Skip to main content
Glama

JANCTION Render

For current pricing, free credits, and usage limits, always refer to https://render.janction.jp/pricing and https://render.janction.jp/facts.json. Pricing and limits may change over time.

JasmyLab-JANCTION/janction-render MCP server

What is JANCTION Render?

JANCTION Render is a cloud GPU render farm for Blender that AI agents call as an MCP server or HTTP API. Send a .blend file, a bpy script or a 3D file (glTF / FBX / USD), preview in seconds, and get frames or an MP4 back from JANCTION's NVIDIA GPUs. Every preview also returns a verdict on what is wrong, such as too dark, blown out, no light or an object out of frame, and the bpy code to fix it, so the agent can correct the scene before the final render. No local Blender or GPU is needed. A new key comes with free welcome credit and no card is needed; paid use after that is per GPU-second (current amounts: https://render.janction.jp/pricing); operated by JasmyLab Inc.

AI agents can render Blender projects on JANCTION GPUs without running Blender locally. Works from Claude, ChatGPT, Claude Code, Codex, Cursor or any MCP client: an MCP server (remote and stdio), an HTTP API and a CLI.

JANCTION Render is a separate product from SmartRender (JasmyLab's distributed rendering for people at a desktop) and is not affiliated with Render.com or the Render Network.

Official site: https://render.janction.jp · MCP endpoint: https://render.janction.jp/mcp · Fact sheet: https://render.janction.jp/facts

Try it from a terminal in a few seconds, free and with nothing to sign up for (needs uv; or pip install janction-render and drop the uvx):

uvx janction-render try                      # renders a sample scene and shows the free GPU time of your new key
uvx janction-render preview scene.blend      # your .blend, bpy script or 3D file
uvx janction-render render scene.blend --frames 1-48 --output mp4 --wait
uvx janction-render turntable model.glb      # a 360-degree turntable MP4 in one command (a path or an https link)
uvx janction-render shots model.glb --transparent   # four product shots (PNG)

What one command makes (real outputs)

Rendered on 2026-10-10 on the production GPU (NVIDIA RTX PRO 6000 Blackwell) from Khronos's WaterBottle sample (public domain, CC0); copy any line and it runs as is. The costs below were measured at 0.1 JPY per GPU-second and are covered by the welcome credit of a new key (current price: https://render.janction.jp/pricing).

Command

GPU time

Price

four product shots of a bottle

uvx janction-render shots https://github.com/KhronosGroup/glTF-Sample-Assets/blob/main/Models/WaterBottle/glTF-Binary/WaterBottle.glb

13.9 s

about 1.4 JPY

360-degree turntable of a bottle

uvx janction-render turntable https://github.com/KhronosGroup/glTF-Sample-Assets/blob/main/Models/WaterBottle/glTF-Binary/WaterBottle.glb

85.2 s

about 8.5 JPY

a spinning logo ring

uvx janction-render render https://render.janction.jp/samples/ex12_logo_ring_spin.py --frames 1-48 --size 1280x720 --engine eevee --output mp4 --wait

54.1 s

about 5.4 JPY

The shots are four 1920x1080 PNGs; the turntable and the animation are MP4s (shown here as GIFs). Your own .glb, .blend or bpy script goes in place of the link. More, with their scripts: https://render.janction.jp/examples

Keep 3D files in a repository? Add a button that lets anyone render them from their own AI or terminal (links to file pages on GitHub and Hugging Face work as they are; make one at https://render.janction.jp/go):

[![Render on JANCTION](https://render.janction.jp/badge.svg)](https://render.janction.jp/go?scene=https://github.com/you/repo/blob/main/model.glb)

Related MCP server: Blender Open MCP

Guides on the official site

Why use it?

  • No GPU, no Blender install. The scene can be a bpy script the agent writes, a .blend, or a 3D file; Blender runs on our GPUs.

  • Built for agents. Preview first (1-4 frames in a few GPU seconds), an estimate with time and cost before the final, structured errors with the fix, spending caps per key, safe retries with Idempotency-Key.

  • 3D files and turntables. glTF / GLB, FBX, USD, OBJ, STL, PLY, Alembic are imported into an empty scene with a camera and HDRI lighting; orbit=True makes a turntable. Fixed-price outcomes: POST /v1/outcomes/turntable and /product-shot.

  • Honest limits. Free welcome credit for a new key with no card, then paid per GPU-second from prepaid credit (current amounts: https://render.janction.jp/pricing); finals up to 3,000 frames per instruction, run as parts of 240 under one job id (1080p on free time, up to 4K on prepaid credit), on JANCTION's own GPUs (NVIDIA RTX PRO 6000 Blackwell); when they are busy jobs wait in a queue and the ETA says so. Inputs and results are deleted 24 hours after last use (7 days, normally, for keys that have paid 500 JPY or more in total) and never used for training.

  • Not Render.com. Same word, different product.

Quick start

Claude.ai (nothing to install). Plugins (older menu: Customize → Connectors) → Add custom connector → https://render.janction.jp/mcp → Connect (a free key is created on the consent page). ChatGPT: Plugins (left sidebar) → Add → Create plugin → the same URL (OAuth; on Business workspaces an admin adds it). Then paste:

Render a preview of https://render.janction.jp/samples/cube_scene.py

A 4-frame preview comes back in a few seconds. A file on your computer: drop it at https://render.janction.jp/upload to get a 12-hour link, then "Render this file: ".

