Figma Context MCP
Give your coding agent access to your Figma data. Implement designs in any framework in one-shot.
제작자가 쓴 설명(영어 원문)
A 3D compiler for coding agents: objects, worlds and games as small recipes. Emits Godot and STL.
이 세 가지는 절대 하나의 점수로 합치지 않아요. 의견, 측정, 인기는 서로 다른 것이니까요.
이 서버는 아직 쉬운 말로 된 요약을 쓰지 못했어요. 아래는 레지스트리에서 읽어 온 사실이에요.
쓰고 있는 AI 앱을 고른 다음 설정을 복사하세요.
필요한 것
어떤 앱을 쓰세요?
위에서 앱을 고르세요. 기억해 두었다가 다음부터는 버튼에 “…에 설치”라고 표시해요.
Claude Desktop → Settings → Developer → Edit Config를 열고 claude_desktop_config.json에 이 내용을 붙여 넣으세요
{
"mcpServers": {
"mojulo": {
"command": "npx",
"args": [
"-y",
"mojulo"
]
}
}
}터미널에서 이 명령어를 실행하세요
claude mcp add mojulo -- npx -y mojulo프로젝트의 .cursor/mcp.json 또는 ~/.cursor/mcp.json에 붙여 넣으세요
{
"mcpServers": {
"mojulo": {
"command": "npx",
"args": [
"-y",
"mojulo"
]
}
}
}브라우저가 앱을 열지 물어본 다음, 앱이 설정을 보여 주고 확인을 요청해요. 키 값은 비워 두니 직접 입력하세요.
프로젝트의 .vscode/mcp.json에 붙여 넣으세요
{
"servers": {
"mojulo": {
"type": "stdio",
"command": "npx",
"args": [
"-y",
"mojulo"
]
}
}
}브라우저가 앱을 열지 물어본 다음, 앱이 설정을 보여 주고 확인을 요청해요. 키 값은 비워 두니 직접 입력하세요.
이 서버는 내 컴퓨터에서 실행되는데, ChatGPT는 인터넷에 있는 서버에만 연결할 수 있어요. 다른 앱을 고르세요.
선택한 앱은 이 기기의 쿠키에만 저장돼요. 계정은 필요 없어요.
이 설정은 제작자의 레지스트리 정보로 만들었어요. README와 다르면 README를 따르세요.
내 컴퓨터에서 실행돼요. 설치하면 AI 앱에 도구 목록이 나타나요.
누구나 볼 수 있는 정보를 점검했고, 코드는 읽지 않았어요. 해당하지 않는 항목은 개수에서 뺐어요. · 2026년 11월 6일 점검
레지스트리 이름이 GitHub 계정 zombico 기준으로 확인되었고, 이 계정이 저장소를 소유하고 있어요
아직 GitHub에서 이 저장소를 읽어 오지 않았어요
아직 GitHub에서 이 저장소를 읽어 오지 않았어요
내 컴퓨터에서 실행되는 서버라 인터넷 엔드포인트가 없어요
내 컴퓨터에서 실행되며, 대신 로컬 설정을 사용해요
내 컴퓨터에서 실행돼요. 도구 목록은 인터넷 엔드포인트가 있는 서버에서만 읽을 수 있어요
레지스트리에서 이 카테고리의 활성 서버 전체와 비교했어요. 스타는 게시자가 저장소를 소유한 경우에만 세요.
해당하는 기본 점검 1개 중 1개를 통과했어요. 코드는 읽지 않았어요. 키나 토큰을 넣기 전에 서버가 어떤 권한을 요구하는지 확인하고, 꼭 필요한 권한만 있는 키를 쓰세요.
레지스트리에 필수 키가 나와 있지 않아요. 다만 처음 쓸 때 로그인을 요구하는 서버도 있어요.
내 컴퓨터에서 실행돼요. AI 앱이 필요할 때 실행하고, 데이터는 제작자의 서버를 거치지 않아요(서버 자체가 온라인 서비스를 호출하는 경우는 제외).
GitHub 저장소는 마지막으로 – 변경됐고, 최신 버전(3.1.1)은 21일 전 레지스트리에 올라왔어요.
Claude Desktop, Claude Code, Cursor, VS Code처럼 MCP를 지원하는 앱에서 쓸 수 있어요. 내 컴퓨터에 Node.js도 있어야 해요.
같은 카테고리에는: Figma Context MCP, Claude Real Video, Figma MCP Server
같은 카테고리에서 다른 제작자가 만든 서버예요. 스타 순으로 정렬했어요.
카드 보는 법:★ GitHub 스타i세 기둥: 리뷰 · 점검 · 사용 정도i업데이트 = 최신 버전을 레지스트리에 공개한 날i
Give your coding agent access to your Figma data. Implement designs in any framework in one-shot.
