Apple Human Interface Guidelines
Apple's platform design guidance: foundations, patterns, components, inputs, technologies.
Sourcedeveloper.apple.com/design/human-interface-guidelines
Agent Academy is a free, source-linked library of skills, prompts, MCP servers and bot templates, organised into courses by profession, for people who hand real work to AI agents: 1,467 live resources, each with its original link, license and safety tags.
MCP server
Original text · EnglishFigma MCP: list frames in a file and fetch one frame's JSON and image safely. 2 tools.
https://github.com/scalably-io/figma-mcp
FIGMA_TOKEN, FIGMA_API_BASE_URL, FIGMA_REQUEST_TIMEOUT_MS, FIGMA_MAX_JSON_BYTES, FIGMA_MAX_FRAME_BYTES, FIGMA_OUTPUT_ROOT, FIGMA_ALLOW_HTTP_FOR_TESTS
npx -y @scalably-io/figma-mcpRepublished in full under its license, with attribution. The source is authoritative.
Figma REST API MCP server. 2 tools list the top-level frames in a file and fetch one frame's rendered PNG plus its node JSON and image-fill map into a local output directory.
Claude Code:
claude mcp add figma -e FIGMA_TOKEN=your-token -- npx -y @scalably-io/figma-mcp
Codex:
codex mcp add figma --env FIGMA_TOKEN=your-token -- npx -y @scalably-io/figma-mcp
Claude Desktop: download figma-mcp.mcpb from the latest GitHub release and open it.
file_content:read scope./design/ or /file/, for example https://www.figma.com/design/AbC123xyz/My-file gives AbC123xyz. Both tools take it as file_key.FIGMA_TOKEN is not set the server still starts and lists its tools; every call then fails with FIGMA_NOT_CONFIGURED until the token is provided.fetch_frame is the only tool that writes files (so it is not marked read-only); it writes frame.png, node.json, and fills.json into a directory below the configured output root (default ./figma-output). The other tool is fully read-only.| Tool | What it does |
|---|---|
list_frames | List and optionally filter all top-level FRAME nodes in a Figma file, with exact page/name/node-id data, dimensions, and file metadata |
fetch_frame | Fetch one Figma frame and transactionally write frame.png, node.json, and a normalized image-fill map into a directory below the output root |
| Variable | Required | Purpose |
|---|---|---|
FIGMA_TOKEN | yes | Figma personal access token with file_content:read |
FIGMA_API_BASE_URL | no | Override the Figma REST API base URL (default https://api.figma.com/v1) |
FIGMA_REQUEST_TIMEOUT_MS | no | Per-request timeout in milliseconds (default 60000) |
FIGMA_MAX_JSON_BYTES | no | Upper bound on a Figma JSON response, in bytes (default 104857600) |
FIGMA_MAX_FRAME_BYTES | no | Upper bound on a downloaded frame PNG, in bytes (default 104857600) |
FIGMA_OUTPUT_ROOT | no | Directory that every fetch_frame output directory must stay below (default ./figma-output, created on first use) |
FIGMA_ALLOW_HTTP_FOR_TESTS | no | Test suite only: 1 allows a plain-HTTP loopback API base. Never set it in normal use |
Every tool returns plain JSON with status (succeeded, partial, no_op), summary, target, result, proof, warnings, recovery. Failures throw a plain error string: : <message> <hint>.
fetch_frame renders through Figma's image API, so very large frames or extreme scale values can exceed the configured JSON or frame byte limits; lower scale or split the frame if that happens. fills.json URLs are temporary and expire within 14 days.
Each release lists the package version, the .mcpb sha256 and the production commit it was derived from in CHANGELOG.md. CI runs the tests and a clean install of the packed tarball on every push.
This server runs locally, on your machine, under your own credentials. It collects no personal data, contains no telemetry, stores nothing persistently beyond the frame bundles you explicitly fetch, and talks only to the vendor API it wraps. No third party, including Scalably, receives your data. Contact: hello@scalably.io. Canonical copy: https://scalably.io/connector-privacy.html
MIT. Copyright Scalably.
| Description | Figma MCP: list frames in a file and fetch one frame's JSON and image safely. 2 tools. |
|---|---|
| Version | 1.0.1 |
| Packages | npm · @scalably-io/figma-mcp@1.0.1 · stdiomcpb · https://github.com/scalably-io/figma-mcp/releases/download/v1.0.1/figma-mcp.mcpb · stdio |
| Environment variables | FIGMA_TOKEN required secretFigma personal access token with file_content:read FIGMA_API_BASE_URLFigma REST API base URL, default https://api.figma.com/v1 FIGMA_REQUEST_TIMEOUT_MSPer-request timeout in milliseconds, default 60000 FIGMA_MAX_JSON_BYTESUpper bound on a Figma JSON response in bytes, default 104857600 FIGMA_MAX_FRAME_BYTESUpper bound on a downloaded frame PNG in bytes, default 104857600 FIGMA_OUTPUT_ROOTDirectory that all fetch_frame output directories must stay below, default ./figma-output FIGMA_ALLOW_HTTP_FOR_TESTSTest suite only: set to 1 to allow a plain-HTTP loopback API base. Never set it in normal use |
| Website | https://scalably.io/mcp/figma-mcp |
Apple's platform design guidance: foundations, patterns, components, inputs, technologies.
Sourcedeveloper.apple.com/design/human-interface-guidelines
Curated multilingual directory of ~2,391 public UI resources with visual-style (vs) facets, design KB (specs, skills), JSON endpoints and a recommended design-skill workflow.
Sourcesiinxu.github.io/ui-resource-hub/llms.txt
Workflow: pick ONE direction skill (frontend-design or taste-skill) → search resources by style/kind → build with emil-design-eng → audit with impeccable + web-design-guidelines + accessibility → verify in browser light+dark, mobile.
Sourcesiinxu.github.io/ui-resource-hub/api/skills.json
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Sourcegithub.com/anthropics/skills/blob/main/skills/algorithmic-art/SKILL.md
Create beautiful visual art in .png and .pdf documents using design philosophy. You should use this skill when the user asks to create a poster, piece of art, design, or other static piece. Create original visual designs, never copying existing artists' work to avoid copyright violations.
Sourcegithub.com/anthropics/skills/blob/main/skills/canvas-design/SKILL.md
A Streamlit application that provides comprehensive design analysis using a team of specialized AI agents powered by Google's Gemini model.
Sourcegithub.com/Shubhamsaboo/awesome-llm-apps/tree/main/advanced_ai_agents/multi_agent_apps/agent_teams/multimodal_design_agent_team