Figma Context MCP
Give your coding agent access to your Figma data. Implement designs in any framework in one-shot.
Descripción del creador (original en inglés)
PLATEAU 3D city data as scene-editing and glTF export tools for creative LLM agents.
Estos tres nunca se combinan en una sola puntuación: las opiniones, las mediciones y la popularidad son cosas distintas.
Todavía no escribimos un resumen sencillo para este. Abajo están los datos que leímos del registro.
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Abre Claude Desktop → Settings → Developer → Edit Config y pega esto en claude_desktop_config.json
{
"mcpServers": {
"plateau-creative": {
"command": "npx",
"args": [
"-y",
"@yodolabs/plateau-creative-mcp"
]
}
}
}Ejecuta esto en tu terminal
claude mcp add plateau-creative -- npx -y @yodolabs/plateau-creative-mcpPégalo en .cursor/mcp.json de tu proyecto, o en ~/.cursor/mcp.json
{
"mcpServers": {
"plateau-creative": {
"command": "npx",
"args": [
"-y",
"@yodolabs/plateau-creative-mcp"
]
}
}
}Tu navegador te pide permiso para abrir la app; luego la app muestra la configuración y te pide confirmar. Los valores de las claves quedan vacíos para que los completes tú.
Pégalo en .vscode/mcp.json de tu proyecto
{
"servers": {
"plateau-creative": {
"type": "stdio",
"command": "npx",
"args": [
"-y",
"@yodolabs/plateau-creative-mcp"
]
}
}
}Tu navegador te pide permiso para abrir la app; luego la app muestra la configuración y te pide confirmar. Los valores de las claves quedan vacíos para que los completes tú.
Este se ejecuta en tu computadora, y ChatGPT solo puede conectarse a servidores en internet. Elige otra app.
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Esta configuración se genera a partir de la ficha del creador en el registro. Si el README dice otra cosa, sigue el README.
Se ejecuta en tu computadora; la lista de herramientas aparece en tu app de IA después de instalarlo.
Revisamos información que cualquiera puede ver; no hemos leído el código. Las revisiones que no aplican no se cuentan. · Revisado el 7 nov 2026
El nombre en el registro se verificó con la cuenta de GitHub pixelx-jp, dueña del repo
Todavía no hemos leído este repo en GitHub
Todavía no hemos leído este repo en GitHub
Este se ejecuta en tu computadora; no hay endpoint en internet
Se ejecuta en tu computadora y usa ajustes locales en su lugar
Se ejecuta en tu computadora; solo podemos leer listas de herramientas de endpoints en internet
Comparado con todos los servidores activos de esta categoría en el registro. Las estrellas solo cuentan cuando quien lo publica es dueño del repo.
Superó 1 de 1 revisiones básicas aplicables. No hemos leído el código. Antes de agregar una clave o un token, revisa qué acceso pide el servidor y usa una clave que tenga solo los permisos que necesitas.
El registro no indica ninguna clave obligatoria, aunque algunos servidores te piden iniciar sesión la primera vez que los usas.
Se ejecuta en tu computadora. Tu app de IA lo inicia cuando hace falta, y los datos no pasan por los servidores del creador (a menos que el propio servidor llame a un servicio en línea).
El repo de GitHub cambió por última vez –, y la última versión (0.1.1) llegó al registro hace 5 meses.
Las apps compatibles con MCP, como Claude Desktop, Claude Code, Cursor y VS Code. También necesitas Node.js en tu computadora.
En la misma categoría: Figma Context MCP, Claude Real Video, Figma MCP Server
Servidores de la misma categoría hechos por otros creadores, ordenados por estrellas.
Cómo leer una tarjeta:★ Estrellas de GitHubiTres pilares: reseñas · revisiones · usoiActualizado = fecha en que se publicó la última versión en el registroi
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.
Copiado tal cual del repo del creador. PopNx MCP no lo ha revisado ni lo respalda. Se quitaron HTML, imágenes y scripts. Los enlaces llevan fuera de este sitio.
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
Solo se muestra el principio; lee el resto en el repo