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Blender MCP servers for AI agents, compared: local vs cloud

Updated 2026-10-02

A local Blender MCP (ahujasid/blender-mcp, Blender Agent Bridge) lets an agent inspect and edit the scene open in your Blender and render on your own machine, so it needs Blender installed and your GPU. A cloud Blender MCP runs Blender on a server: Sceneplane gives agents a hosted Blender with durable projects and scene tools; JANCTION Render is a render farm for agents: send a .blend, a bpy script or a glTF/FBX/USD file and get a 4-frame preview in about 4 seconds and the final frames or MP4 on a datacenter GPU, free beta 10 GPU-minutes per key per day, OAuth connect with no key to paste. They combine: edit locally, render on JANCTION.

The four, side by side

server	where Blender runs	what the agent can do	you need	GPU used	price	transport
ahujasid/blender-mcp	your machine (an add-on opens a local socket, port 9876 by default; the MCP server relays commands)	inspect and edit the live scene, run Python in Blender, viewport screenshots, render with your Blender	Blender 3.0+ running with the add-on, Python 3.10+, uv	yours	free, open source	stdio (local)
Blender Agent Bridge	your machine (a Blender extension plus a local bridge)	inspect objects, materials, rigs, animation, cameras, nodes and render settings; preview edits then commit or revert; playblasts and inspection renders; progress polling for long jobs; configs for Codex, Claude Code, Claude Desktop and Cursor	Blender with the extension running	yours	free, open source	local bridge
Sceneplane	their cloud: an isolated Blender compute environment per deployment	durable projects with versioned revisions, scene operations, renders, MP4, STL/GLB exports, bpy signature lookup, Blender manual search, Poly Haven / Sketchfab asset search	an account and an API key sent as a bearer header	theirs	account-based plans (see sceneplane.online)	remote MCP (mcp.sceneplane.online/v1)
JANCTION Render	JANCTION data center: a throwaway container per job on an NVIDIA RTX PRO 6000 Blackwell	scene_info, 4-frame preview, time estimate, final frames or MP4, HDRI lighting presets, turntable, download links; no scene-editing tools: the agent writes or fixes the bpy script itself and re-previews	nothing locally for the remote MCP (OAuth consent page); or `pip install janction-render` for stdio	datacenter GPU	free beta: 10 GPU-minutes per key per day; planned 0.1 JPY per GPU second	remote MCP (Streamable HTTP, OAuth 2.1) and stdio

Checked on 2026-10-02 from each project's public pages and repositories; tell us at the support page if a row is out of date.

Which one to pick

You work inside Blender and have a GPU: a local server. blender-mcp is the most used; Blender Agent Bridge adds preview-then-commit edits and a cleaner setup for Codex and Cursor.
The agent should keep a project alive across sessions and edit it in the cloud: Sceneplane.
You have a scene (or the agent can write one) and need the render, fast and free, with no Blender installed: JANCTION Render. It is the only one of the four with a free daily GPU quota and a preview tool measured in seconds (benchmarks).
Both: edit with blender-mcp on your machine, save the .blend, and let the same agent send it to JANCTION Render for the final frames (the CLI collects the textures the file references).

What "cloud MCP" changes for the agent

No local process to start: the tool list is there as soon as the connector is added, and the preview image comes back inline (Claude.ai shows it in a panel).
Every render is an isolated container with no network, so a script cannot reach your machine or the internet; scripts are checked statically before they run (security).
The GPU is shared: the status page says whether it is lent out right now; queued jobs start when it returns.

Connect JANCTION Render

from	how
Claude.ai (web / desktop / mobile)	Settings → Connectors → Add custom connector → `https://render.janction.jp/mcp`. "Connect" opens a page that creates a free key
ChatGPT	Settings → Connectors → Advanced → Developer mode → Create → `https://render.janction.jp/mcp` (OAuth)
Claude Code	`claude mcp add --transport http janction-render https://render.janction.jp/mcp`, then `/mcp` to authenticate
Codex	`codex mcp add janction-render --url https://render.janction.jp/mcp`
Cursor / VS Code	Add to Cursor Add to VS Code The button opens the editor; confirm and it is added. Manual: Streamable HTTP at `https://render.janction.jp/mcp`
Other MCP clients	Streamable HTTP at `https://render.janction.jp/mcp`; OAuth or `Authorization: Bearer <api key>`
Terminal (stdio, sends local files)	`claude mcp add janction-render -e JANCTION_RENDER_SERVER=https://render.janction.jp -- uvx --from janction-render janction-render-mcp`

Using JANCTION Render, build a glossy red cube rotating on a grey floor and show me a 4-frame preview.
If it looks right, render 24 frames at 1280x720 as an MP4.

FAQ

Can I use blender-mcp and JANCTION Render at the same time?

Yes. They are separate MCP servers; add both. Edit with blender-mcp, save the .blend, and ask the agent to render it with JANCTION Render.

Does JANCTION Render edit my scene?

No. It renders what you send. The agent edits by changing the bpy script or the .blend and sending it again; the sha256 lookup skips re-uploading unchanged files.

Do I need an API key for the remote MCP?

No. Claude.ai, ChatGPT and Codex open a consent page that creates a free key; the CLI gets one with janction-render key.

Is a local MCP faster?

For editing, yes: it works on the open scene with no upload. For rendering it depends on your GPU; our measured times are on the benchmarks page.

Overview · llms.txt

JANCTION Render v0.4.0 · JasmyLab Inc. · 日本語