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Figma-Context-MCP
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Figma-Context-MCP

Active·★ 16.0k·MIT·Updated 2026-10-03
★ Most Popular★ Trending★ Essential

Framelink MCP for Figma gives AI coding agents access to your Figma design data so they can implement designs accurately. You paste a link to a Figma file, frame or group into your agent's chat and ask it to build the design; the server fetches the relevant metadata from the Figma API, simplifies it to the layout and styling information that matters, and hands that to the model.

It is aimed at front-end developers who turn Figma designs into code with Cursor or another MCP-capable coding agent. The project's main argument is that structured design data produces much more faithful results than pasting screenshots, and that trimming the Figma API response keeps the model focused and improves accuracy. It was designed with Cursor in mind but works with any client that supports MCP configuration files.

Getting started: create a Figma personal access token, then add the server to your MCP configuration with `npx -y figma-developer-mcp --figma-api-key=YOUR-KEY --stdio` (on Windows, run it through `cmd /c`). You can also provide the key and port through environment variables.

#Figma#Model Context Protocol#AI Coding#Design to Code#Developer Tools#Coding
$ Install
$ npx -y figma-developer-mcp --figma-api-key=YOUR-KEY --stdio
↗ Visit site★ GitHub
01

Features

01Provides AI coding agents with Figma design data access.
02Enables one-shot design implementation into any framework.
03Simplifies and translates Figma API responses for AI models.
04Optimizes context for improved AI accuracy and relevance.
05Compatible with Cursor and other MCP-enabled AI clients.
02

Why choose it

+Structured design data gives far more accurate implementations than screenshots.
+Trims the Figma API response to relevant layout and styling, saving context.
+Very simple setup with a single npx command.
+MIT licensed and widely used.
03

Trade-offs

!Requires a Figma personal access token; putting it directly in a shared configuration file risks leaking it, so prefer environment variables.
!Read-only: it informs code generation but does not modify Figma files.
!Output quality still depends on how well the Figma file is structured (auto layout, naming, components).
04

Compatibility

Cursor
Native
Verified via docs
AI-powered Coding Tools
Supported
Verified via docs
05

Quick start

1
$ npx -y figma-developer-mcp --figma-api-key=YOUR-KEY --stdio
06

Use cases

↳Implementing UI designs in code using AI agents like Cursor.
↳Automating the conversion of Figma designs into various code frameworks.
↳Enhancing the accuracy and efficiency of AI-powered design-to-code workflows.
07

How it compares

≈vs TalkToFigma (cursor-talk-to-figma-mcp): TalkToFigma lets the agent both read and modify designs in Figma; Framelink focuses on reading design data for implementation.
≈vs Magic MCP (21st.dev): Magic generates UI components from prompts; Framelink implements your existing Figma designs.
≈vs pasting screenshots into a vision model: Framelink provides exact measurements, styles and structure rather than pixels.
08

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On this page
01Features02Why choose it03Trade-offs04Compatibility05Quick start06Use cases07How it compares08Alternatives
Stats
GitHub Stars★ 16.0k
Last commit6d ago
StatusActive
LicenseMIT
CategoryAPI Integration
Trend (30d)
+0.6k↑ 4.8%
Links
Documentation↗Discussion↗Issues↗Releases↗

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