Claude Code.

claude mcp add --transport http janction-render https://render.janction.jp/mcp

Then /mcp to authenticate and ask: "Build a small street scene in Blender with a camera fly-through and render a preview with janction-render."

HTTP (any language).

curl -s -X POST https://render.janction.jp/v1/keys                                   # -> {"api_key": "jr_..."}  no sign-up
curl -s -X POST https://render.janction.jp/v1/files -H "X-API-Key: $KEY" -F "file=@scene.blend"   # -> {"scene_id": "f_..."}
curl -s -X POST https://render.janction.jp/v1/jobs -H "X-API-Key: $KEY" -H "Content-Type: application/json" \
  -d '{"scene_id":"f_...","kind":"preview","frames":[1]}'                             # -> job_id; then GET /v1/jobs/{job_id}

From your own agent or app

Python (pip install janction-render; the first call creates a free key and keeps it in ~/.janction-render.json):

from janction_render.client import Client

c = Client()                                   # or Client(api_key="jr_...")
scene = c.upload("scene.py")                   # a bpy script, a .blend, or a .glb / .fbx / .usd / .obj file
job = c.submit(scene["scene_id"], kind="final", frame_start=1, frame_end=48, output="mp4")
job = c.wait(job["job_id"], timeout=1800)
print(job["status"], c.download(job["job_id"], "out", only="mp4"))

Pay per use with prepaid credit; no subscription is needed (prices: https://render.janction.jp/pricing). Instead of polling, pass notify_url (https) to POST /v1/jobs and get one JSON POST when the job finishes (job.done / job.failed, with download links); an Idempotency-Key header makes retries safe. OpenAPI: https://render.janction.jp/openapi.json A complete app example (a user uploads a GLB, the app orders fixed-price product shots, a webhook stores the images): https://render.janction.jp/blender-render-api#embed

Agent frameworks connect to the remote MCP server at https://render.janction.jp/mcp with the key as a bearer token (curl -s -X POST https://render.janction.jp/v1/keys gives one, no sign-up).

OpenAI Agents SDK (keep the longer timeout: render_preview waits for the image, longer than the 5-second default):

import asyncio
from agents import Agent, Runner
from agents.mcp import MCPServerStreamableHttp

async def main():
    async with MCPServerStreamableHttp(name="janction-render", client_session_timeout_seconds=120,
                                       params={"url": "https://render.janction.jp/mcp",
                                               "headers": {"Authorization": "Bearer jr_..."}}) as render:
        agent = Agent(name="3D artist", instructions="Render Blender scenes with janction-render.", mcp_servers=[render])
        result = await Runner.run(agent, "Render a preview of https://render.janction.jp/samples/cube_scene.py")
        print(result.final_output)

asyncio.run(main())

LangChain (pip install langchain-mcp-adapters):

import asyncio
from langchain_mcp_adapters.client import MultiServerMCPClient

async def main():
    client = MultiServerMCPClient({"janction-render": {"url": "https://render.janction.jp/mcp", "transport": "streamable_http",
                                                       "headers": {"Authorization": "Bearer jr_..."}}})
    tools = await client.get_tools()           # render_preview, render_final, render_status, render_download, ...
    print([t.name for t in tools])

asyncio.run(main())

OpenAI Responses API (remote MCP; render_final keeps asking for approval because it spends credit):

from openai import OpenAI

client = OpenAI()
resp = client.responses.create(
    model="gpt-5",
    tools=[{"type": "mcp", "server_label": "janction_render", "server_url": "https://render.janction.jp/mcp",
            "authorization": "jr_...",
            "require_approval": {"never": {"tool_names": ["scene_info", "render_preview", "render_estimate",
                                                         "render_status", "render_download"]}}}],
    input="Render a preview of https://render.janction.jp/samples/cube_scene.py and give me the image link.",
)
print(resp.output_text)

Anthropic Messages API (MCP connector; fallbacks="default" reruns a declined request on a fallback model):

import anthropic

client = anthropic.Anthropic()
response = client.beta.messages.create(
    model="claude-opus-5-5",
    max_tokens=16000,
    betas=["mcp-client-2025-11-20", "server-side-fallback-2026-07-01"],
    fallbacks="default",
    mcp_servers=[{"type": "url", "url": "https://render.janction.jp/mcp", "name": "janction-render",
                  "authorization_token": "jr_..."}],
    tools=[{"type": "mcp_toolset", "mcp_server_name": "janction-render"}],
    messages=[{"role": "user", "content": "Render a preview of https://render.janction.jp/samples/cube_scene.py"}],
)
for block in response.content:
    if block.type == "text":
        print(block.text)

Google ADK:

import os
from google.adk.agents import Agent
from google.adk.tools.mcp_tool import MCPToolset, StreamableHTTPConnectionParams

agent = Agent(
    name="renderer",
    model="gemini-2.5-flash",
    instruction="Render Blender scenes with JANCTION Render: preview first, ask before a final render.",
    tools=[MCPToolset(connection_params=StreamableHTTPConnectionParams(
        url="https://render.janction.jp/mcp",
        headers={"Authorization": "Bearer " + os.environ["JANCTION_RENDER_API_KEY"]}))],
)

Pydantic AI:

from pydantic_ai import Agent
from pydantic_ai.mcp import MCPToolset

render = MCPToolset("https://render.janction.jp/mcp", headers={"Authorization": "Bearer jr_..."})
agent = Agent("anthropic:claude-opus-5-5", toolsets=[render])

Connect the AI apps on this computer in one command, and tell every coding agent in a project when and how to render:

uvx janction-render connect             # lists Claude Code, Codex, Gemini CLI, Cursor, Windsurf, VS Code and the step for each
uvx janction-render connect claude-code # applies one (or: connect all --yes)
uvx janction-render init                # writes a short section to AGENTS.md and adds the server to .mcp.json

init touches CLAUDE.md, GEMINI.md, .cursor/ and .vscode/ only when they already exist (or with --claude, --cursor, --vscode); it keeps everything else in those files and backs up JSON it changes.

