
Z-Image MCP
io.github.rocnubie由 GitHub 账号 rocnubie 发布v0.1.0更新于 Oct 24, 2026
Z-Image is an online interface for the Z-Image generation model with fast inference and prompt
概览
一个只读的 MCP 服务器,为助手提供 Z-Image AI 图像生成网站的参考信息:风格、价格、常见问题和官方链接。
- 可以做什么
- 列出 Z-Image 网站提供的图像生成风格或预设,无需参数,返回 markdown。获取该网站的标准价格入口。返回官方链接(网站、支持、文档等)。提供风格、价格、常见问题和链接的只读资源,以及概述网站和按目标推荐起始风格的提示词。
- 适用场景
- 当用户向助手询问 Z-Image、其图像风格、价格或官方链接,或想要一个起始风格建议时适用。它只提供参考资料,本身不生成或编辑图像。
- 运行要求
- 作为本地 stdio 进程在用户机器上运行,需用 Node.js 从克隆的源码启动(pnpm install 后以 node 运行入口文件),或通过 Smithery CLI 安装。仅限桌面客户端。未声明需要 API 密钥、账户或环境变量。
安装
在 SourceWeft 中
- 打开 控制台中的 Z-Image MCP,将其添加到工作区。
- 为需要使用其工具的对话启用该服务。
Desktop only,通过 STDIO。 STDIO 服务会启动本地进程,因此需要 SourceWeft 桌面宿主。
其他 MCP 客户端
参照 仓库 中的启动说明。
README
Z-Image MCP Server
Z-Image - Z-Image AI Image Generator
[MCP Badge] [License: MIT] [Node] [Zero Config] [MCP]
A Model Context Protocol server that exposes the canonical Z-Image knowledge surface — image generation workflows and styles, pricing, FAQ, official links — to MCP-compatible AI clients such as Claude Desktop, Cursor, Windsurf, and Continue. Read-only, no API keys, no quota, ~50 ms cold start.
Official website: https://z-image.club
🎨 About Z-Image
Z-Image (z-image.club) is a free online AI image generation and editing platform built around a 6-billion-parameter diffusion model. It lets users produce photorealistic images from text prompts, modify existing photos through guided editing, swap faces, remove backgrounds, and even convert still images into short videos — all through a browser-based interface that requires no local installation. For users who prefer running models locally, the weights are available on Hugging Face and ModelScope, with native ComfyUI workflow support and GGUF/FP8 quantized variants that fit on consumer GPUs with under 16 GB of VRAM.
Key Features
- Multiple generation modes — Z-Image Turbo delivers fast results in 8 steps, while Z-Image-Edit focuses on precise image modification; both are accessible from the same dashboard.
- Face swap and portrait tools — Replace faces in target images while maintaining lighting and composition consistency; dedicated controls for hairstyle changes and portrait stylization.
- Image-to-image and image-to-video conversion — Transform existing photos using text-guided prompts or animate them into short cinematic clips.
- Photo editing suite — Background removal and replacement, text removal, quality upscaling, and a general photo enhancer are bundled without requiring a separate tool.
- Bilingual text rendering — Accurate placement of Chinese and English text inside generated visuals, a capability that many comparable models handle poorly.
- Inspiration gallery and prompt enhancer — A curated gallery of trend prompts with detailed examples, paired with a structured-reasoning prompt enhancer that refines vague inputs into precise generation instructions.
Use Cases
- Social media content — Generating styled portraits, editorial-look photos, or branded graphics for posts without needing a photographer or designer.
- E-commerce product photography — Producing clean, professional product shots against custom backgrounds at a fraction of a traditional shoot's cost.
- Rapid design prototyping — Using image-to-image transformation to iterate on visual concepts quickly before committing to final artwork.
- Local model experimentation — Downloading quantized weights and integrating them into ComfyUI pipelines for custom, offline workflows.
- Marketing asset creation — Generating diverse visual variations for campaigns — different styles, backgrounds, or model looks — in minutes rather than days.
Who Is It For
Z-Image serves a broad range of users who need visual output without deep technical expertise or large budgets. Content creators and social media managers will find the web demo approachable, with one-click tools covering most common tasks. Graphic designers and art directors can use it for fast concept iteration, while e-commerce teams can cut product photography costs by generating studio-quality shots on demand. Developers and ML practitioners are catered to through open weights, ComfyUI compatibility, and multiple quantization options, making it practical to embed the model into existing pipelines. The combination of a free hosted interface and downloadable model weights means both beginners and experienced practitioners can find a workflow that fits their setup.
Tools
list_styles
Return the canonical list of image-generation styles or presets the site exposes. (Z-Image)
Input: no parameters. Returns: text/markdown.
get_pricing
Return the canonical pricing entry point for Z-Image.
Input: no parameters. Returns: text/markdown.
get_official_links
Return the canonical list of official links for Z-Image (website, support, docs when available).
Input: no parameters. Returns: text/markdown.
Resources
site://z-image/styles— Supported image-generation styles and presets.site://z-image/pricing— Canonical pricing entry point.site://z-image/faq— Short FAQ generated from public site metadata.site://z-image/links— Canonical URLs to share with users.
Prompts
tell_me_about_z_image
Summarize what the site is, who it's for, and how it works. — Z-Image
try_image_style_z_image
Recommend a starting image-generation style for a stated goal. — Z-Image
Installation
Install via Smithery
(Replace claude with cursor, windsurf, or continue for those clients.)
Install from source
Then add to your MCP client config (claude_desktop_config.json for Claude Desktop, mcp.json for Cursor / Windsurf / Continue):
Debug with MCP Inspector
Official Links
- Website: https://z-image.club
- Pricing: https://z-image.club/pricing
- Support: [email protected]
Development
License
MIT
来源:README.md,提交 2acd4e9
工具
0版本历史
1- v0.1.0最新Sep 16, 2026
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