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.
Star History
Learn More
The Framelink MCP for Figma is simple but powerful. Get the most out of it by learning more at the Framelink site.
Recommend MCP Servers 💡
agentrpc
AgentRPC is a universal RPC layer for AI agents, enabling them to connect to any function in any language across network boundaries. It wraps your functions in a universal RPC interface and provides a hosted Model Context Protocol (MCP) server, ideal for integrating services deployed in private VPCs, Kubernetes clusters, or multiple cloud environments.
markitdown-mcp
A lightweight Model Context Protocol (MCP) server from Microsoft's MarkItDown project, providing STDIO, Streamable HTTP, and SSE transports to convert various URIs (http:, https:, file:, data:) into Markdown.
@thomasvan/mcp-brave-search
MCP server for Brave Search integration with AI assistants
php-mcp/server
A comprehensive PHP SDK for building Model Context Protocol (MCP) servers, supporting stdio, http+sse, and streamable HTTP transports.
deepl-mcp-server
A Model Context Protocol (MCP) server that provides translation and rephrasing capabilities using the DeepL API.
MCP-Bridge
A bridge between OpenAI API and MCP tools, enabling MCP tool usage through OpenAI API interface
