PicoBerry

السجل الرسمي الإنتاجية

An AI 3D workspace for games, VR, and beyond. Generate, remesh, texture, and animate 3D assets.

التثبيت

أضف هذا إلى إعدادات MCP في عميلك (Claude Desktop: claude_desktop_config.json، وCursor: ‏.cursor/mcp.json، ويستخدم VS Code وغيره الصيغة نفسها «mcpServers»).

NPM package @picoberry/mcp-server
Claude Code
claude mcp add picoberry -e 'PICOBERRY_API_KEY=<your picoberry_api_key>' -e 'PICOBERRY_API_BASE=<PICOBERRY_API_BASE>' -- npx -y @picoberry/mcp-server@0.1.7
إعداد JSON (Claude Desktop وCursor وVS Code)
{
    "mcpServers": {
        "picoberry": {
            "command": "npx",
            "args": [
                "-y",
                "@picoberry/mcp-server@0.1.7"
            ],
            "env": {
                "PICOBERRY_API_KEY": "<your picoberry_api_key>",
                "PICOBERRY_API_BASE": "<PICOBERRY_API_BASE>"
            }
        }
    }
}

متغيرات البيئة

  • PICOBERRY_API_KEY إلزامي سري PicoBerry API key (pb_live_...). Create one at https://picoberry.ai/dashboard/api-keys. Requires a completed purchase (a subscription or a one-off credit pack) or an active paid subscription.
  • PICOBERRY_API_BASE Override the API base URL. Defaults to https://api.picoberry.ai — leave unset unless you were given a different host.

التوثيق

مأخوذ من ملف README للمشروع على GitHub ويُحدَّث أسبوعيًا. تفتح الروابط على GitHub.

المحتويات
  1. PicoBerry MCP Server
  2. Install
  3. Tools
  4. How generation works
  5. Example (in an agent)
  6. Use it alongside Blender MCP
  7. Develop
  8. Release
  9. License

PicoBerry MCP Server

Generate 3D models, images, and animations for game and 3D workflows from any MCP client — Claude Code, Cursor, Claude Desktop, Cline — with no HTTP glue. A thin wrapper over the PicoBerry /v1 API, so you get PicoBerry's multi-engine pipeline directly inside your agent. Several 3D and image engines sit behind one API; call list_models for the live set and each engine's cost. Generated assets are drafts — useful for prototyping and iteration, and can be reviewed or refined for your project.

📖 Full reference: API + MCP docs · PicoBerry API

There's no separate subscription for the MCP or the API. Generation spends the same prepaid PicoBerry credits as the web app, per engine, at rates you can read with list_models before you spend anything. (Using the API does require a completed purchase — see Get an API key.)

Install

No install needed — run it with npx:

// Claude Code:  .mcp.json   ·   Claude Desktop:  claude_desktop_config.json
{
  "mcpServers": {
    "picoberry": {
      "command": "npx",
      "args": ["-y", "@picoberry/mcp-server"],
      "env": {
        "PICOBERRY_API_KEY": "pb_live_xxxxxxxxxxxxxxxx"
      }
    }
  }
}

Cursor uses the same shape in ~/.cursor/mcp.json.

Get an API key

Sign in at https://picoberry.ai, open the API Keys tab in your dashboard, and hit Create key. The key is shown once — copy it immediately and treat it like a password.

API access needs a completed purchase: a subscription or a one-off credit pack. A purchase entitles you permanently — you don't need a current subscription. (An active paid subscription works too, of course.)

Environment variables
VarRequiredDefaultNotes
PICOBERRY_API_KEY✅—pb_live_...
PICOBERRY_API_BASE—https://api.picoberry.aileave unset unless you were given a different host

Tools

ToolWhat it does
list_modelsEngines + credit cost for a category (3d / image / parts-board / remesh / texture / animate). Call before generating — don't hardcode engines.
list_animation_presetsAnimation preset ids (engine-specific), with optional substring filter.
get_creditsCurrent credit balance.
generate_imageText → image (+ optional reference image URLs). count (1–4) makes several images in one call → assets[], wait on each id.
generate_3d_from_textText → 3D model (GLB).
generate_3d_from_imageImage → 3D model. Single: image_url or local image_path. Multi-view (2–4 views, higher fidelity): image_urls or image_paths, ordered [front, left, back, right] — tripo\*/meshy6/hunyuan-3.x only.
parts_boardDecompose one image into an exploded parts-board image (server-fixed engine). Input asset_id, image_url, or local image_path; feed the result to generate_3d_from_image for a parts-separated mesh.
remeshRetopologize an existing 3D asset → new asset.
textureRe-texture (PBR) an existing 3D asset → new asset.
animateAuto-rig + animate an existing 3D character → new asset.
get_assetStatus + result URLs for one asset.
wait_for_assetPoll until an asset finishes (or times out), then return it.
list_my_assetsBrowse your generated assets.
download_assetExport a completed 3D asset (glb / fbx / obj) → signed URL.