Let any LLM watch a video locally — and search everything it has ever watched.
The Figma MCP server brings Figma design context directly into your AI workflow.
제작자의 저장소에서 쓰인 그대로 가져왔어요. PopNx MCP가 검토하거나 보증한 내용이 아니에요. HTML, 이미지, 스크립트는 제거했어요. 링크를 누르면 이 사이트를 벗어나요.
Mojulo is a 3D factory with a media studio for coding agents: an MCP server that runs wherever your agent runs, on your machine or in the throwaway Linux box it gives itself, where the agent you already run (Claude Code, Codex, any MCP host, or a chat app that can open a Linux box: Claude, ChatGPT with Codex, Grok, Meta Muse, Google AI Studio) builds things to play, print, read, hear and watch (games, objects, walkable worlds, pictures, scores) by conversation, and what gets stored is source, not a mesh. Every artifact is a small deterministic recipe: a few hundred bytes of JSON, or an OpenSCAD program, that a kernel compiles back to the same geometry on every read (byte for byte on the same platform), and that emits to Godot, Blender, Unity, Unreal, glTF, OpenUSD, or print-ready STL / 3MF at true scale. Small enough to carry home from a box and re-mint on your own disk. A compiler, not a generator: you edit and diff the recipe like code, and renders are disposable. No API key, no account, no external telemetry. Your agent does the thinking; mojulo holds the state and does the geometry.
npx mojulo init
Needs Node 22.14+ and an MCP-capable coding agent (Claude Code or Codex; Claude Desktop works too). init finds the hosts on your machine, asks once per host, and opens the dashboard at http://localhost:3001. Everything lands in ~/.mojulo/. Then open a fresh agent session and ask: "what is this?"
In Claude Code you can install the plugin instead: /plugin marketplace add zombico/mojulo, then /plugin install mojulo@mojulo. It starts the same server pinned to one version (plugins/mojulo). The plugin build leaves out the handoff tools for AI image, voice and mesh generators and never downloads a browser, ffmpeg or the search model on its own. Use the plugin or init for Claude Code, not both: two registrations run two servers.
The first install is the big one: npx pulls a ~7 MB package that lands, with its dependencies, at about 227 MB on disk plus about 140 MB of npm cache (about 79 MB downloaded; measured for 3.0.0 on one macOS arm64 machine, where a cold start answered in about 4.5 s, nearly all of it npm's install). The biggest pieces are node-web-audio-api (audio), manifold-3d (exact booleans) and better-sqlite3. The dashboard is a separate package fetched the first time you open it, and the local search model is the opt-in mojulo install recall (semantic_search ranks lexically without it). Nothing in the list reaches the network on its own; the per-dependency sheet is in docs/tech-requirements.md. Verified on macOS (Apple Silicon) and on native Windows under Claude Code (init and a first render). On Linux x64 the test suite runs in CI, and the agent-box path below has been run to a mint and an export from the Claude app and web, ChatGPT work mode with Codex, Grok chat, Meta Muse and Google AI Studio.
Wire it by hand instead
# Claude Code (--scope user makes mojulo available in every project):
claude mcp add --scope user mojulo -- npx -y mojulo
[mcp_servers.mojulo] command = "npx" args = ["-y", "mojulo"]
// Claude Desktop: add under "mcpServers" in claude_desktop_config.json, then restart.
// If it fails with "spawn npx ENOENT", replace "npx" with the absolute path from which npx. "mojulo": { "command": "npx", "args": ["-y", "mojulo"] }
Open the dashboard on its own with npx -y mojulo-ui. It is its own npm package since 3.0.0, so your agent's npx mojulo start never downloads it; npx -y -p mojulo mojulo-ui still works and fetches the matching version from npm on first use. The mojulo bin is also a CLI over the tool registry: npx mojulo tools, npx mojulo help mint_solid, npx mojulo call version.
Mojulo runs wherever your agent runs, and a recipe minted in one place re-mints as the same geometry in the other. Two shapes, one install.
In your agent's box, nothing on your machine. One sentence to the agent installs mojulo in the Linux box it gives itself:
Each of those has been run this way, from the sentence to a mint and an export handed back. You get the same recipes and the same exports, as files: the export result names this host's door, an artifact page, a PR, a file card or Muse's Library. The box has no dashboard you can reach, a scene-to-PNG bake needs a browser it may not be allowed to fetch, and on most hosts it is gone when the session ends, so ask for the bundle (one zip: world.html, mesh, print STL for literal-scale objects, recipe.json, README) and keep the recipe. Meta Muse is the exception: one VM behind all its clients, where ~/.mojulo stays across conversations. A box with no MCP client never sends initialize, so tell the agent to run npx mojulo orient first: it prints what an MCP client is handed at connect, translated to the shell, and points at the routing index. Claude's box built a 47-part phone at true scale this way and handed back the glTF; Grok chat's sandbox minted a city from the shell. Blender installs in those boxes too.
