"Resources and Tools for Frontend Development (e.g., Jira, Figma, GitHub)" matching MCP servers:

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 Vue component development and Figma design restoration, featuring snapDOM-powered screenshots, pixel-perfect visual comparison, and automated SVG optimization.

Enables AI agents to interact with Jira and GitHub through MCP tools, including searching, creating, commenting on, and transitioning Jira issues and listing pull requests, summarizing diffs, creating issues, and commenting on GitHub.

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.

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

Web scraper and token compressor that converts HTML to clean markdown with 70-80% fewer tokens. Single-page compression and multi-page BFS crawling with auto-fallback fetch modes.

Enables creating Jira issues and listing issue types for a Jira Cloud project using Basic Auth credentials.

Enables AI agents to perform local video, audio, and file operations inside an isolated workspace, including cutting/concat videos, extracting audio, transcribing, and managing files, with typed responses and background job support.

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 AI assistants to discover, retrieve, and compare official international development indicators from sources such as the World Bank, FAOSTAT, WHO, UNICEF, and IMF, while preserving source identifiers, units, and citations.

MCP server that demonstrates the Resources feature by exposing static and dynamic resources, including contact data and personalized greetings, through MCP.

An async MCP server for JIRA integration, enabling AI assistants to search, create, and manage JIRA issues via JQL and other operations.

Enables issue search, creation, updates, comments, status transitions, and project listing in Jira, purpose-built for security incident management and SOC workflows.

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.

MCP server for Jira Cloud enabling issue tracking, comments, transitions, and attachments management through natural language.

MCP server for Jira Server/Data Center that enables issue retrieval, JQL search, comment posting, and Tempo worklog queries via the atlassian-python-api.

A local MCP server for Jira Cloud-driven development. Connects MCP clients to Jira for searching issues, reading tasks, parsing attachments, and mapping projects to local repos.

Enables listing top-level frames in a Figma file and fetching a selected frame's rendered PNG, node JSON, and image-fill map into a local output directory.

Allow your AI coding agents to access Figma files & prototypes directly. You can DM me for any issues / improvements: https://x.com/jasonzhou1993 1. Access all figma pages 2. Access all figma components 3. Access figma prototype flows

Pull a Figma frame once, then let Claude Code, Codex or any MCP agent read it offline with no rate limits. Six read-only tools serve the normalized node tree, design tokens and locally built SVG icons from a vault you can commit, so teammates need no Figma token.

A Model Context Protocol (MCP) server that provides tools for interacting with Jira. Enables Cursor and other MCP clients to fetch tickets, manage linked tickets, and update ticket status.

Enables AI agents to interact with Jira Cloud and Confluence through natural language, performing JQL searches, issue management, and Confluence page creation.

MCP server for seamless Jira integration with GitHub Copilot CLI, allowing natural language queries to search, view, and manage Jira tickets.

Converts Figma designs into structured code context with token-aware styling, enabling AI agents to generate production-level frontend code.

Converts Figma designs (frames, components, instances) into inspectable packets and static Unity UGUI YAML prefabs via the Figma REST API, enabling direct design-to-Unity asset generation.

An MCP server implementing a 7-stage agentic frontend workflow—from design audit to PR review—including AI-driven component generation, browser validation, E2E testing, and CI self-healing.

Transforms design inputs (URLs, screenshots, descriptions) into production-ready React components following G2's Elevate 2.0 design system, providing both an MCP server for Claude Code and a web interface.

Provides 8 MCP tools for frontend design: load design system, generate components, scaffold pages, review consistency, extract tokens, check WCAG 2.2 AA, test responsiveness, and export to Figma.

Enhanced Figma MCP Server that exposes prototype flow data — screen lists, prototype connections, and full flow maps — via the Figma REST API. Designed as a replacement for the official Figma MCP server, adding prototype interaction layer so Claude Code can understand entire user flows from a single Figma URL.