and edit parts of a document without ingesting the whole file.

Enables AI assistants to interact with OpenAPI documents for analysis, validation, and management through structured interfaces.

MCP server that enables introspection of any MCP server's registered tools by exposing mcpreg/list, mcpreg/get, and mcpreg/query tools, making tool registry accessible even when the underlying SDK lacks list_tools().

A collection of MCP servers for Slack, Jira, Confluence, and release coordination to automate QA workflows and daily release status reporting.

Enables Claude to read and analyze PDF documents with automatic OCR processing for scanned files. Features intelligent text extraction, caching for performance, and secure file access with search capabilities.

Enables interactive AI chat through the Anthropic API, with document retrieval, slash commands, and extensible MCP tool integrations.

Enables querying Kapa.ai's documentation and Q&A capabilities for any project enrolled with Kapa, with tools for asking questions and searching sources.

Enables hybrid search (BM25 + semantic with RRF) over documentation, with Thai language support. It exposes MCP tools for adding documents and searching via Qdrant and Ollama/OpenAI, using a stateless Streamable HTTP transport.

Enables users to list, search, and read official versioned PostgreSQL documentation, including archived, beta, and development releases, and retrieve pages as Markdown.

An MCP (Model Context Protocol) server that turns the book Deep Learning with Python (François Chollet) into a searchable knowledge base, so Claude can act as a deep-learning/ML expert grounded in the book's content.

Provides AI assistants with current Ionic Framework v9 and v8 documentation, including component API references, usage examples for Angular, React, Vue, and vanilla JavaScript, and Ionic blog posts. Enables searching docs, reading pages, listing components, retrieving usage examples, and listing blog posts.

MCP server providing on-demand access to official prompting guides for building robust meta-prompts.

Enables AI coding agents to search, read, and cite official Workday developer documentation, grounding their answers in real docs instead of hallucinating. Particularly useful for building Workday Extend apps.

Explains known developer errors offline and deterministically (CORS, ESM/CommonJS, npm ERESOLVE, Next.js builds, Postgres connection and DATABASE_URL errors). One tool, explain_error; no LLM, no network.

Fresh, source-verified docs for building MCP servers and Claude agents, served to your AI coding agent over MCP. Each document is stamped with its source URL and last-verified date.

Enables TF-IDF search and structured browsing of Sisense Compose SDK documentation for React, Vue, and Angular, with support for framework filtering and code context to find relevant code examples.

Gemmein is the backend for AI-powered products: sign-in, data under seven access rules, AI tools priced in credits, and payments through Stripe, a relay, or RevenueCat. The @gemmein/mcp server gives a coding agent that whole contract as tools: the builder guide, the SDK reference, doc search, rule and error explainers, and check_integration, a live check of an app's access boundaries.