High-performance code intelligence MCP server. Indexes codebases into a persistent knowledge graph — average repo in milliseconds. 158 languages, sub-ms queries, 99% fewer tokens. Single static binary, zero dependencies.
MCP server for Figma layout data
This MCP server gives your coding agent access to Figma files, frames, and groups. It translates Figma API responses into a smaller set of layout and styling details so the agent can use the design as build context instead of a screenshot.
Builders who use Cursor or other AI coding tools and want to build from Figma layouts.
You can ask your agent to implement a Figma design with clearer context and less back-and-forth.
What it does
Figma file access
Connects an agent to Figma files, frames, and groups through Model Context Protocol.
Context simplification
Reduces Figma API data to the layout and styling details most relevant to the model.
Cursor setup
Provides config examples for Cursor and other MCP-capable clients on macOS, Linux, and Windows.
Command-line startup
Runs as a local MCP server through `npx -y figma-developer-mcp --figma-api-key=YOUR-KEY --stdio`.
README

Framelink MCP for Figma
Give your coding agent access to your Figma data.
Implement designs in any framework in one-shot.
Give Cursor and other AI-powered coding tools access to your Figma files with this Model Context Protocol server.
When Cursor has access to Figma design data, it's way better at one-shotting designs accurately than alternative approaches like pasting screenshots.
See quickstart instructions →
Demo
Watch a demo of building a UI in Cursor with Figma design data
How it works
- Open your IDE's chat (e.g. agent mode in Cursor).
- Paste a link to a Figma file, frame, or group.
- Ask Cursor to do something with the Figma file—e.g. implement the design.
- Cursor will fetch the relevant metadata from Figma and use it to write your code.
This MCP server is specifically designed for use with Cursor. Before responding with context from the Figma API, it simplifies and translates the response so only the most relevant layout and styling information is provided to the model.
Reducing the amount of context provided to the model helps make the AI more accurate and the responses more relevant.
Getting Started
Many code editors and other AI clients use a configuration file to manage MCP servers.
The figma-developer-mcp server can be configured by adding the following to your configuration file.
NOTE: You will need to create a Figma access token to use this server. Instructions on how to create a Figma API access token can be found here.
MacOS / Linux
{
"mcpServers": {
"Framelink MCP for Figma": {
"command": "npx",
"args": ["-y", "figma-developer-mcp", "--figma-api-key=YOUR-KEY", "--stdio"]
}
}
}
Windows
{
"mcpServers": {
"Framelink MCP for Figma": {
"command": "cmd",
"args": ["/c", "npx", "-y", "figma-developer-mcp", "--figma-api-key=YOUR-KEY", "--stdio"]
}
}
}
Or you can set FIGMA_API_KEY and PORT in the env field.
If you need more information on how to configure the Framelink MCP for Figma, see the Framelink docs.
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Learn More
The Framelink MCP for Figma is simple but powerful. Get the most out of it by learning more at the Framelink site.
Files in the repo
- .claude
- .github
- scripts
- src
- .env.example
- .gitignore
- .nvmrc
- .prettierrc
- .release-please-manifest.json
- CHANGELOG.md
- CLAUDE.md
- CONTRIBUTING.md
- eslint.config.js
- lefthook.yml
- LICENSE
- package.json
- pnpm-lock.yaml
- README.md
- release-please-config.json
- ROADMAP.md
- SECURITY.md
- server.json
- tsconfig.json
- tsup.config.ts
- vitest.config.ts
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