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io.github.JasmyLab-JANCTION/janction-render

Blender cloud GPU render farm for AI agents (MCP/API): .blend, bpy, glTF/FBX/USD in; frames/MP4 out

Developer ToolsPythonv0.4.30

JANCTION Render

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. Free up to 500 JPY of GPU time per new key, then 0.1 JPY per GPU-second (previews free up to 2 GPU-minutes a day); 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. The numbers, as of 2026-10-08 (the primary source is https://render.janction.jp/facts.json): a 500 JPY welcome credit (5,000 GPU-seconds, 14 days) per new key; after that, previews are free up to 2 GPU-minutes a day and finals cost 0.1 JPY per GPU-second from prepaid credit (paid use started on 2026-10-08); jobs up to 240 frames at 1080p; inputs and results deleted 24 hours after last use (7 days for keys that have topped up).

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

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 up to 500 JPY of GPU time per new key (14 days), then 0.1 JPY per GPU-second (previews free up to 2 GPU-minutes a day), finals up to 240 frames at 1080p, one GPU shared with another workload (jobs can wait; the ETA says so). Inputs and results are deleted 24 hours after last use (7 days for keys that have topped up) and never used for training.
  • Not Render.com. Same word, different product.

Quick start

Claude.ai / ChatGPT (nothing to install). Settings → Connectors → add https://render.janction.jp/mcp → Connect (a free key is created on the consent page). 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

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())

MCP

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

clienthow
Claude.ai (web, desktop, mobile)Settings → Connectors → Add custom connector → paste the URL → Connect
ChatGPTSettings → Connectors → Advanced → Developer mode → Create → paste the URL (OAuth)
Claude Codeclaude mcp add --transport http janction-render https://render.janction.jp/mcp, then /mcp to authenticate
Codexcodex mcp add janction-render --url https://render.janction.jp/mcp
Gemini CLI / Antigravity CLIgemini extensions install https://github.com/JasmyLab-JANCTION/janction-render (this repository carries gemini-extension.json)
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
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 clientsStreamable 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

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.

# 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

toolwhat
`scene_info(scene_scriptscene_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).

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/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 cheaper animations (about half the per-frame cost after ~7 s of shader compilation per job). 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

Each new key starts with a 500 JPY welcome credit (5,000 GPU-seconds, 14 days) that covers previews and finals; one full credit per network every 30 days. 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 500 JPY; 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 240 frames at 1080p. POST /v1/estimate quotes what will be charged (cost.estimated_yen), the currency and an expiry before any GPU time is used: https://render.janction.jp/pricing

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 5.0, Cycles on GPU (blender="5.2" selects Blender 5.2 when the worker has it; 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

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.

Installation

Source-derived launch command. Check the maintainer’s required arguments and credentials before running:

bash
uvx janction-render

Set up in your AI client

Merge this template into ~/Library/Application Support/Claude/claude_desktop_config.json. Keep existing servers. Add any arguments, credentials, and permissions required by the maintainer; this template has not been install-tested.

json
{
  "mcpServers": {
    "io-github-jasmylab-janction-janction-render": {
      "command": "uvx",
      "args": [
        "janction-render"
      ]
    }
  }
}

Restart Claude Desktop completely for changes to take effect. Confirm the server appears connected in the client’s tool list, then try a read-only example from its documentation.

Claude Desktop setup reference

Package

janction-renderpypi

Compatible MCP Clients

io.github.JasmyLab-JANCTION/janction-render works with any MCP-compatible client. Copy the config snippet from the Configuration section above and add it to the file shown for your client, then restart the application.

  • Claude Desktop~/Library/Application Support/Claude/claude_desktop_config.jsonRestart Claude Desktop completely for changes to take effect.
  • Cursor~/.cursor/mcp.jsonRestart Cursor for changes to take effect.
  • VS Code.vscode/mcp.jsonReload VS Code window for changes to take effect.
  • Windsurf~/.codeium/windsurf/mcp_config.jsonRestart Windsurf for changes to take effect.
  • Claude Code.mcp.jsonSave at the project root, then start Claude Code in that project and review the MCP server approval prompt. Keep real credentials out of shared files.

Learn More