Figma Context MCP
Give your coding agent access to your Figma data. Implement designs in any framework in one-shot.
作者による説明(英語の原文)
Free Blender MCP addon for faster AI scene edits, fewer tokens and built-in scene checks.
この3つを1つのスコアにまとめることはしません。意見、測定、人気はそれぞれ別のものだからです。
このサーバーのやさしい解説はまだ書いていません。以下はレジストリから読み取った事実です。
使っているAIアプリを選んで、設定をコピーしてください。
どのアプリを使っていますか?
上でアプリを選んでください。選んだアプリを覚えておくので、次からはボタンに「…にインストール」と表示されます。
リンク先は作者自身のファイルです。私たちが置いたり再パッケージしたりしたものではありません。ファイルを開くと、Claude Desktopがインストールします。
ターミナルでこれを実行します
ブラウザがアプリを開いてよいか確認し、そのあとアプリが設定を表示して確認を求めます。キーの値は空欄のままなので、自分で入力してください。
ブラウザがアプリを開いてよいか確認し、そのあとアプリが設定を表示して確認を求めます。キーの値は空欄のままなので、自分で入力してください。
これはパソコンで動くサーバーですが、ChatGPTがつなげるのはインターネット上のサーバーだけです。ほかのアプリを選んでください。
選んだアプリは、この端末のCookieに保存されます。アカウントは不要です。
この設定は、作者のレジストリ登録情報から作成しています。READMEと違う場合は、READMEに従ってください。
パソコンで動くサーバーです。インストールすると、ツール一覧がAIアプリに表示されます。
誰でも見られる情報をチェックしており、コードは読んでいません。当てはまらない項目は数に入れていません。 · 2026年11月7日にチェック
レジストリ名は、リポジトリを所有するGitHubアカウント Ker102 で確認済みです
このリポジトリはまだGitHubから読み取っていません
このリポジトリはまだGitHubから読み取っていません
これはパソコンで動くため、インターネット上のエンドポイントはありません
パソコンで動き、代わりにローカルの設定を使います
パソコンで動くサーバーです。ツール一覧を読み取れるのは、インターネット上のエンドポイントがある場合だけです
レジストリでこのカテゴリにある有効なすべてのサーバーと比較しています。スターは、公開者がリポジトリの所有者である場合だけ数えます。
当てはまる基本チェック1項目のうち1項目に合格しました。コードは読んでいません。キーやトークンを追加する前に、サーバーがどんなアクセスを求めているかを確認し、必要な権限だけを持つキーを使ってください。
レジストリには必須のキーは載っていません。ただし、最初に使うときにサインインを求めるサーバーもあります。
あなたのパソコンで動きます。必要なときにAIアプリが起動し、データは作者のサーバーを通りません(サーバー自体がオンラインサービスを呼び出す場合を除きます)。
GitHubリポジトリの最終更新は–、最新バージョン(1.3.0)がレジストリに届いたのは30 日前です。
Claude Desktop、Claude Code、Cursor、VS CodeなどのMCP対応アプリで使えます。パソコンにMCPBも必要です。
同じカテゴリには:Figma Context MCP, Claude Real Video, Figma MCP Server
同じカテゴリで、ほかの作者が作ったサーバー。スターの多い順。
カードの見方:★ GitHubスターi3つの柱:レビュー · チェック · 利用状況i更新=最新バージョンをレジストリに公開した日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.
作者のリポジトリから書かれたとおりにコピーしたものです。PopNx MCPは内容を確認・推奨していません。HTML、画像、スクリプトは取り除いています。リンクはこのサイトの外へ移動します。
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ViperMesh for Blender Open-source Blender MCP server and addon for AI agents.
AI assistance for Blender, with less code and less waiting.
Designed for faster scene edits, fewer AI tokens and better-checked results.
Project overview and setup | ViperMesh Studio waitlist
ViperMesh for Blender is a free, open-source Blender MCP server and addon that lets a compatible AI assistant work inside your Blender scene. It is for Blender artists, hobbyists and game creators who want help making and editing 3D scenes, not another coding project.
The goal: faster AI-assisted work, fewer AI tokens and better-checked results. Your assistant gets ready-to-use Blender actions instead of having to write new Python code for many common edits. You keep working in Blender and decide what you want the assistant to help with.
Watch the 77-second video or download the MP4. See how your AI client uses ready-made Blender actions, why less generated code can help, and how to get started. This is an illustrated overview with music, not a timed benchmark recording. GitHub's README links to the playable video.
| What matters to you | How ViperMesh helps |
|---|---|
| Less AI usage | Reusable actions reduce the Blender code the assistant needs to generate for covered tasks. |
| Less waiting | The connection stays open, and related actions can run together instead of repeating setup for each step. |
| Better-checked scenes | Built-in checks help identify floating objects, wrong orientations and clearance problems; the assistant can inspect images and repair mistakes. |
| Easier for your assistant | Discoverable tools and concise guidance explain what actions are available and how to use them. |
| Room for custom work | The assistant can still write Python when your request needs something the ready-made tools do not cover. |
AI tokens are the units of text a model reads and writes. Generating less code can reduce AI usage, but total tokens, cost and time also depend on your model and the task. Scene checks help with correctness; they do not guarantee a beautiful or error-free result.