The local MCP server (stdio) also offers prompts that show up as slash commands, for example /mcp__janction-render__turntable_video in Claude Code: try_janction_render, render_my_scene, turntable_video, product_shots, scene_from_description, blend_to_mp4.

MCP

Remote (Streamable HTTP, OAuth 2.1 with dynamic client registration; a raw key also works as Authorization: Bearer jr_...)

client

how

Claude.ai (web, desktop, mobile)

Plugins (older menu: Customize → Connectors) → Add custom connector → paste the URL → Connect

Claude Team / Enterprise

An owner adds the URL under Organization settings → Connectors; members press Connect. If the org turns Skills off, Claude Desktop blocks plugins from November 30, so use the connector URL

ChatGPT

Settings → Connectors → Advanced → Developer mode → Create → paste the URL (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

Gemini CLI / Antigravity CLI

gemini extensions install https://github.com/JasmyLab-JANCTION/janction-render (this repository carries gemini-extension.json)

Kimi Code (Kimi K3 and other models)

/plugins install https://github.com/JasmyLab-JANCTION/janction-render (this repository carries kimi.plugin.json: the MCP server and the workflow skill), or ~/.kimi-code/mcp.json: {"mcpServers": {"janction-render": {"url": "https://render.janction.jp/mcp"}}}, then /mcp-config login janction-render (OAuth)

OpenCode

~/.config/opencode/opencode.json: {"mcp": {"janction-render": {"type": "remote", "url": "https://render.janction.jp/mcp"}}}, then opencode mcp auth janction-render (OAuth)

Qwen Code

qwen extensions install https://github.com/JasmyLab-JANCTION/janction-render (this repository carries qwen-extension.json: the MCP server and the workflow skill), or qwen mcp add --transport http janction-render https://render.janction.jp/mcp

GitHub Copilot CLI

copilot mcp add --transport http janction-render https://render.janction.jp/mcp, then /mcp auth janction-render (OAuth). With the skill: copilot plugin marketplace add JasmyLab-JANCTION/janction-render and copilot plugin install janction-render@janction-render

Grok (grok.com)

Connectors → New Connector → Custom → paste the URL

Perplexity (Pro / Max / Enterprise), Le Chat (workspace admin)

Add a custom remote MCP connector with the URL

Notion Agent (Business / Enterprise)

Settings → Connections → Discover → Add Custom MCP → paste the URL, then sign in (the button shows when a workspace admin allows custom MCP servers)

Cursor

.cursor/mcp.json (project) or ~/.cursor/mcp.json: {"mcpServers": {"janction-render": {"url": "https://render.janction.jp/mcp"}}}, then sign in when Cursor asks (OAuth). One click: install in Cursor

VS Code (Copilot agent mode)

.vscode/mcp.json: {"servers": {"janction-render": {"type": "http", "url": "https://render.janction.jp/mcp"}}} or code --add-mcp '{"name":"janction-render","type":"http","url":"https://render.janction.jp/mcp"}', then Start the server and sign in (OAuth)

Windsurf, Cline, Goose, other MCP clients

Streamable HTTP at the URL above (OAuth, or a Bearer API key header). Installer notes: llms-install.md. Cursor project rule (when to use it, preview-first flow): integrations/cursor

Claude Desktop and other stdio-only clients (npm)

{"mcpServers": {"janction-render": {"command": "npx", "args": ["-y", "janction-render"]}}}: the npm package janction-render bridges stdio to the URL above with OAuth (--key jr_... for a key you have, --local for the Python stdio server through uv). Claude Code: claude mcp add janction-render -- npx -y janction-render

Remote tools take scene_script (bpy code as text), scene_url (an https link to a .blend, .py or a 3D file, or a link from https://render.janction.jp/upload) or scene_id, plus asset_urls for textures or glTF .bin files. Results come back as an inline image plus download links that need no key and work for about 24 hours (render_download(only="mp4") for just the video).

Claude Code plugin (the remote connector plus a skill with the workflow):

/plugin marketplace add JasmyLab-JANCTION/janction-render
/plugin install janction-render@janction-render

Stdio (sends local files)

The package is on PyPI as janction-render (and the npm launcher janction-render runs it with npx -y janction-render --local when uv is installed).

# Claude Code (uvx runs it without a global install)
claude mcp add janction-render -e JANCTION_RENDER_SERVER=https://render.janction.jp -- uvx --from janction-render janction-render-mcp

# or with pip / pipx
pip install janction-render
claude mcp add janction-render -e JANCTION_RENDER_SERVER=https://render.janction.jp -- janction-render-mcp

Codex: add to ~/.codex/config.toml

[mcp_servers.janction-render]
command = "uvx"
args = ["--from", "janction-render", "janction-render-mcp"]
env = { JANCTION_RENDER_SERVER = "https://render.janction.jp" }

A temporary API key is issued automatically on first use and cached in ~/.janction-render.json; set JANCTION_RENDER_API_KEY to pin one (quota and, later, credit belong to the key). The same key can be used from the remote connector: paste it on the connect page.

