"How to generate HTML code from Figma design files" matching MCP servers:

A runtime-free MCP server that converts source code into AST🌲, regardless of language.

Enables AI coding agents to extract Figma design data and convert it into Flutter widgets and screens. Supports theme setup, component analysis, asset exports, and provides Flutter implementation guidance from Figma designs.

Visual tech-stack inventory of any codebase: languages, frameworks, databases, AI SDKs, infra.

This MCP server renders UI design artifacts headlessly, runs deterministic linters, and manages stateful design review loops with an independent vision critic.

Enables high-craft web design and engineering through OKLCH color systems, fluid typography, Three.js 3D scenes, frontend security audits, multi-viewport capture, and Python-backed design verification.

Provides access to Ant Design component library documentation and information for automated code generation. Enables searching components by category or keyword, retrieving component props, examples, API documentation, and available icons.

Provides software design guidance via MCP, including SOLID principles, design patterns, pattern scaffolding, and heuristic code-smell detection to help review and refactor code.

An MCP server that provides design-pattern selection expertise to AI coding agents.

Enables mapping Figma designs to a project's own component library — shadcn/ui, antd, mui, or Astryx — by resolving variants against authoritative component contracts instead of guessing. It compiles Figma nodes into code and then deterministically writes the resulting files into the codebase, cleaning node-id artifacts and updating exports.

Enables Claude to list directories, read text files, and search code within a designated read-only project folder, while skipping common dependency folders and blocking sensitive files.

Enables AI coding tools like Cursor to access Figma design data through the Model Context Protocol, allowing accurate implementation of designs across frameworks. Based on NCDS (NHN Commerce Design System) with enhanced source generation capabilities.

Enables AI assistants to discover, document, and generate React code using the pastel-themed Baby Design UI component library. It provides tools for retrieving design tokens and component specifications to streamline the development of user interfaces.

MCP server for persistent code exploration and diff-aware review, exposing explore and review tools to map call paths, blast radius, and generate explainable risk-scored reports.

Enables AI coding agents to submit code, files, or diffs for deterministic checks and optional re-verified LLM repair, returning cleaned code, structured findings, and a pass/fixed/reject verdict.

MCP server with local vector search for your codebase. Smart indexing, semantic search, Git history — all offline.

embedded code search engine CLI -AST based that just works - improves speed and efficiency for coding agent

An MCP server that provides dynamic codebase context to Claude Code through tools like hybrid search, recent changes, and symbol definitions, enhancing AI-assisted coding with local RAG.

Wraps Claude Code's code-review skill so any MCP client can run reviews over a PR, branch, working directory, or last commit, with five parallel reviewer subagents, low-to-max effort levels, and optional fix mode that edits files in place. Also supports follow-up questions on a previous review session and a free environment self-check.

Gemini-powered MCP server for automated code review, analysis, and documentation.

Enables efficient codebase exploration with tools to list exports, get file outlines, read targeted regions, and find references without loading entire files.

An MCP server for intelligently reading Java source code, supporting extraction from Maven dependencies and local projects with dual decompilers.

Indexes a mono-repo into a knowledge graph and provides MCP tools to query code structure—packages, components, routes, HTTP calls—without file reads or grep round-trips.

Enables agents to run semantic search across one or more local project directories by automatically maintaining a LAN-local Qdrant index with Ollama embeddings. Indexing, staleness checks, and incremental updates happen transparently, so users can query code by meaning without managing collections, chunks, or hashes.

Checks a code repository without running it: Safe, Works and Complete scores with an A-F grade, catching leaked keys, dangerous calls, invented or lookalike packages, broken imports and missing project files. Standard-library Python; MCP tools scan, orphans and explain.

AI-powered continuous code assistant for Cursor, VS Code, Antigravity, and Claude Code via MCP, providing tools for code review, testing, documentation, and quality analysis.

Connects Kimi Code with Claude Code, enabling Claude to delegate bulk codebase reading to Kimi (256K context) for cost savings, while Claude focuses on reasoning and code edits.

Provides structural, queryable understanding of a Python codebase via MCP tools, enabling direct lookups for callers, dependencies, and class hierarchies without repeated grep/read cycles.

Enables AI coding assistants to generate, score, run, and auto-heal Playwright E2E tests while enforcing domain-driven page object architecture and anti-flakiness rules.

Enables AI assistants to perform comprehensive code reviews of local uncommitted changes by combining git diffs with static analysis from linters like ESLint and TypeScript. Returns structured JSON feedback with findings, suggestions, and quality assessments powered by Google's Gemini CLI.

Strict AI code reviewer powered by Groq. Finds bugs, vulnerabilities and security issues in your code. Supports analyze, compare versions, explain code, generate tests, and HTML reports.

Enables AI coding agents to perform fast regex/text and structural AST searches across codebases, find symbols, list files, and safely preview or apply refactors. It unifies ripgrep and ast-grep with pagination, gitignore-aware defaults, and fallback engines for zero-setup code search.

Enables AI assistants to search, analyze, and understand multi-language codebases by providing indexed code intelligence via MCP.

A self-hosted semantic code retrieval MCP server that enables natural language queries to find relevant code snippets using Tree-sitter AST parsing, embedding, and hybrid search with reranking.

A production-grade MCP server for the Code-Fundi API, enabling AI agents to map codebases, search semantically, and analyze blast radius. It provides tools for repository management, AI-powered research, and impact analysis before shipping changes.

Enables agents to quickly find and edit code in a codebase with surgical precision. Find symbols, edit them everywhere with tools for reading code blocks, searching/replacing text, and making precise line-based modifications.

A persistent, Git-versioned map of your whole codebase and database schema that coding agents read before they touch anything. Local-first MCP server + CLI in Go: a governed repository index of code knowledge that gives Claude Code, Codex, Cursor, and opencode long-term context, memory, and code intelligence.

Enables comprehensive code analysis including quality assessment, security vulnerability detection, refactoring suggestions, complexity calculations, and automatic documentation generation for multiple programming languages.

An MCP server that indexes source code into a local database and provides tools for querying code symbols, dependencies, and tree structure for JavaScript/TypeScript, Java, and Python.

Enables LLMs to efficiently read, write, and refactor code using precise AST-based operations, reducing token usage and context window waste.

Enables auditing codebases for production readiness, including linting, testing, CI/CD, security, branch conventions, architecture, and an A–F quality scorecard via MCP tools.