Figma Context MCP
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PLATEAU 3D city data as scene-editing and glTF export tools for creative LLM agents.
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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": {
"plateau-creative": {
"command": "npx",
"args": [
"-y",
"@yodolabs/plateau-creative-mcp"
]
}
}
}터미널에서 이 명령어를 실행하세요
claude mcp add plateau-creative -- npx -y @yodolabs/plateau-creative-mcp프로젝트의 .cursor/mcp.json 또는 ~/.cursor/mcp.json에 붙여 넣으세요
{
"mcpServers": {
"plateau-creative": {
"command": "npx",
"args": [
"-y",
"@yodolabs/plateau-creative-mcp"
]
}
}
}브라우저가 앱을 열지 물어본 다음, 앱이 설정을 보여 주고 확인을 요청해요. 키 값은 비워 두니 직접 입력하세요.
프로젝트의 .vscode/mcp.json에 붙여 넣으세요
{
"servers": {
"plateau-creative": {
"type": "stdio",
"command": "npx",
"args": [
"-y",
"@yodolabs/plateau-creative-mcp"
]
}
}
}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 7일 점검
레지스트리 이름이 GitHub 계정 pixelx-jp 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(0.1.1)은 5개월 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.
An MCP server that turns Project PLATEAU's 3D city data into scene-editing and glTF export tools for creative LLM agents.
English · 日本語
A real Shibuya block — loaded from PLATEAU, edited, and exported as one .glb by the export_glb tool, here rendered with three.js. Same geometry your LLM hands off to Blender / Unity / Unreal. Data © Project PLATEAU / MLIT (CC BY 4.0).
This server exposes tools. Orchestration is your LLM's job — point Claude / Cursor / any MCP client at this server alongside Blender MCP / Unity MCP / Unreal MCP and let it compose the workflow.
PLATEAU has an official MCP server for data access (catalog, specs, CityGML, attributes). This one fills the missing creation, scene-editing, and DCC export layer: load a Tokyo neighbourhood, delete every skyscraper, scale a block to 3× height, and emit a .glb ready for Blender / Unity / Unreal — all driven by tool calls.
flowchart LR
CLIENT["Claude / Cursor (any MCP client)"] -->|tool calls| MCP["plateau-creative-mcp"] MCP -->|download_area| DATA["plateau-bridge artifact index + bundles"] MCP -->|"load → filter → edit"| SCENE["scene_id (in-memory)"] MCP -->|export_glb| OUT[".glb + LICENSE.txt"] OUT --> DCC["Blender / Unity / Unreal"]
v0.1.0 — first public release. 10 MCP tools (incl. on-demand artifact download — no data clone needed), polygon footprint extrusion with mesh merging, single-GLB export ≤ 1 km² (≈40% gltf-transform compression) with a scene_manifest 3D Tiles fallback for larger areas, three data-access modes (TS+duckdb artifact / Python subprocess / upstream MCP via JSON-RPC), Overpass POI linking, and an optional cross-MCP bridge to BlenderMCP. Vendor-neutral over MCP — Claude, Cursor, any client works.
| Tool | Purpose |
|---|---|
download_area | Fetch + cache a prebuilt city bundle from the plateau-bridge artifact index (resolves the slug, downloads the .tar.zst, verifies sha256, extracts buildings.parquet + manifest.json), so load_area works without cloning the data pipeline. |
load_area | Load a city + bbox + LOD into a new scene_id. |
filter_buildings | Query building_uid[] inside a scene by height / year / use / zoning / flood depth. |
delete_buildings | Counterfactual edits — mark buildings as removed. |
extrude_buildings | Scale heights by a factor. |
compose_scene | Set render hints (time of day, weather, camera). |
export_glb | Emit a .glb (single_glb, real geometry from the parquet) or a scene_manifest referencing 3D Tiles. scene_manifest tile enrichment needs locally-built 3D Tiles; downloaded cities get a tile-less manifest (edits + bbox + attribution) plus a tileset_note. |
link_buildings_to_pois | Associate buildings with nearby OSM POIs (Overpass). |
get_attribution | Full dataset / license / URL metadata for a scene. |
render_via_blender | Export the scene as GLB and (optionally) bridge to a BlenderMCP-compatible HTTP MCP server via JSON-RPC. Dry-run returns the suggested cross-MCP call sequence instead. |
When PLATEAU_UPSTREAM_ENABLED=true, the server also exposes 13 tools proxied from the official Project PLATEAU MCP server: plateau_spec_outline, plateau_spec_read, plateau_get_metadata, plateau_search_areas, plateau_get_area, plateau_search_datasets, plateau_get_dataset, plateau_list_dataset_types, plateau_citygml_get_attributes, plateau_citygml_get_features, plateau_citygml_get_geoid_height, plateau_get_citygml_files, plateau_explain_spatial_id. The LLM client sees 23 tools in a single catalog, with no need to wire two separate MCP servers.
Every tool returns { result, attribution_metadata }. export_glb writes asset.extras.attribution into the GLB and a LICENSE.txt next to it. You must keep that attribution in any derived video, image, or asset.
npm install
npm run build
There are two ways to get city data in place.
Don't clone the data pipeline at all. Out of the box the server reads the public plateau-bridge artifact index, so download_area works with no configuration — it fetches the prebuilt bundle for a city, verifies its sha256, and caches it locally:
export PLATEAU_AUTO_DOWNLOAD=true # load_area auto-fetches a missing city (optional)
export PLATEAU_OUTPUT_DIR=./out npx @yodolabs/plateau-creative-mcp # stdio MCP server
Call download_area(city="shibuya") once (or set PLATEAU_AUTO_DOWNLOAD=true and just call load_area, which fetches a missing city first). Only buildings.parquet + manifest.json are extracted; bundles cache under PLATEAU_ARTIFACT_DIR (default ~/.cache/plateau-creative-mcp/artifacts), so each city downloads only once. Point PLATEAU_ARTIFACT_INDEX_URL at a different index to use your own mirror.