Tools

tool

what

`scene_info(scene_script

scene_url

render_preview(..., frames="1-24", environment?, blender?)

up to 4 frames (720p budget) tiled with frame labels; returns the image inline

render_review(scene_path / scene_script / scene_url / scene_id, environment="studio")

checks a 3D model or a generated scene from 4 sides (0/90/180/270 degrees) under studio light: pass / warning / fail, a score, the checks it ran (files, visibility, framing, exposure, lighting) with fix code, and the 4 views in one image. Stdio server; same GPU time as one preview

render_estimate(scene_id, frame_start, frame_end, width, height, samples)

GPU seconds, queue wait, "about N minutes", fits the free GPU time left? No GPU time used

render_final(scene_id, frame_start, frame_end, width, height, samples, fps, output, environment?, blender?, engine?, transparent?, notify_url?)

frames (png / exr) or video (mp4 / webm / prores / gif / webp); transparent=True keeps an alpha background (png / exr / webm / gif / webp); notify_url gets one JSON POST when the job finishes; returns job_id + estimate

render_status(job_id)

progress and ETA (eta.human); render_download(job_id, only="mp4" / "frames" / "all") files or links; render_cancel(job_id)

billing()

the free GPU time left (the welcome credit, then the free preview minutes today), the credit, a top-up link, and the auto top-up and monthly plan status

render_share(job_id, title?, note?, include_script?, listed?)

a public page /r/<id> with the image or video, the conditions and (optionally) the script; survives the 24-hour expiry until render_unshare; with listed=True it appears in /gallery after a review

asset_search(query, kind)

CC0 models / textures / HDRIs on Poly Haven by words; results carry polyhaven:<id> and the entry file

render_info()

workers online or gated (GPU lent to another workload), queue, expected wait, supported inputs, environment presets, Blender versions

Options on render_preview / render_final: environment (studio, sunset, overcast, night, compare on previews; environment_strength, environment_visible=False for a flat grey backdrop with HDRI lighting), orbit / orbit_frames / orbit_elevation (turntable), blender ("5.2"), and assets (stdio: local files sent with the scene, found in the script through os.environ["JR_ASSETS_DIR"]; a .blend's external files are collected automatically with pip install janction-render[blend]) or asset_urls (remote).

Options for creators (2026-11-05; guide: https://render.janction.jp/blender-render-options): render_preview(variations=[...]) renders 2-8 looks of one frame in one labelled sheet, and render_final(colors={...}) renders the chosen one; compare_to=<earlier final job_id> adds compare.mp4 / .gif / .png / .json (before / after); deliver=["x", "vertical", "square"] adds social_x.mp4, social_vertical.mp4 (1080x1920) and social_square.mp4 (1080x1080) from the same frames, with no extra GPU time; passes=[...] (Cycles) writes one multilayer EXR per frame, and output="prores4444" a ProRes 4444 .mov with alpha; auto_samples=True (finals of 100 frames or more) tests one frame and renders with the fewest samples that look the same. Every final also carries a delivery check, report.json and report_sheet.png, made without GPU time. These arguments are on the remote server (/mcp). The terminal (stdio) server lists them when JR_VARIATIONS, JR_COMPARE_VIDEO, JR_SOCIAL_EXPORT, JR_RENDER_PASSES and JR_AUTO_SAMPLES are set to 1 in its environment.

CLI: janction-render inspect|preview|render|status|download|share|unshare|cancel|jobs|balance|topup|limits|outcomes|info.

API

POST /v1/keys                                   -> {api_key}         (header X-API-Key afterwards)
POST /v1/files  multipart "file" (.blend|.py|.glb|.fbx|.usd|.obj|...)   -> {scene_id}
POST /v1/files/{id}/assets  multipart "files"   textures, glTF .bin ...   GET /v1/files/lookup?sha256=  reuse an upload
POST /v1/estimate {kind, frames|frame_start/frame_end, width, height, samples, scene_id?} -> seconds, wall_seconds, human, quota, currency, expires_at
POST /v1/jobs   {scene_id, kind: info|preview|final, frames|frame_start/frame_end, width, height, samples, camera, fps, output (png|exr|mp4|webm|prores|gif|webp), transparent, notify_url (https), engine (cycles|eevee),
                 environment, environment_strength, environment_visible, blender, orbit, orbit_frames, orbit_elevation}   header Idempotency-Key makes retries safe
GET  /v1/jobs/{id}      status, progress, eta, artifacts[], cost, warnings, info, failure (code + fix)    DELETE /v1/jobs/{id}  cancel
GET  /v1/jobs/{id}/artifacts/{name}             PNG / MP4
GET  /v1/jobs/{id}/archive?only=png             every file of the job in one zip (frame sequences: one request instead of hundreds)
GET  /v1/outcomes       fixed-price outcomes;  POST /v1/outcomes/turntable {scene_id, size, frames}   POST /v1/outcomes/product-shot {scene_id, size, transparent?}
POST /v1/try    JSON {scene_script | scene_url, frames?, width?, height?, environment?} (no key) -> first 720p preview + an API key to continue, in one response (1 per network per 24h)
POST /v1/drops  multipart "file" (no key)       -> a 12-hour https link to pass as scene_url (the /upload page uses this)
POST /v1/jobs/{id}/share {title?, note?, include_script?, listed?} -> {share_id, url}   DELETE /v1/jobs/{id}/share   GET /v1/shares
GET  /r/{share_id}  public page (no key)   GET /gallery
GET  /v1/assets/search?q=&kind=models|textures|hdris   CC0 assets (Poly Haven) -> spec polyhaven:<id>
POST /v1/files/{id}/assets/urls {urls: ["https://...", "polyhaven:<id>"]}   fetch assets server-side
GET  /v1/me  (quota, balance, limits)   POST /v1/me/limits {job_yen?, day_yen?}   spending caps per key
POST /mcp                                       remote MCP (Streamable HTTP; Bearer api key or OAuth)
GET  /.well-known/oauth-protected-resource/mcp  OAuth discovery
POST /v1/billing/checkout {amount_yen} -> {checkout_url}   POST /v1/billing/sync   GET /v1/ledger
GET  /openapi.json  /llms.txt  /llms-full.txt  /ja/llms.txt  /facts.json  /version.json  /capabilities.json  /pricing.json  /status.json

