glips/figma-context-mcp

MCP server to provide Figma layout information to AI coding agents like Cursor

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Summary Information

Updated 32 minutes ago
Added to GitGenius on September 3rd, 2026
Created on February 13th, 2025
Open Issues & Pull Requests: 24 (+0)
GitHub issues: Enabled
Number of forks: 1,260
Total Stargazers: 15,792 (+0)
Total Subscribers: 65 (+0)

Repository Insights (GitGenius)

Median issue/PR response: 8.2 hours
Mean response time: 8.2 days
90th percentile: 8.2 days
Tracked items: 174

How this project is maintained

Around half of the issues opened in the past year never receive a reply. Only 11% of issues opened in the past year have been closed. Three people close 89% of everything that gets resolved.

Charts & Analytics

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Issue Activity (beta)

Open issues: 6
New in 7 days: 0
Closed in 7 days: 0
Avg open age: 285 days
Stale 30+ days: 6
Stale 90+ days: 3

Recent activity

Opened in 7 days: 0
Closed in 7 days: 0
Comments in 7 days: 0
Events in 7 days: 0

Top labels

  • bug (40)
  • enhancement (9)
  • good first issue (7)
  • documentation (1)
  • question (1)
  • wontfix (1)

Most active issues this week

No issue events were indexed in the last 7 days.

Detailed Description

figma-context-mcp is an MCP server that bridges Figma design files with AI coding agents.

The tool solves the problem of AI coding assistants lacking access to design context when building user interfaces. Rather than requiring developers to manually describe layouts or paste screenshots, the server connects directly to Figma and extracts structural information about designs. This allows AI agents like Cursor to understand the spatial relationships, component hierarchy, and layout details of a design file programmatically, enabling more accurate code generation that matches the intended design.

Developers should adopt this tool if they work in environments where AI-assisted coding is part of their workflow and designs live in Figma. It suits projects where designers and developers collaborate closely and where maintaining fidelity between design and implementation matters. The tool is particularly valuable for teams using Cursor or similar AI coding agents that support MCP server integration, as it eliminates the friction of manually translating design specifications into code context.

The project shows active development with recent commits addressing core functionality. The codebase is well-structured and maintained in TypeScript, indicating attention to code quality and type safety. Documentation appears focused on practical integration, with a homepage providing additional context for users evaluating the tool.