On your machine: macOS, Windows, Linux. npx mojulo init wires mojulo into the agents it finds, opens the dashboard at localhost:3001, keeps everything under ~/.mojulo/, and probes your PATH for the optional local workers (Blender, a slicer, OpenSCAD, the game engines). This is the whole loop, and where a recipe from a box comes home to.
Who has run it where. persistent (your machine, or a box that keeps ~/.mojulo/) · ephemeral (the web agent's throwaway Linux box; keep the recipe). Blank means not verified yet, not "does not work".
| agent | macOS | Windows | Web Agent Linux Box (Headless) |
|---|---|---|---|
| Claude Code | |||
| Claude app (macOS, Windows, web, iOS) | |||
| ChatGPT (work mode; Codex) | Codex | ||
| Hermes Agent | |||
| Grok (Build; chat) | Build | ||
| Meta Muse (iOS, web, macOS app; one session across them) | |||
| Google AI Studio |
Two things are opt-in, and the choice is the same in both places:
| add | with | what you get |
|---|---|---|
| creative (installed by default) | plain npm install | worlds, audio, fonts for wordmarks, exact booleans, OpenSCAD-in-process, sharp for skins and sprite sheets. npm install --omit=optional sheds those helpers (about 115 MB); the studio tools still list and run, and a call that needs a missing helper says so. |
| recall | mojulo install recall | the embedding model behind semantic_search. Without it, search still answers, ranking by the words in your ask (about 480 MB of runtime plus a 130 MB model, kept under ~/.mojulo/ so it survives upgrades). Most sessions never need it: the agent reads the tool index and the vocab cards directly. |
mojulo install with no argument prints which of the two are present.
The chatbot factory is no longer part of mojulo as of 3.0 and is moving to its own project. Earlier 2.x versions that include it are unmaintained and have known security issues (SECURITY.md). mojulo install chatbot now installs nothing and prints this notice.
Upgrading from 2.x? Read Upgrading from 2.x first: an unpinned npx mojulo moves to 3.0 on its next start, and 3.0 re-encrypts saved provider keys so 2.x can no longer read them.
Each one is a sentence to your agent, the tool it reaches for, and the recipe that gets stored. Every example below runs keyless and offline.
The agent calls mint_solid { kind: 'scad' } and the program is the recipe, stored verbatim:
board_w = 85; board_d = 56; clear = 1; wall = 2; floor_t = 2; wall_h = 12;
holes = [[3.5, 3.5], [61.5, 3.5], [3.5, 52.5], [61.5, 52.5]]; // the Pi's M2.5 pattern module rounded_box(w, d, h, r) { hull() for (x = [r, w - r], y = [r, d - r]) translate([x, y, 0]) cylinder(r = r, h = h, $fn = 48); } module tray() { color("#3a3f4b") difference() { rounded_box(board_w + 2 * (clear + wall), board_d + 2 * (clear + wall), floor_t + wall_h, 3); translate([wall, wall, floor_t]) rounded_box(board_w + 2 * clear, board_d + 2 * clear, wall_h + 1, 1.5); translate([board_w + 2 * clear + wall - 1, wall + 2, floor_t + 3]) cube([wall + 2, board_d + 2 * clear - 4, wall_h]); // USB / Ethernet translate([wall + clear + 5, -1, floor_t + 3]) cube([55, wall + 2, wall_h]); // USB-C, HDMI, audio } } module standoffs() { color("#c9a227") for (p = holes) translate([wall + clear + p[0], wall + clear + p[1], floor_t]) difference() { cylinder(d = 6, h = 3, $fn = 32); translate([0, 0, -1]) cylinder(d = 2.5, h = 5, $fn = 24); } }
with parts: { tray: 'tray();', standoffs: 'standoffs();' }. OpenSCAD itself meshes it on every read, in-process as WebAssembly with the Manifold backend, so booleans are exact and every edge is sharp. color() is the tint; each named part is a render group a hinge in movers can swing. The same ref serves the orbit view, the .glb, the engine packs and model.stl at 91 × 62 × 14 mm as written; model.scad hands the source back unchanged. Change wall_h with update_sketch and the readout names the one part that moved. For what OpenSCAD cannot say, a blended join, a stroked dent, seeded noise, the source calls mojulo_field(" ") and a field solid from the same recipe is baked in at that spot.
T
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