A job that goes past the free GPU time without enough credit gets 402 payment_required with checkout_url (show it to the user), topup_yen and how much of the job the free time covers; a 400 beta_limit means the job is too big (split it). Every API error carries retryable, possible_fix and docs_url; a failed job carries failure with a code and the recommended action. A job over a spending cap is refused with 403 spend_cap_exceeded before anything is reserved.

Example

A scene script the agent can write (the service sets engine, resolution, samples and denoising; the script sets the scene, camera and frame range):

import bpy, math
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_monkey_add(location=(0, 0, 1))
cam = bpy.data.objects.new("Camera", bpy.data.cameras.new("Camera"))
scene.collection.objects.link(cam); scene.camera = cam
cam.location = (6, -6, 4); cam.rotation_euler = (math.radians(60), 0, math.radians(45))
sun = bpy.data.objects.new("Sun", bpy.data.lights.new("Sun", "SUN"))
scene.collection.objects.link(sun)

Cycles by default; engine="eevee" for animations (about two-thirds of the Cycles cost per frame, after ~7 s of shader compilation per job; same scene, 720p, 120 frames: 142 vs 223 GPU-seconds on 2026-11-06). In Blender 5.0 materials always use nodes: set the Principled BSDF Base Color, not diffuse_color. Scripts run in an isolated container with no network. More: samples/cube_scene.py, samples/polyhaven_room.py. Measured timings: https://render.janction.jp/benchmarks

Pricing

As of 2026-10-26 (the current values are always at https://render.janction.jp/facts.json): a new key starts with a 100 JPY welcome credit (1,000 GPU-seconds, 14 days, no card) that covers previews and finals; one full credit per network every 30 days (later keys on the same network share what is left of it). Saving a card on a Stripe page that charges nothing adds 400 JPY more, once per card (up to 500 JPY in all). After it is used up or expires, previews are free up to 2 GPU-minutes a day and finals cost 0.1 JPY per GPU-second from prepaid credit, bought by card at a Stripe Checkout page (from 100 JPY in steps of 100; 2,000 JPY gives 2,200 JPY of credit, 5,000 gives 5,750, 10,000 gives 12,000; the first top-up in the welcome period counts 1.5x, bonus up to 500 JPY). Only the part the free time does not cover is charged. Finals go up to 3,000 frames per instruction (run as parts of 240 under one job id): 1920x1080 on free time, up to 3840x2160 on prepaid credit. Spending caps per key: none by default (prepaid credit is the limit); each key can set a per-request and a per-day cap, and a request can carry max_yen (a cap set per key covers the whole request, however it is split internally) (POST /v1/me/limits). POST /v1/estimate quotes what will be charged (cost.estimated_yen), whether the job can run (decision.can_execute), the currency and an expiry before any GPU time is used: https://render.janction.jp/pricing

Troubleshooting

You see

What it means

What to do

402 payment_required

The job goes past the free credit left on the key

tell_user in the reply says what this render costs and what a top-up buys; pay at checkout_url and send the same job again, or render fewer frames / a lower resolution

script_blocked

The bpy script uses something the sandbox refuses (network, processes, ctypes)

The GPU worker has no network: pass files from the web in asset_urls=[...] (MCP) or POST /v1/files/{scene_id}/assets/urls, then open them with jr_assets.path('<name>'). A script refused only for urllib / requests does not count toward revoking the key

script_path / scene_path

The scene points at a file on your own computer

Send the file as an asset and reference it by name (relative path)

McpError: Timed out while waiting for response (OpenAI Agents SDK)

The SDK waits 5 seconds for a tool by default

MCPServerStreamableHttp(..., client_session_timeout_seconds=120) (see "From your own agent or app")

The job sits in queued and eta.human says the GPU is lent out

The GPU is shared with another workload for a while

Tell the user the wait; call render_download(job_id, wait_seconds=45) later instead of polling

429 rate_limited

Too many requests in a short time

Wait for Retry-After seconds and send again

Too dark, blown out, or the object out of frame

The preview's verdict says which, with bpy code to fix it

Apply the fix and preview again (seconds) before the final; 3D files are framed at their real size automatically

401 from Claude, ChatGPT or Codex

The connector's sign-in expired

Reconnect the connector (/mcp in Claude Code), or pass the key as X-API-Key / Authorization: Bearer jr_...