How generation works

Generation is asynchronous:

  1. generate_3d_from_text({ prompt }) → returns an asset { id }.
  2. wait_for_asset({ asset_id: id }) → polls until taskStatus === 2 (succeeded).
  3. Read the result URL from files.model (GLB) or files.image (PNG).

taskStatus: 0 pending · 1 processing · 2 succeeded · 3 failed. Result URLs are signed and short-lived — download promptly. Errors come back with an actionable message (e.g. an unknown engine returns the list of valid names).

Example (in an agent)

"Make a low-poly treasure chest, retopo it to 3k tris, and give me a Unity FBX."

list_models(category="3d")                         → pick an engine
generate_3d_from_text(prompt="low-poly treasure chest")  → { id: A }
wait_for_asset(asset_id=A)                          → taskStatus 2
remesh(asset_id=A, polycount=3000)                  → { id: B }
wait_for_asset(asset_id=B)
download_asset(asset_id=B, format="fbx", texture_preset="unity")  → signed URL

Use it alongside Blender MCP

Run this next to blender-mcp and the agent can generate with PicoBerry, then import into Blender in one flow:

{
  "mcpServers": {
    "picoberry": { "command": "npx", "args": ["-y", "@picoberry/mcp-server"], "env": { "PICOBERRY_API_KEY": "pb_live_..." } },
    "blender":   { "command": "uvx", "args": ["blender-mcp"] }
  }
}

Develop

npm install
npm run build      # tsc → dist/
PICOBERRY_API_KEY=pb_live_... npm start

Release

Run Actions → Publish → Run workflow (or push a v* tag). It publishes to npm and then to the official MCP registry, in that order — the registry validates by fetching the package's npm metadata and matching its mcpName against server.json's name, so npm has to land first. A guard step checks every invariant (name/version agreement, namespace casing, version not already on npm) before anything is published, because npm versions are immutable and a failed half-publish burns the number.

Bump version in both package.json and server.json (version and packages[0].version) — the guard fails the run if they disagree.

One-time setup — no secrets. Both publishes authenticate over the workflow's GitHub OIDC token (id-token: write). There is nothing to store or rotate.

The only step is telling npm to trust this workflow. On npmjs.com go to @picoberry/mcp-server → Settings → Trusted publishing → GitHub Actions and enter:

FieldValue
Organization or userUModeler
Repositorypicoberry-mcp
Workflow filenamepublish.yml
Environment name(leave empty)
Allowed actionsnpm publish

The workflow filename must match exactly — it is part of what npm verifies.

The MCP registry needs no setup at all: mcp-publisher exchanges the Actions OIDC token, and the registry grants io.github.<repository_owner>/* from the token's repository_owner claim. That covers io.github.UModeler/picoberry-mcp and avoids the interactive browser login (which additionally requires org Owner).

Trusted Publishing needs npm >= 11.5.1, so the workflow runs on Node 24 (npm 11.x). Node 22 still bundles npm 10.9 and would fail — the node-version pin is load-bearing. A guard step fails the run early if the runner ever ships an older npm.

The namespace is compared byte-exactly — io.github.UModeler/..., matching the GitHub org's login. A lowercased io.github.umodeler/... is rejected 403.

After publishing, claim the Glama listing — unclaimed servers get limited discoverability, and awesome-mcp-servers gates its PRs on a Glama badge in CI.

License

MIT

الأسئلة الشائعة

ما هو PicoBerry؟

An AI 3D workspace for games, VR, and beyond. Generate, remesh, texture, and animate 3D assets.

كيف أثبّت PicoBerry؟

يعمل على جهازك. في Claude Code: claude mcp add picoberry -e 'PICOBERRY_API_KEY=<your picoberry_api_key>' -e 'PICOBERRY_API_BASE=<PICOBERRY_API_BASE>' -- npx -y @picoberry/mcp-server@0.1.7. وفي العملاء الآخرين، الصق إعداد JSON من هذه الصفحة في إعدادات MCP الخاصة بهم.

هل يحتاج PicoBerry إلى مفتاح API؟

نعم. يتطلب PICOBERRY_API_KEY، وتضبطها في إعداداته.

هل PicoBerry مفتوح المصدر؟

نعم. شيفرته متاحة على GitHub بترخيص MIT.

من يصون PicoBerry؟

ينشره UModeler. يدرجه AI.tn لكنه لا يصونه ولا يوصي به.

من سجل MCP الرسمي. الإدراج ليس توصية: راجع شيفرة الخادم وصلاحياته قبل منحه الوصول إلى بياناتك.