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 Pack
https://github.com/pipeworx-io/mcp-figma
remote (streamable-http): https://gateway.pipeworx.io/figma/mcpRepublished in full under its license, with attribution. The source is authoritative.
Figma MCP Pack
Part of Pipeworx — an MCP gateway connecting AI agents to 1683+ live data sources.
| Tool | Description |
|---|---|
get_me | Get the signed-in Figma user: id, email, handle, and avatar image URL. Use to identify whose Figma account is connected. |
get_file | Get a compact summary of a Figma design file by its file key: name, last modified time, version, editor type, role, thumbnail URL, and the list of top-level pages (id, name, type, child count). Use to understand the structure of a Figma design file without fetching the full node tree. |
list_comments | List comments on a Figma design file. Returns each comment's id, message, author handle, created time, and resolved time. Use to review feedback and discussion on a design. |
get_file_nodes | Get specific nodes from a Figma design file by their node ids. Returns a compact map of node id to { name, type }. Use to inspect particular frames, components, or layers within a design file. |
get_file_images | Render images of specific nodes in a Figma design file. Returns a map of node id to a rendered image URL. Use to get visual previews (PNG, SVG, or JPG) of frames, components, or layers from a design. |
Add to your MCP client (Claude Desktop, Cursor, Windsurf, etc.):
{
"mcpServers": {
"figma": {
"url": "https://gateway.pipeworx.io/figma/mcp"
}
}
}
tools/list at https://gateway.pipeworx.io/figma/mcp returns the tools in the table
above plus the shared Pipeworx meta-tools — ask_pipeworx,
discover_tools, search_within, remember/recall and the rest of the
gateway-wide set. So the tool count you see is larger than this table: a
single-pack endpoint currently lists roughly 30 shared tools alongside the
pack's own. The connection's initialize response states its exact scope, and
is the authoritative answer for a given day.
This is deliberate, not multiplexing by accident. The meta-tools are what let a
scoped connection answer a question this pack does not cover — via
ask_pipeworx, which routes across the whole catalog — without you adding a
second MCP server. There is currently no way to mount a pack endpoint without
them; if the extra schemas cost you more context than the routing is worth,
connect to the full gateway once rather than to several pack endpoints.
Or connect to the full Pipeworx gateway to get every pack's tools listed
directly, instead of just this one's:
{
"mcpServers": {
"pipeworx": {
"url": "https://gateway.pipeworx.io/mcp"
}
}
}
Both URLs reach the same gateway and the same 1683+ data sources. The
only difference is which pack's tools are listed directly; ask_pipeworx
reaches all of them from either one.
This pack runs against a connected figma account, so it needs a Pipeworx key: sign in at https://pipeworx.io/account, connect figma, then call POST https://gateway.pipeworx.io/v1/tools/figma_get_me with Authorization: Bearer <your Pipeworx key>. Inspect any tool: GET https://gateway.pipeworx.io/v1/tools/figma_get_me. Find one: POST https://gateway.pipeworx.io/v1/tools/search_packs with {"query":"..."}.
This package also runs as a local stdio MCP server — no Pipeworx account, no
gateway round-trip:
{
"mcpServers": {
"figma": {
"command": "npx",
"args": ["-y", "@pipeworx/mcp-figma"]
}
}
}
Or run it directly to confirm it starts:
npx -y @pipeworx/mcp-figma
It speaks MCP over stdin/stdout and answers initialize/tools/list/tools/call
for only this pack's tools — none of the shared meta-tools the gateway
connection above adds. Same source, same tools, no ask_pipeworx routing.
Instead of calling tools directly, you can ask questions in plain English —
this works on the pack endpoint above as well as on the full gateway:
ask_pipeworx({ question: "your question about Figma data" })
The gateway picks the right tool and fills the arguments automatically.
MIT
| Description | Figma MCP Pack |
|---|---|
| Version | 0.1.2 |
| Packages | None stated |
| Environment variables | None stated |
| Remote endpoints | streamable-http https://gateway.pipeworx.io/figma/mcp |
| Website | https://pipeworx.io/packs/figma |
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
Creating algorithmic art using p5.js with seeded randomness and interactive parameter exploration. Use this when users request creating art using code, generative art, algorithmic art, flow fields, or particle systems. Create original algorithmic art rather than copying existing artists' work to avoid copyright violations.
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