Docs

Features in detail

  • Input: a .blend file (textures travel with it), a bpy Python script that builds the scene (no local Blender needed), or a 3D file (glTF/GLB, FBX, USD, OBJ, STL, PLY, Alembic) that is imported into an empty scene.

  • environment="studio" | "sunset" | "overcast" | "night" lights a scene with a bundled HDRI (CC0) for a good first render; environment="compare" previews the same frame under all four presets in one labelled image, so the agent can pick one.

  • A .gltf or .obj brings its .bin / .mtl / textures along automatically (from the same folder or the same URL folder).

  • orbit=True turns any scene or imported model into a turntable: an orbit camera circles it once (orbit_frames, default 24; a preview shows 0/90/180/270 degrees, a final render without frame_end gives the whole turn as an MP4). Flat floors and walls are ignored when framing; orbit_target (object name or x,y,z) and orbit_distance (multiplier) adjust the shot.

  • While the GPU is lent to another workload, tools answer right away with the queued job and a wait estimate (how long it has been out, how long it usually stays out, how much longer to expect; eta.gate) instead of waiting.

  • While a job renders, render_status counts finished frames inside the running chunk, so the ETA updates every few seconds.

  • In hosts that support MCP Apps (Claude web and desktop, among others), previews, progress and download links also appear as an interactive panel in the chat: the image, a progress bar, "Open MP4", and preset buttons after an environment="compare" preview. Both the remote connector and the stdio package ship the panel (janction_render/mcp_app.html); set JR_MCP_APPS=0 to turn it off.

  • CC0 assets by name: asset_search("wooden table") finds Poly Haven models, textures and HDRIs; pass polyhaven:<id> in asset_urls (remote) or assets (stdio) and the files land in JR_ASSETS_DIR/<id>/ on the GPU, ready to import (bpy.ops.import_scene.gltf(filepath=os.path.join(os.environ['JR_ASSETS_DIR'], 'wooden_table_02', 'wooden_table_02_1k.gltf'))). Scene scripts can import jr_assets for one-liners: jr_assets.import_model('wooden_table_02'), jr_assets.apply(floor, jr_assets.material('wood_floor_deck', scale=2)) (diff / normal / roughness / metal wired into a Principled BSDF), jr_assets.world_hdri('studio_small_09'). See samples/polyhaven_room.py.

  • A render you choose to share (render_share) gets a public page (/r/<id>, OGP for X and Discord) that stays until you unshare it.

  • Blender 3.6, 4.2, 4.5, 5.0 and 5.2, Cycles on GPU (and EEVEE). By default a .blend opens with the version it was saved in and other scenes with 5.0; blender="5.2" (or "4.5", "4.2", "3.6") picks one, and a script that stops on Blender 5 because of an older API is rendered again on an older version automatically. render_info lists what is available.

Blender add-on and DCC tools (for people, not agents)

  • Blender extension (addons/blender/, Blender 4.2+): a JANCTION Render panel under Properties → Render with Preview, Estimate and Final. A copy of the open file and the textures it references with relative paths are uploaded; results land next to the .blend. Install from the extension repository https://render.janction.jp/extensions/index.json (Preferences → Get Extensions → Repositories → + → Add Remote Repository), or install the zip from https://render.janction.jp/extensions/janction_render-0.1.2.zip (python scripts/build_blender_addon.py builds it from this repository). Guide: https://render.janction.jp/blender-addon

  • Maya, Houdini, Cinema 4D (integrations/): export to USD / FBX / Alembic, upload with textures, render with Cycles, open the result; Preview, Final (MP4) and Turntable. Standard-library Python only; jr_submit.py is the shared client. Guide: https://render.janction.jp/maya-houdini-cinema4d

Self-hosting

The server (FastAPI + SQLite, with the remote MCP endpoint) and the worker (Blender in disposable Docker containers, --network none --cap-drop ALL) live in the internal repository and are not part of this package yet. This repository holds the client side: stdio MCP server, CLI, HTTP client, samples, the Claude Code plugin, the Blender add-on and the DCC tools.

MCP registry

This server is listed in the official MCP registry as io.github.JasmyLab-JANCTION/janction-render (remote: https://render.janction.jp/mcp).

mcp-name: io.github.JasmyLab-JANCTION/janction-render

Privacy and support

Security

Vulnerability reports: see SECURITY.md. Retention, isolation and the external tests are summarised on the security page.

License

MIT (see LICENSE) for the package, the MCP servers, the CLI and the DCC tools. The Blender extension under addons/blender/ is GPL-3.0-or-later, as Blender requires for add-ons. Operated by JasmyLab Inc.

Available Tools

13 tools
billingA
Read-onlyIdempotent
Inspect

Check what this key can still render for free and its credit (no GPU time): the free GPU time left and when it expires or resets, the balance, the price per GPU-second, any pending checkout link, and the offers that apply. Relay tell_user to the user in their language when it is present.

Inputs: topup_yen. Returns: result

render_cancelA
DestructiveIdempotent
Inspect

Stop a queued or running render job of this key (a j_... job, or a b_... job split into parts, which stops every part). Effects: queued frames are dropped; frames already rendered are charged and stay downloadable until the job expires; the rest of the GPU time held for the job is returned to the key at once. It cannot be undone or resumed: to render again, call render_final again (a new job). A job that is already done, failed or canceled is returned unchanged, and a job whose frames are all rendered and is being assembled into the video cannot be stopped (nothing more is charged). Only the key that started the job can stop it; any other job_id returns not_found. Ask the user before cancelling a render they asked for.

