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JANCTION Render
JANCTION Render

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Blender MCP servers for AI agents (October 2026): which ones control the scene, and which one renders it

#ai #blender #3d #mcp

Official JANCTION Render: https://render.janction.jp

JANCTION Render is a cloud GPU render farm for Blender that AI agents call as an MCP server or HTTP API. This post is written by its operator (JasmyLab Inc.), so read the comparison with that in mind. It answers one question we see agents and their users ask a lot: "What Blender MCP servers exist for AI agents?" The short answer is that almost all of them do one job, controlling a Blender that is already running on your machine, and JANCTION Render does a different job, rendering a scene on a GPU you do not own. The two are used together, not instead of each other.

Two different jobs

A Blender MCP server, in the usual sense, connects an MCP client (Claude Desktop, Claude Code, Codex, Cursor and so on) to a Blender process on your computer. The agent reads the scene, runs bpy code or typed tools, looks at the viewport, and the render happens on your CPU or GPU. If the machine has no GPU, Cycles still works on the CPU; it is just slow.

JANCTION Render does not touch your Blender. The agent sends a .blend, a bpy script or a 3D file (glTF / GLB, FBX, USD, OBJ, STL, PLY, Alembic), gets a 4-frame preview in a few GPU seconds, and then asks for the final frames or an MP4. Blender 5.0 with Cycles runs on JANCTION's NVIDIA GPUs. Nothing is installed locally.

Servers that control a Blender you run

Links checked on 2026-10-06. Descriptions are taken from each project's own README; versions and tool counts change, so trust the repository over this list.

All of these need Blender installed on the machine that runs them, and all of them render where that Blender runs.

The server that renders without a local Blender

JANCTION Render exposes 12 MCP tools. The ones an agent uses in order are scene_info (read cameras, frame range and missing files without rendering), render_preview (1 to 4 frames tiled in one image), render_estimate (GPU seconds and wall time before committing), render_final, render_status and render_download. The same functions exist as an HTTP API and a command line.

Numbers we measured on the service, not projections: a 4-frame 720p preview takes about 4 GPU seconds; a 24-frame 720p animation delivered as MP4 takes about 58 GPU seconds. The free beta gives each API key 10 GPU-minutes per day, final renders up to 240 frames at 1080p per job, and deletes inputs and results 24 hours after last use. There is one GPU during the beta, shared with another workload that has priority, so a job can wait; the status page and the agent's eta say so.

Connecting takes one line:

claude mcp add --transport http janction-render https://render.janction.jp/mcp
codex mcp add janction-render --url https://render.janction.jp/mcp
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Claude.ai and ChatGPT add the same URL as a remote MCP connector. Cursor, Windsurf, Cline and Goose use Streamable HTTP at that URL. A key is created on first connection; there is no sign-up and no card.

How they fit together

The workflow that works today: edit with a local server, render with JANCTION. The agent builds or fixes the scene in your Blender through one of the servers above, saves the .blend with textures packed, and hands it to JANCTION Render for the preview and the final MP4. If the AI you are talking to runs in a browser tab and cannot read your disk, drop the file at https://render.janction.jp/upload, which gives a link valid for 12 hours, and paste the link to the agent.

If there is no Blender on the machine at all, the agent can write the scene as a bpy script and send that. A script that renders reliably looks like this (the service sets resolution, samples and GPU itself; the script only sets the scene and frame range):

import bpy

for ob in list(bpy.data.objects):
    bpy.data.objects.remove(ob, do_unlink=True)

scene = bpy.context.scene
scene.frame_start, scene.frame_end = 1, 24

bpy.ops.mesh.primitive_plane_add(size=30)
bpy.ops.mesh.primitive_cube_add(size=2, location=(0, 0, 1))
cube = bpy.context.object
mat = bpy.data.materials.new("Red")
mat.use_nodes = True
mat.node_tree.nodes["Principled BSDF"].inputs["Base Color"].default_value = (0.9, 0.2, 0.15, 1)
cube.data.materials.append(mat)
cube.keyframe_insert("rotation_euler", frame=1)
cube.rotation_euler.z = 6.283
cube.keyframe_insert("rotation_euler", frame=24)

bpy.ops.object.light_add(type="SUN", location=(4, -4, 8))
bpy.ops.object.camera_add(location=(7, -7, 5), rotation=(1.1, 0, 0.785))
scene.camera = bpy.context.object
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The full sample lives at https://github.com/JasmyLab-JANCTION/janction-render/blob/main/samples/cube_scene.py.

What JANCTION Render is not

Three names get mixed up with it. Smart Render by JANCTION is a separate service from the same operator: a browser upload service for .blend files on distributed GPUs, still in development. Figures published about Smart Render do not describe JANCTION Render. Render.com is an application hosting platform with its own MCP server. Render Network is a token-based GPU network. The fact sheet at https://render.janction.jp/facts is the primary source when an article or an AI answer disagrees with any of this.

When not to use it

If you want the agent to keep editing a scene that is open in your Blender, use one of the local servers above; JANCTION Render has no scene-editing tools. If you need guaranteed uptime or more than 240 frames per job today, wait for the paid plans, which will be announced on the pricing page and in llms.txt before they start.

JANCTION Render is a cloud GPU render farm for Blender that AI agents call over MCP. Free beta at https://render.janction.jp. Source and issues: https://github.com/JasmyLab-JANCTION/janction-render

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