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)
Drive Blender scenes: scene and object info, code execution, assets and 3D generation.
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": {
"scenemodel": {
"command": "npx",
"args": [
"-y",
"@reneturcios/scenemodel",
"mcp"
]
}
}
}在终端中运行这条命令
claude mcp add scenemodel -- npx -y @reneturcios/scenemodel mcp粘贴到项目中的 .cursor/mcp.json,或 ~/.cursor/mcp.json
{
"mcpServers": {
"scenemodel": {
"command": "npx",
"args": [
"-y",
"@reneturcios/scenemodel",
"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": {
"scenemodel": {
"type": "stdio",
"command": "npx",
"args": [
"-y",
"@reneturcios/scenemodel",
"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7日
注册名称已通过 GitHub 账户 CloudCorpRecords 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(0.1.0)于5天前进入注册中心。
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, Docker。
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。
scenemodel is a small MCP server and CLI for driving a Blender scene from an agent. It is a clean-room rebuild of a core subset — eight tools — from the documented surface of ahujasid/blender-mcp: scene and object info, arbitrary Blender Python execution, viewport screenshots, PolyHaven category browsing, search and download, and Hunyuan3D model generation.
The transport is the original's, unchanged: Blender runs an addon that listens on a TCP socket (default localhost:9876) and exchanges JSON commands of the shape {type, params} for JSON responses. scenemodel implements exactly that protocol behind an injectable socket function — one connection, one JSON request, one JSON response per call — with the host and port taken from BLENDER_HOST / BLENDER_PORT. When nothing is listening, calls fail honestly with the underlying connection error (ECONNREFUSED); scenemodel never invents scene data.
One documented gap: upstream, the screenshot tool returns image content. scenemodel returns an artifact summary instead — the image format plus its byte and base64 lengths — and never the image content block itself.
Deliberately omitted: the Hyper3D (Rodin) generation tools and their status checks, Hunyuan job status/polling beyond the generate call, the dedicated set_texture tool (texture setting stays reachable through asset download and code execution, as in the original), telemetry/user-id tools, and viewport scene manipulation beyond execute_blender_code.
The published container image bundles no Blender binary: the addon runs inside the user's own Blender install, so the image expects to reach a host Blender socket and says so in its Dockerfile.
npx @reneturcios/scenemodel get-scene-info
docker run -i ghcr.io/cloudcorprecords/scenemodel
Start Blender with the blender-mcp addon enabled first; it listens on localhost:9876 by default.
scenemodel get-scene-info
scenemodel get-object-info scenemodel execute-blender-code "import bpy; print(bpy.context.scene.name)" scenemodel get-viewport-screenshot [--max-size 1024] scenemodel get-polyhaven-categories [asset_type] scenemodel search-polyhaven-assets [asset_type] [categories] scenemodel download-polyhaven-asset [--resolution 2k] [--format gltf] scenemodel generate-hunyuan3d-model --text "a wooden chair" scenemodel --version
Exit codes: 0 success, 1 addon/socket error, 2 usage error.
npx -y @reneturcios/scenemodel mcp
{
"mcpServers": { "scenemodel": { "command": "npx", "args": ["-y", "@reneturcios/scenemodel", "mcp"], "env": { "BLENDER_HOST": "localhost", "BLENDER_PORT": "9876" } } } }
The env block is optional; the defaults are shown.
| Tool | Input | Addon command |
|---|---|---|
get_scene_info | — | get_scene_info |
get_object_info | object_name (required) | get_object_info |
execute_blender_code | code (required) | execute_code |
get_viewport_screenshot | max_size (optional) | get_viewport_screenshot — returns a format/length summary, not image content |
get_polyhaven_categories | asset_type (optional) | get_polyhaven_categories |
search_polyhaven_assets | asset_type, categories (optional) | search_polyhaven_assets |
download_polyhaven_asset | asset_id, asset_type (required), resolution, file_format | download_polyhaven_asset |
generate_hunyuan3d_model | text_prompt, input_image_url (one required) | generate_hunyuan3d_model |
Addon error envelopes and socket failures — a refused connection, a timeout, a malformed response — are reported as tool errors carrying the underlying message.
npm install
npm run build npm test npm run dev
Tests run entirely on a fake socket function: command shaping, response unwrapping, screenshot summarisation, and error propagation. No live Blender instance is touched.
MIT — see LICENSE.