One historical image-reconstruction test using the ViperMesh Blender MCP harness and available assets. Only the centre heading was relabelled; the reference and both scene screenshots are unchanged. This is one example, not a guarantee of every result. The public addon does not bundle private Studio asset libraries.
Read the Blender MCP case study, Part One | Open the full-size comparison | Image integrity record
For example, you could ask your assistant:
Move the basket under the right side of the table, without intersecting its legs.
Soften the sharp edges on this furniture, keeping its overall shape.
Check this scene for unsupported objects, then show me what needs fixing.
These are examples of requests, not prebuilt scene templates. You do not need to write Blender Python yourself for the operations the tools cover.
ViperMesh builds on the original BlenderMCP project by Siddharth Ahuja, now named MCP for Blender. The main difference is its emphasis on a broad set of ready-made editing actions, reusable workflows and scene checks, rather than relying on newly generated Python for common edits.
Both projects can inspect scenes and run custom Python. The original project also offers asset and generation integrations. ViperMesh's aim is to make everyday scene operations more token-efficient, faster, simpler for assistants to use and easier to validate. This is not a claim that it wins every task or that the public connector includes every feature of ViperMesh Studio.
Website installation guide · Harness Library listing
MCP, short for Model Context Protocol, is a connection standard that lets an AI assistant use tools in another application. You need an AI app that supports these connections; installing the addon alone does not add an AI model to Blender.
Download the versioned addon .py or addon .zip from the latest release. In Blender:
Keep the bridge running for the complete agent session.
Packaged option: Download the v1.3.0 MCPB bundle and import it into a client that supports local MCPB extensions. It contains the Node server and its dependencies, so you do not need to clone or build the repository. Node.js and the separately enabled Blender addon are still required.
The connector is also listed on Smithery and in the official MCP Registry. These listings distribute the local connector, not a hosted Blender service. See distribution and bundle setup for the checksum, manual extraction option, and current validation limits.
Source option: Until the npm package is published, clone and build it:
git clone https://github.com/OpenRootdev/vipermesh-blender.git
cd vipermesh-blender npm install npm run build
When using the MCPB import, the client reads its launch configuration from the bundle. For the source option, use the built entry point from an absolute path:
{
"mcpServers": { "vipermesh-blender": { "command": "node", "args": [ "C:/absolute/path/to/vipermesh-blender/dist/public-portable-blender-mcp.js" ] } } }
Start this command once through the MCP client. Do not invoke npm, npx, or tsx again for each Blender operation. See MCP client setup for Codex, JSON-configured clients, compatibility, and the optional Docker MCP Toolkit route.
The sections below are for setting up or developing an AI connection. Blender users can start with the installation steps and the example requests above.
MCP-compatible AI assistant
| | stdio, one long-lived process v ViperMesh MCP server | | serialized loopback connection v ViperMesh Blender addon (127.0.0.1:9876) | v Blender scene
The MCP server opens no network listener. The Blender addon listens on loopback by default and reports Stopped, Ready, Agent connected, or Error in the ViperMesh sidebar.
bootstrap_vipermesh_session.call_blender_tool(name="get_scene_info").search_3d_guidance.list_blender_tools.The public MCP surface includes:
bootstrap_vipermesh_sessioncheck_blender_connectionlist_blender_toolscall_blender_toolcall_blender_tool_batchrun_blender_scene_stageget_blender_agent_contextsearch_3d_guidanceget_3d_guidance_documentRead the complete connector manual for request shapes, batching rules, staged workflows, local tool skills, and troubleshooting. The repository also ships an installable using-vipermesh-blender agent skill.
This connector is intended for a trusted local workstation. execute_code can run arbitrary Python in Blender. Only connect trusted MCP clients, keep the bridge on loopback, and review high-impact or destructive operations.
See SECURITY.md for the trust boundary and private vulnerability reporting process.
This repository contains the open-source Blender addon, portable MCP server, portable public tool skills, and connector tests. It does not include the ViperMesh application, authentication, billing, private prompts, private RAG data, cloud model routing, private assets, raw benchmark traces, or private evaluation datasets. The illustrated comparison is separately provided public evidence, not a bundled asset library.
The connector does not bundle a commercial 3D generation provider. Neural generation can be added later through provider-neutral authenticated services without embedding third-party credentials in Blender.
No. The public addon and local connection are free to use without a ViperMesh account. Your AI app or model provider may charge separately. The addon does not include free AI model access.
冒頭だけを表示しています。続きはリポジトリで読めます