Downloaded bundles do not include 3D Tiles (they are gigabytes per city). Everything works from the parquet — load_area, all edits, and export_glb single_glb (real geometry, ≤ 1 km² / ≤ 5000 buildings). Only scene_manifest export loses its tile references for downloaded cities (it still emits the edit list, bbox, and attribution, with a tileset_note telling you to narrow to single_glb or run a local build). For full-geometry exports of larger areas, use Option B with a local build.
For Claude Desktop, add to claude_desktop_config.json:
{
"mcpServers": { "plateau-creative": { "command": "npx", "args": ["-y", "@yodolabs/plateau-creative-mcp"], "env": { "PLATEAU_AUTO_DOWNLOAD": "true", "PLATEAU_OUTPUT_DIR": "/Users/you/plateau-out" } } } }
If you already have plateau-bridge's out_ / outputs, point straight at them:
export PLATEAU_ARTIFACT_DIR=/path/to/plateau-bridge
export PLATEAU_OUTPUT_DIR=./out npx @yodolabs/plateau-creative-mcp # stdio MCP server
{
"mcpServers": { "plateau-creative": { "command": "npx", "args": ["-y", "@yodolabs/plateau-creative-mcp"], "env": { "PLATEAU_ARTIFACT_DIR": "/path/to/plateau-bridge", "PLATEAU_OUTPUT_DIR": "/Users/you/plateau-out" } } } }
Smoke run without an MCP client:
npx tsx scripts/smoke-load-area.ts
load_area(city="shibuya", bbox=[139.6975,35.6555,139.7045,35.6605], lod=2)
-> compose_scene(time="19:30", weather="rain") -> export_glb() # to ./out/ _v3.glb => BlenderMCP: import_glb + cyberpunk shader + render
flowchart LR
LLM(("LLM")) --> A["plateau-creative-mcp load · edit · export_glb"] LLM --> B["Blender MCP import · shade · render"] A -->|".glb + sidecar"| B
load_area(...)
-> filter_buildings({height_min: 100}) -> delete_buildings(filter={height_min: 100}) -> export_glb()
load_area(...)
-> filter_buildings({zoning_use: ["commercial"], far_max_min: 400}) => SketchUp MCP: design a new building inside those parcels
src/
server/ MCP protocol entry, tool registry, unified envelope tools/ 10 MCP tool handlers schemas/ Zod schemas + JSON Schema export scene/ scene_id LRU + lock + optional disk persistence data/ Artifact (duckdb) access layer + on-demand bundle downloader export/ three.js scene builder + GLTFExporter + manifest fallback attribution/ Envelope wrapping, attribution merge rateLimit/ Token bucket per (client, tool) errors/ Stable error codes + AppError config/ Env-driven config utils/ ids, bbox, paths, logger
gml_id or batch index alternates.single_glb. Larger scenes return EXPORT_LIMIT_EXCEEDED with a suggestion to switch to scene_manifest.| Env | Default | Meaning |
|---|---|---|
PLATEAU_ARTIFACT_DIR | ~/.cache/plateau-creative-mcp/artifacts | Directory containing out_ /buildings.parquet. Defaults to a cache dir (where download_area writes); set it to point at an existing plateau-bridge checkout. |
PLATEAU_ARTIFACT_INDEX_URL | plateau-bridge distribution/index.json | Cache index (JSON) listing each city's bundle URL + sha256. Defaults to the public mirror; override to use your own. |
PLATEAU_ARTIFACT_DOWNLOAD_TIMEOUT_MS | 300000 | Per-download timeout in milliseconds (5s–30min). |
PLATEAU_AUTO_DOWNLOAD | false | true makes load_area auto-fetch a missing city from the index before loading. |
PLATEAU_OUTPUT_DIR | ./out | Where .glb / LICENSE.txt / manifests are written. |
PLATEAU_DATA_MODE | artifact | artifact (TS + duckdb) or subprocess (Python helper). |
PLATEAU_PYTHON_BIN | python3 | Python interpreter for subprocess mode (must have duckdb installed). |
PLATEAU_SUBPROCESS_SCRIPT | bundled python/plateau_query.py | Override path to the JSON-stdio helper. |
PLATEAU_SCENE_DIR | ./.scene-store | Disk dir when scene persistence is enabled. |
PLATEAU_PERSIST_SCENES | false | true to serialize scenes to disk between calls. |
PLATEAU_MAX_SCENES | 64 | LRU cap on in-memory scenes. |
PLATEAU_SCENE_TTL_MS | 3600000 | Scene TTL in milliseconds. |
OSM_OVERPASS_URL | unset | Set to enable link_buildings_to_pois (e.g. https://overpass-api.de/api/interpreter). |
OSM_OVERPASS_TIMEOUT_MS | 25000 | Overpass request timeout. |
PLATEAU_UPSTREAM_ENABLED | false | true registers 13 official plateau_* tools proxied to the hosted PLATEAU MCP. |
OFFICIAL_PLATEAU_MCP_URL | hosted default | Override the official PLATEAU MCP endpoint (rare). |
See .env.example for a copy-paste template.
Polygon extrusion via the DuckDB spatial extension is on by default; on first run the extension is auto-installed. If install/load fails (offline CI, restricted environment), the exporter cleanly falls back to centroid-anchored 12 m × 12 m boxes per building. available_attributes in load_area's response includes footprint_polygon when the high-fidelity path is active.
single_glb exports merge every building into on
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