figma-context-MCP
VerifiedMCP server (Framelink) that feeds AI coding tools like Cursor simplified Figma layout and styling data for one-shot design-to-code implementation.
Overview
MCP server (Framelink) that feeds AI coding tools like Cursor simplified Figma layout and styling data for one-shot design-to-code implementation.
Best Fit
figma-context-MCP is best suited for teams evaluating MCP integrations, developers exploring TypeScript-based tooling, and operators who want a fast way to assess external AI workflow capabilities.
Operational Notes
This profile is generated from the captured MCP service dataset. It focuses on reliable comparison context, installation readiness, and the core value of figma-context-MCP.
Key Features
Protocol-ready integration
figma-context-MCP is positioned as an MCP-compatible service that can be connected into assistant workflows with a standardized tool interface.
Developer-friendly setup
The service appears in the captured MCP catalog with a primary stack of TypeScript, making it easier to evaluate from an implementation perspective.
Workflow acceleration
This service is designed to reduce friction in AI-assisted tasks by exposing targeted capabilities through the Model Context Protocol.
Advantages
- Provides a focused MCP integration surface for figma-context-MCP.
- Easy to compare against other MCP services in the catalog.
- Useful for teams working with TypeScript tooling and automation workflows.
Trade offs
- Captured source content may omit deep implementation details.
- Production usage still requires reviewing trust, credentials, and operational boundaries.
Use Cases
Evaluation and shortlist building
Use this page to understand whether figma-context-MCP fits your MCP stack before deeper technical adoption.
Assistant workflow integration
Teams can review figma-context-MCP as a candidate tool for expanding agent capabilities in real product or research workflows.
FAQ
What does figma-context-MCP help with?
figma-context-MCP exposes a focused capability through MCP so assistants and AI workflows can interact with that capability in a more structured way.
How should I evaluate it?
Start with the summary, review the install snippet if available, inspect the tools it exposes, and confirm whether its trust model fits your environment.
Install
Copy the configuration below into your MCP client.
{
"mcpServers": {
"Framelink Figma MCP": {
"command": "npx",
"args": ["-y", "figma-developer-mcp", "--figma-api-key=YOUR-KEY", "--stdio"]
}
}
}
{
"mcpServers": {
"Framelink Figma MCP": {
"command": "cmd",
"args": ["/c", "npx", "-y", "figma-developer-mcp", "--figma-api-key=YOUR-KEY", "--stdio"]
}
}
} Tools
download_figma_images
Download image assets from a Figma file to a local destination.
| Parameter | Description |
|---|---|
| fileId: string | The Figma file identifier. |
| savePath: string | The local path where downloaded assets should be saved. |
start
Start the MCP service or its local HTTP process.
stop
Stop the MCP service or its local HTTP process.
status
Check whether the MCP service is currently running and available.
get_figma_data
Fetch structured data from a Figma file for downstream AI workflows.
| Parameter | Description |
|---|---|
| fileKey: string | The Figma file key. |