How I Cut Figma REST API Tokens by 95% for Cursor, Claude Code, and Modern AI Editors A developer built Figma Spec Compressor, an open-source tool that prunes Figma REST API payloads through a four-stage pipeline — dropping invisible nodes, translating auto-layout to Tailwind, and collapsing vector paths — to cut token counts by 80%–95% before feeding designs to AI coding editors. Tested with OpenAI's gpt-tokenizer, an enterprise dashboard frame fell from 189,485 to 9,800 tokens (94.8% reduction) in 54ms, while a pricing card dropped from 3,010 to 615 tokens. The tool ships as a Model Context Protocol server over stdio, configurable in Cursor and Claude Code. Connecting AI coding tools like Cursor Composer, Claude Code, or Google Antigravity to Figma is the holy grail of frontend engineering. You paste a Figma URL, and your AI writes pixel-perfect Tailwind components. Except in practice, there's a huge catch: Figma's raw REST API is absurdly noisy. In this article, I'll break down why raw Figma payloads explode context windows, how AST pruning reduces token counts by 80%–95%, and how you can run this as a native Model Context Protocol MCP server. When you query Figma's /v1/files/:key/nodes endpoint for an enterprise SaaS dashboard, you don't just get colors and typography. You get: On an enterprise analytics dashboard with 646 nodes: A single design frame consumes almost the entire 200k context window of modern LLMs, causing severe layout hallucinations and broken CSS. To fix this, I engineered Figma Spec Compressor Open Source on GitHub https://github.com/leethoneid/figma-spec-compressor . Instead of blindly dumping JSON into an LLM, it executes a 4-stage optimization pipeline: Raw Figma JSON 189k tokens │ ▼ 1 Node Pruner Drops invisible nodes, masks & deep redlines │ ▼ 2 Auto-Layout Translator Maps flexbox, padding & fills to Tailwind │ ▼ 3 Vector Collapser Replaces 100+ SVG points with