Figma Context MCP
Give your coding agent access to your Figma data. Implement designs in any framework in one-shot.
作者提供的说明(英文原文)
PLATEAU 3D city data as scene-editing and glTF export tools for creative LLM agents.
这三项永远不会合并成一个分数:意见、测量和人气是不同的东西。
我们还没有为它写通俗的介绍。下面是我们从注册中心读取到的事实。
选择你使用的 AI 应用,然后复制设置。
你需要
你用的是哪个应用?
在上方选择你的应用。我们会记住它,下次按钮会显示“安装到 …”。
打开 Claude Desktop → Settings → Developer → Edit Config,把下面的内容粘贴到 claude_desktop_config.json
{
"mcpServers": {
"plateau-creative": {
"command": "npx",
"args": [
"-y",
"@yodolabs/plateau-creative-mcp"
]
}
}
}在终端中运行这条命令
claude mcp add plateau-creative -- npx -y @yodolabs/plateau-creative-mcp粘贴到项目中的 .cursor/mcp.json,或 ~/.cursor/mcp.json
{
"mcpServers": {
"plateau-creative": {
"command": "npx",
"args": [
"-y",
"@yodolabs/plateau-creative-mcp"
]
}
}
}浏览器会先询问是否打开应用,然后应用会显示设置并请你确认。密钥的值会留空,由你自己填写。
粘贴到项目中的 .vscode/mcp.json
{
"servers": {
"plateau-creative": {
"type": "stdio",
"command": "npx",
"args": [
"-y",
"@yodolabs/plateau-creative-mcp"
]
}
}
}浏览器会先询问是否打开应用,然后应用会显示设置并请你确认。密钥的值会留空,由你自己填写。
这个服务器在你的电脑上运行,而 ChatGPT 只能连接互联网上的服务器。请选择其他应用。
你的选择通过 Cookie 保存在这台设备上,无需账户。
这些设置是根据作者在注册中心的条目生成的。如果 README 的写法不同,请以 README 为准。
它在你的电脑上运行;安装后,工具列表会显示在你的 AI 应用中。
我们检查的是任何人都能看到的信息;我们没有阅读代码。不适用的检查项不计入总数。 · 检查于 2026年11月8日
注册名称已通过 GitHub 账户 pixelx-jp 验证,该账户拥有此仓库
我们还没有从 GitHub 读取这个仓库
我们还没有从 GitHub 读取这个仓库
它在你的电脑上运行,没有互联网端点
在你的电脑上运行,改用本地设置
它在你的电脑上运行;我们只能读取互联网端点的工具列表
与注册中心里这个分类中所有活跃的服务器比较。只有当发布者拥有该仓库时,星标数才计入。
它在 1 项适用的基础检查中通过了 1 项。我们没有阅读代码。在添加密钥或令牌之前,请先看看这个服务器要求哪些权限,并使用只具备所需权限的密钥。
注册中心没有列出必需的密钥,不过有些服务器会在首次使用时要求你登录。
它在你的电脑上运行。你的 AI 应用会在需要时启动它,数据不会经过作者的服务器(除非它自己调用在线服务)。
GitHub 仓库最后更新于–,最新版本(0.1.1)于5个月前进入注册中心。
支持 MCP 的应用,例如 Claude Desktop、Claude Code、Cursor 和 VS Code。你的电脑上还需要有 Node.js。
同一分类中有:Figma Context MCP, Claude Real Video, Figma MCP Server
同一分类中其他作者的服务器,按星标数排序。
如何看卡片:★ GitHub 星标i三大支柱:评价 · 检查 · 使用情况i更新 = 最新版本发布到注册中心的时间i
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.
按原文从作者的仓库复制。PopNx MCP 没有审查或背书其内容。HTML、图片和脚本已被移除。链接会离开本站。
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
只显示了开头部分;其余内容请在仓库中阅读