"Understanding Frontend and Backend Development" matching MCP servers:

MCP server for multimodal understanding and object grounding (bounding boxes) across images, videos, and documents, with support for multiple AI providers (Zhipu GLM-V, OpenAI GPT-4o, Anthropic Claude, or any OpenAI-compatible endpoint).

Enables AI agents to maintain persistent, inspectable understanding through typed, revisable updates, and to coordinate multi-agent work via shared graph-based stigmergy.

Enables AI tools to interact with browsers for enhanced frontend development, providing context to LLMs through tools like API call analysis, screenshots, element selection, and documentation ingestion.

An MCP server that provides tools for frontend development, including i18n issue detection, OpenAPI type generation, and project structure analysis.

Saves the user's exact words as immutable, SHA-256-hashed captures before anything else, then derives events, entities, context cards, and causal hypotheses — every fact traceable to its verbatim source. Local-first personal memory for Claude Code, Codex, and any MCP client.

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.

A zero-dependency local MCP server that audits and auto-fixes React/Next.js frontend code smells, unused imports, and responsive UI issues

Enables users to turn GIFs, local videos, and Bilibili videos into timestamped, queryable, and verifiable frame evidence and event timelines, while passing extracted frames to the current session's model instead of calling an external vision API.

Enables coding agents to load frontend anti-slop rules and deterministically verify generated React, Next.js, and Tailwind UI before completion. It audits for common AI-generated patterns, checks stylesheet/token wiring, provides real or placeholder images, and verifies TypeScript compilation.

A zero-dependency Node.js playground for debugging how MCP clients authenticate to an MCP server over HTTP.

Enables frontend navigation and browser automation through a deterministic MCP server, integrating Browser Use and optional code graph hints for coding agents.

Enables coding agents to visually verify front-end changes by capturing screenshots at real breakpoints, identifying the single element responsible for overflow, and surfacing console and network errors.

Provides AI assistants with frontend development tools including component scaffolding, bundle analysis, accessibility checks, and responsive design guidance. Enables automated generation of React components with tests and stories, bundle optimization recommendations, and WCAG compliance fixes.

A comprehensive MCP server for frontend analysis. It provides Google Lighthouse audits, code quality checks, SEO metadata verification, accessibility analysis, and bundle optimization for React and Next.js projects.

Enables local video inspection and offline transcription with timestamped JSON and Markdown output, enforced filesystem boundaries, and reproducible content-addressed caching.

Gives AI coding agents a ten-phase frontend design pipeline (audit, style direction, build, review, verify, perf, brand) with an exclusive style menu. Its verify_page tool loads a URL in a real Playwright browser at mobile and desktop viewports and returns screenshots, ARIA snapshots, console errors, failed requests, horizontal-overflow offenders, axe-core violations, and pointer type.

An MCP server that analyzes local or remote GitHub repositories, providing intelligent code context and structure to AI coding assistants.

Provides tools for frontend testing including code analysis, test generation, test execution, and React component testing for Jest and Cypress frameworks.

MCP server for Next2D application development that generates code following MVVM + Clean Architecture + Atomic Design patterns, validates architecture, and provides API references.

Exposes GOV.UK Frontend components and Design System patterns and styles as MCP resources for use with AI assistants.

Serves plain-text notes that an Obsidian user has explicitly published for AI over streamable HTTP, with full-text and embedding-based search. MCP clients can read and search those notes and queue suggested edits that the user's own client applies only if the AI rules allow it.

Enables AI assistants to retrieve NHS.UK frontend component templates, styles, macro options, and usage examples directly from the source repository.

A template for building MCP backends for lab equipment with an embedded Echo example for immediate testing and development.

Enables coding agents to load backend anti-slop rules and deterministically audit TypeScript/backend files for violations like SELECT *, SQL interpolation, N+1 calls, silent catches, stack leaks, type escapes, and TODOs, plus verify TypeScript compilation. Returns PASS/FAIL findings so agents can fix issues before shipping.

A Docker-based local RAG backend that provides advanced document search capabilities using vector, graph, and full-text retrieval via the Model Context Protocol. It supports over 28 file formats and tracks evolving relationships between concepts using a Neo4j-backed graphiti implementation.

Enables AI agents to read Microsoft Fabric lakehouse or warehouse tables, infer keys and relationships, and create or update a GraphQL API item — returning a ready endpoint for Lovable, Cursor, or Claude Code. It also plans and validates schemas and drafts companion artifacts such as semantic models, dbt sources, join paths, and data dictionaries, with dry-run defaults.

Enables AI agents to interact with both frontend and backend projects by providing file system access and context through the MCP protocol, facilitating full-stack development assistance.

An all-in-one development toolkit that integrates 10 popular MCPs with comprehensive features for solo developers, supporting frontend, backend, mobile development, database management, testing, and deployment automation.

Integrates Xiaomi MiMo's multimodal API to enable understanding of images, audio, and video through natural language prompts.

Enables AI coding agents to search public design-system catalogs and retrieve only the relevant tokens or sections for a chosen brand, so generated UI matches a specified visual style instead of generic AI output.