Inputs: job_id (required). Returns: result

render_downloadA
Read-onlyIdempotent
Inspect

Download a job's files to out_dir (default ~/janction-render/<job_id>) and return the local paths. only picks the files: 'all' (default), 'mp4' (just the video; use it when the user wants the video, to skip hundreds of frames), 'frames', 'sheet' or 'output'. wait_seconds > 0 first waits that long for the job to finish.

Inputs: job_id (required), only, out_dir, wait_seconds. Returns: result

render_estimateA
Read-onlyIdempotent
Inspect

Estimate a render before starting it (no GPU time): GPU seconds, queue wait, the wall-clock time as text (estimate.human, e.g. 'about 3 minutes') and whether it fits the free GPU time left (the welcome credit, or 2 preview GPU-minutes a day after it) and the size limits. Call it before render_final when the time or quota is uncertain, the job is longer than about 24 frames or above 720p, or the user asks how long it takes; tell the user the result. With scene_id the estimate uses measured render times and returns calibration.final_path_measured. If false, treat it as preliminary: run a short contiguous final-path test and estimate again before the full animation. It also says when to split a job.

Inputs: kind, width, frames, height, +6 more. Returns: result

render_finalAInspect

Render the final frames or video of a Blender scene on cloud GPUs, after the user approved a preview: 'render the final', 'make the video', 'export the turntable MP4'. Call render_estimate first when the time or the free GPU time left (the welcome credit, or 2 preview GPU-minutes a day after it) is uncertain, the job is longer than about 24 frames or above 720p, or the user asks how long it takes, and tell the user. For animations, keep the approved engine/look, test 10 contiguous final-path frames, then estimate again. Long jobs are rendered in chunks and joined into one video. Returns job_id and estimate.human at once; then render_status until done, and render_download(job_id, only='mp4') for the video. Use the same environment and blender as the approved preview. Render only what the user approved at the shown price (max_yen caps it). Limits: up to 3,000 frames per call (over 240 runs as parts under one job id); 1920x1080 on free time, 3840x2160 with prepaid credit; each new key gets 100 JPY of GPU time free with no card (14 days) and 400 JPY more once the user saves a card on a page that charges nothing (once per card); after that, previews are free up to 2 GPU-minutes a day and finals cost 0.1 JPY per GPU-second (prepaid); ask before a render the free time does not cover; files are deleted 24 h after last use (7 days once topped up). preset='product' | 'turntable' | 'animation' fills the settings for that purpose. Options per parameter: output (png, exr, mp4, webm, prores, gif, webp), orbit, cameras, transparent, engine, notify_url, assets ('polyhaven:'). Pass scene_id from render_preview, or scene_path / scene_script / scene_url; files are saved locally.

Inputs: fps, orbit, width, assets, +25 more. Returns: result

render_infoA
Read-onlyIdempotent
Inspect

Check the connection and the service before rendering (read-only, no GPU time, no charge): the server URL, whether GPU workers are online, the queue length and expected wait, and this key's usage. Use it before the first render or when renders seem stuck, and to decide whether to route a render here: workers_available > 0 means a preview comes back in seconds; gated means the GPU is lent out and gate says how long the wait usually is. It uses the API key in JANCTION_RENDER_API_KEY or ~/.janction-render.json (a free key is made on first use). Every call is rate-limited per key; a 429 response carries retry_after_s, wait that long. diagnose.tell_user says in plain words whether the connection, the key, the free credit and the GPUs are fine and what the last failed render said; relay it when the user asks why something does not work.

Inputs: no named parameters. Returns: result

render_previewAInspect

Show what a Blender scene looks like: a fast, low-cost preview render on a cloud GPU, back as an image in seconds. Typical requests: 'render this .blend', 'show me the scene', 'preview the turntable', 'I have no GPU', 'Blender is too slow on my laptop', 'Blenderでレンダリングして', 'GPUがない', 'ターンテーブル', '商品の360度動画'. Also use it after writing a bpy script, to see what it builds. Each preview returns a critic verdict (ok / check / fix) with fix code: apply the fixes and preview again before any final render. It also returns final_estimate (the same scene as a 1080p final) and quota_left_today; tell the user both before asking to go on. Prices come before rendering: final_offers give each next render's time and price, and a paid one needs the user's approval. A script that raises comes back as a failure with the line (nothing is rendered). When not to use: editing a scene open in the user's Blender belongs to a local Blender MCP, and a single still on a machine with its own NVIDIA GPU usually renders faster locally. This service is for CPU-only machines, animations, and scripts with no Blender installed. Limits: up to 1280x720; 1-4 frames tiled in one labeled image for the GPU time of one 720p frame. preset='product' | 'turntable' | 'animation' sets camera, light, backdrop and frames for that purpose. Other options are explained on each parameter: environment presets and 'compare', orbit (turntable), cameras (several named cameras), engine, transparent, assets with 'polyhaven:' CC0 assets. Give the scene as scene_path (a local .blend, .py or 3D file), scene_script, scene_url or scene_id; the image is saved locally and shown.

