"Understanding Frontend and Backend Development" matching MCP servers:

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

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.

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.

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.

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

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

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.

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

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 control and management of smart home devices across multiple rooms through specialized MCP servers. Supports lights, thermostats, fans, and ovens with room-specific rules and automatic persistence.

An MCP server that visually reviews UI edit requests by comparing screenshots before and after edits, ensuring changes satisfy user requests.

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

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

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 visual review of UI edits by comparing before and after screenshots, returning whether the edit satisfies the request.

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.

Enables structured dynamic analysis of authorized Windows processes via Cheat Engine 7.7, exposing bounded tools for process inspection and debugging without arbitrary code execution or memory writes.

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.

Enables AI agents to perform read-only static analysis of Node.js backend projects, detecting database query anti-patterns, async bottlenecks, connection pooling mistakes, and dependency hygiene issues while returning structured evidence-backed findings.