zimage-mcp
Click on "Deploy Server".
Wait a few minutes for the server to deploy. Once ready, it will show a "Started" state.
In the chat, type
@followed by the MCP server name and your instructions, e.g., "@zimage-mcp generate a hero banner for the homepage, save to ./public/hero.png"
That's it! The server will respond to your query, and you can continue using it as needed.
Here is a step-by-step guide with screenshots.
zimage-mcp
A local MCP server for generating web-dev images with the
Z-Image Turbo model running on the ComfyUI box. It hard-codes the verified Z-Image graph
(UNETLoader + CLIPLoader lumina2 + ModelSamplingAuraFlow shift 3 + KSampler 8/cfg1/res_multistep/simple),
downloads the result, and saves it to a local path at exact pixel dimensions.
It runs alongside the existing @peleke.s/comfyui-mcp (which stays for SDXL/FLUX); tools are
namespaced mcp__zimage__*.
Tools
generate_image(prompt, output_path, size="square", width?, height?, seed?, steps?=8, negative?="", n?=1)
Generates and saves image(s).
output_path— local path, e.g../public/img/hero.png. Parent dirs are created. Format follows the extension (.png/.jpg/.jpeg/.webp).size— a preset (below), or pass exactwidth+height. Because Z-Image needs dimensions that are multiples of 16, any exact size is generated at the nearest valid size (≥ requested, matching aspect) then resize-cover + center-crop to your exact pixels.seed— omitted = random; echoed back in the result for reproducibility.n— 1–4 variants. Files get_1,_2, … suffixes; seeds arebase, base+1, ….Returns
{ images, seed, gen_size, output_size, seconds }.
list_presets()
Returns the preset table (name → WxH).
health()
ComfyUI pre-flight: reachable, comfyui_version, gpu, vram_free_mb.
Related MCP server: image-studio-mcp
Size presets
preset | output | use |
| 1024×1024 | cards, avatars, icons |
| 1216×832 | general content images |
| 832×1216 | tall cards |
| 1280×720 | 16:9 hero/banner |
| 1536×640 | wide banner (12:5) |
| 1200×630 | OpenGraph/social share |
| 768×1344 | mobile-first portrait |
Z-Image is tuned around ~1 MP. Very large custom dimensions (>~1.3 MP) may reduce quality or slow down; for big hero art, generate at a preset and upscale separately (a 2K upscaler template exists on the box). Note: text-in-image is weak — use FLUX/Qwen for legible baked-in text.
Configuration (env vars)
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Run / register
Requires uv. Add to ~/.claude.json under mcpServers:
"zimage": {
"type": "stdio",
"command": "uv",
"args": ["run", "--directory", "/Users/jaimie/projects/zimage-mcp", "server.py"],
"env": { "COMFYUI_URL": "http://10.0.0.109:8188" }
}Restart Claude Code; the tools appear as mcp__zimage__generate_image, etc.
Develop / test
uv sync
uv run pytest -q # unit tests (no network)
ZIMAGE_TEST_LIVE=1 uv run pytest -q # + live tests against the boxAvailable Tools
3 toolsgenerate_imageA
Generate web-dev image(s) with Z-Image Turbo and save to output_path.
size: one of square|landscape|portrait|hero|wide|og|mobile, or pass width+height for exact pixels (image is generated at the nearest valid size then resized/cropped). n: 1-4 variants (paths get _1,_2,... ); seeds are base_seed, base_seed+1, ... Returns {images, seed, gen_size, output_size, seconds}.
Inputs: prompt (required), output_path (required), n, seed, +5 more.
healthA
Quick ComfyUI pre-flight: version, GPU, free VRAM.
Inputs: no named parameters.
list_presetsA
Return available size presets as name -> 'WxH'.
Inputs: no named parameters.
Tool Schema Changelog
Recent tool additions, removals, and schema changes observed during successful MCP inspections.
Loading tool schema changelog…
TDQS
Scored across 3 tools
Each tool has a distinct purpose: generate_image for creation, health for system status, list_presets for configuration. No overlap or ambiguity.
Most tools follow verb_noun pattern (generate_image, list_presets), but 'health' is a noun alone. Minor deviation but still clear and readable.
Three tools is well-scoped for an image generation server: core generation, health check, and preset listing. No unnecessary bloat.
The tool set covers the essential workflow: generate images, check system readiness, and retrieve presets. No obvious missing functionality for the stated purpose.
Maintenance
Related MCP Connectors
MCP server for Qwen Image 3 AI image generation
MCP server for Luma Dream Machine AI video generation
MCP server for Flux AI image generation
MCP server for Grok Imagine AI video generation
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