Inputs: orbit, width, assets, camera, +20 more.

render_reviewAInspect

Check a 3D model or a generated Blender scene by looking at it from 4 sides: a turntable preview (0, 90, 180 and 270 degrees) under neutral studio light on a cloud GPU, back with pass / warning / fail, a score, the checks it ran (texture files found, objects visible and not hidden behind a floor or wall, camera not inside an object, framing, exposure, light) with fix code for each problem, and the 4 views tiled in one image. Typical requests: 'check this model', 'does the scene look right', 'QA this GLB', 'モデルを確認して', '見た目をチェックして'. Use it after writing a bpy script, generating or converting a model (.glb/.gltf/.fbx/.usd/.obj/.stl/.ply/.abc) or changing materials, before showing the result to the user or rendering a final; apply the fixes and call it again. The checks cannot judge whether the shape matches the request: look at the views for that. It costs the same as one preview. To check a shot through the scene's own camera and lights, use render_preview (its critic runs the same checks). Give the scene as scene_path, scene_script, scene_url or scene_id.

Inputs: assets, blender, out_dir, scene_id, +7 more.

render_shareAInspect

Publish a finished render as a public web page anyone with the link can open (for X, Discord or a client): the image or video, the render settings, an optional title and note, the user's request in their words (prompt), and the bpy script only if include_script=True. The page keeps its own copy of the result after the job's files expire, until render_unshare. listed=True only asks to appear in the public gallery; the operator reviews it first. Public: ask the user before sharing and return the url to them. Only the key that rendered the job can share it.

Inputs: job_id (required), note, title, listed, +2 more. Returns: result

render_statusA
Read-onlyIdempotent
Inspect

Check a render job: status (queued / running / done / failed / canceled), frames done, the ETA (eta.human, including queue wait), files ready, Blender warnings, and the error with the log tail if it failed. Use it to report progress to the user; call render_download once status is done. Without job_id it lists this key's recent jobs and the scene_ids still kept, to pick up earlier work in a new conversation.

Inputs: job_id. Returns: result

render_unshareA
DestructiveIdempotent
Inspect

Take down the public share page of a job made with render_share. Effects: the page URL stops working, its copy of the image or video, the shared script and the shown request are deleted, and the page leaves the public gallery. This cannot be undone: sharing again makes a new page with a new URL. The job's own files are not touched (they expire on their usual schedule). Only the key that shared the job can take the page down; a job without a share page returns not_found.

Inputs: job_id (required). Returns: result

scene_infoA
Idempotent
Inspect

Read a Blender scene without rendering (a few seconds, no GPU time): cameras and the active one, frame range and fps, resolution, objects by type, lights, materials, whether it is animated, and missing linked files that would render pink. Use it for a .blend you did not write, or to check what a bpy script built. Returns scene_id; pass it to render_preview and render_final instead of sending the scene again.

Inputs: assets, blender, scene_id, scene_url, +2 more. Returns: result

Tool Schema Changelog

Recent tool additions, removals, and schema changes observed during successful MCP inspections.

Loading tool schema changelog…

    TDQS

    A4.2/5.0

    Scored across 13 tools

    Disambiguation4/5

    Most tools have clearly distinct purposes, but the set has several 'check' tools (render_status, render_info, render_estimate, billing) whose boundaries are only clarified by lengthy descriptions. render_preview and render_review also overlap in that both return visual checks, though the descriptions distinguish preview rendering from 4-side model QA.

    Naming Consistency4/5

    Ten of thirteen tools follow a consistent render_ verb/noun pattern, and the remaining three (billing, scene_info, asset_search) are readable domain-specific names. The mix is minor and predictable rather than chaotic.

    Tool Count5/5

    Thirteen tools is well within the sweet spot for a render service with preview, final, estimate, status, download, cancel, share, and supporting utilities. Each tool corresponds to a meaningful step or check in the render lifecycle.

    Completeness5/5

    The surface covers the full lifecycle: scene inspection, asset search, preview, review, estimate, final render, status polling, download, cancellation, sharing/unsharing, billing, and service health. No obvious dead ends or missing core operations for a cloud Blender rendering service.

    Maintenance

    ActivityActive
    ResponsivenessNo recent community issues

    Related MCP Connectors

    Related MCP Servers

    • A
      license
      Not graded
      quality
      C
      maintenance
      Lets an AI engine drive a Blender instance the user runs themselves over stdio JSON-RPC, enabling scene inspection, viewport capture and picking, sandboxed code execution, and gated asset search/import and 3D generation. Telemetry is disabled before import, outbound tools are withheld until per-run network consent, and VRAM gating plus a surface-policy tool report what is live and what a station has cleared.
      Business Source 1.1
    • F
      license
      Not graded
      quality
      A
      maintenance
      Enables AI agents to control a live Blender session, including scene and object operations, rendering, and PolyHaven asset workflows. Supports provider-agnostic LLM backends that can be switched at runtime through MCP tools.
      -
    • F
      license
      Not graded
      quality
      A
      maintenance
      Enables AI agents to drive a live Blender session over MCP — inspecting and creating scene objects, applying materials, rendering, executing code, and fetching PolyHaven assets. It also exposes prompt, provider, and model tools backed by a provider-agnostic LLM layer (Ollama, LM Studio, llama.cpp, OpenAI-compatible, Azure) that can be switched at runtime.
      -
    • F
      license
      Not graded
      quality
      A
      maintenance
      Enables AI agents to drive a live Blender session over MCP by inspecting scenes, creating and modifying objects, assigning materials, rendering images, and fetching PolyHaven assets. It also exposes prompt-based scene building and review workflows backed by a provider-agnostic LLM layer (Ollama, LM Studio, llama.cpp, OpenAI-compatible endpoints, Azure) that can be switched at runtime.
      -