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"How to use the command features in Figma" matching MCP servers:

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    Converts a Figma file into a React project using Ant Design, AG Grid, ApexCharts, and Tailwind CSS, with optional export of mobile screens as a React Native (Expo) app.
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    MIT
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    Give any LLM agent a real Android or iPhone. 62 MCP tools: tap, swipe, type, screenshot, screen-tree reading, app launch, camera, TTS, crash reports, batched execution. Android via ADB, iPhone via WebDriverAgent, on-device inference, Docker+KVM emulators. Works with Claude Code, Cursor, LangChain, LlamaIndex, and any MCP client. MIT.
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    Enables AI assistants like Claude to interact with humans through intuitive GUI dialogs, supporting text input, choices, confirmations, and information displays.
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    MIT
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    Multi-account X (Twitter) automation that drives a real Chrome session with your own cookies, so no X API key is needed. 32 tools for posting, replies, search, engagement, and media, with draft approval on by default.
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    MIT
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    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
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    MIT
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    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.
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    MIT
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    Enables agents to interact with CLI applications like vim, htop, and gdb by sending key inputs and capturing terminal output through tmux sessions.
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    Enables offline reading and rendering of Figma .fig files, allowing AI agents to extract design specs, export assets, and generate code without needing the Figma API or network access.
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    MIT
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    Enables AI agents to read, inspect, and export Figma designs programmatically. Provides tools for listing components, styles, and exporting assets in various formats.
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    Enables users to describe their LLM fine-tuning job once and get the cheapest, fastest, and most balanced GPU options across a dozen cloud providers in seconds.
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    Enables academic research through paper search across multiple databases (IACR, CryptoBib, Crossref, Google Scholar), PDF processing, and GitHub repository browsing. Features modular architecture with FastMCP-based proxy server routing to specialized academic tools.
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    MIT
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    Converts AI Skills (following Claude Skills format) into MCP server resources, enabling LLM applications to discover, access, and utilize self-contained skill directories through the Model Context Protocol. Provides tools to list available skills, retrieve skill details and content, and read supporting files with security protections.
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    Apache 2.0
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    MCP server for managing i18n translation files — gives your AI agent full control over your app's translations without dumping entire locale files into context.
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    MIT
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    MCP server for AI agents to send notifications, copy to clipboard, request confirmations, and collect text input from users across their devices.
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    Apache 2.0
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    Enables low-cost agent models to control Windows applications through a compact, state-safe proxy over Open Computer Use, reducing model-visible context by up to 99.8% with support for record/replay and reusable UI component memory.
    5
    MIT