MCP Photoshop Server

A local MCP (Model Context Protocol) server that combines Photoshop-style image editing with AI image generation powered by ComfyUI.

Designed for use with Cline — an AI-powered coding assistant. This server integrates as an MCP tool provider to enable image generation and editing directly from your Cline workflow.

Features

Canvas Management

• new_canvas — Create a blank canvas with custom dimensions and background color

• open_image — Load an existing image file

• export — Save to PNG/JPG/WEBP or return base64 data

• get_info — View canvas dimensions, layers, undo/redo state

AI Image Generation & Editing

• generate_image — Text-to-image via Flux2 (photorealistic) or ANIMA (anime)

• img2img — AI instructed editing via Flux Kontext

• character_transform — Pose/expression/action transforms with identity preservation

• inpaint — AI fill masked region (requires mask from select_rect/select_ellipse)

• outpaint — AI extend canvas in a direction (left, right, top, bottom)

AI-Guided Generation

• controlnet_generate — Generate image guided by current canvas (depth/canny/pose)

• style_transfer — Generate image with style of a reference image (Redux StyleModel)

Deterministic Editing (Pillow — no GPU needed)

• crop, resize, rotate, flip — Transform operations

• adjust — Brightness, contrast, saturation, hue, sharpness

• levels — Black point, mid point (gamma), white point adjustment

• curves — Per-channel tone curves (R/G/B) with control points

• apply_filter — 17 filters: blur, gaussian_blur, sharpen, contour, detail, edge_enhance, edge_enhance_more, find_edges, smooth, smooth_more, emboss, pixelate, posterize, solarize, invert, grayscale, sepia

• add_text — Text overlay with font, color, stroke support

Upscaling

• upscale — AI upscaling via ComfyUI (ESRGAN/SUPIR models)

Layer System

• add_layer, select_layer, delete_layer, merge_down, reorder_layer

• set_blend_mode — 12 modes: normal, multiply, screen, overlay, darken, lighten, color_dodge, color_burn, hard_light, soft_light, difference, exclusion

• set_layer_opacity — Per-layer transparency

Selections & Masks

• select_rect — Rectangular mask

• select_ellipse — Elliptical mask

• select_object — Heuristic color/region selection (red, blue, sky, dark, etc.)

• clear_mask — Remove layer mask

History

• undo / redo — Full operation history (up to 20 steps)

System

• get_comfyui_status — Check ComfyUI connection

• clear_vram — Free GPU memory

Related MCP server: fal-mcp

Installation

Prerequisites

• Python 3.10+

• ComfyUI running locally on port 8188

• ⚠️ VRAM Warning: Running ComfyUI without auto-kill causes major OOM on shared GPUs (e.g., 32GB GPU with vLLM). Set COMFYUI_AUTO_KILL=1 to enable idle timeout (60s) which frees VRAM after inactivity while still allowing tool chaining.

• Required models installed in ComfyUI:

  Flux2 Klein (photorealistic generation):

  • flux-2-klein-9b.safetensors (diffusion_models) — IMPORTANT: use 4-6 steps max. Image quality actively diminishes after ~6 steps (artifacts, over-smoothing) and latency increases linearly with each additional step.

  • qwen_3_8b_fp8mixed.safetensors (text_encoders) — Flux2 Klein text encoder

  • flux2-vae.safetensors (vae) — Flux2 Klein VAE

  ANIMA (anime generation):

  • anima-aesthetic-v1.1.safetensors (diffusion_models)

  • qwen_3_06b_base.safetensors (text_encoders)

  • qwen_image_vae.safetensors (vae)

  Flux Kontext (img2img, inpaint, outpaint):

  • flux1-dev-kontext_fp8_scaled.safetensors (diffusion_models)

Install Dependencies

cd mcp-photoshop-server
pip install -r requirements.txt

Configure MCP Client

Add to your MCP client configuration (e.g., Claude Desktop claude_desktop_config.json):

{
  "mcpServers": {
    "photoshop": {
      "command": "python",
      "args": ["<path-to-server>/server.py"],
      "env": {
        "COMFYUI_URL": "http://127.0.0.1:8188",
        "COMFYUI_PYTHON": "<path-to-comfyui>/python_embeded/python.exe",
        "COMFYUI_MAIN": "<path-to-comfyui>/ComfyUI/main.py",
        "COMFYUI_AUTO_KILL": "1",
        "COMFYUI_IDLE_TIMEOUT": "60",
        "VRAM_PRESSURE_THRESHOLD_MB": "8192"
      }
    }
  }
}

Environment Variables

See .env_example for a complete reference. Key variables:

Architecture

mcp-photoshop-server/
├── server.py           # MCP server + 36 tool registrations
├── config.py           # Configuration & model names
├── comfy_client.py     # ComfyUI API client (REST + WebSocket)
├── canvas.py           # Layered document with blend modes + undo/redo
├── session.py          # Per-session document management
├── requirements.txt    # Python dependencies
├── MEMORY.md           # Project memory bank
├── .env_example        # Environment variable template
├── .gitignore          # Git ignore rules
└── README.md

Design Philosophy

• AI operations (generation, inpainting, transforms, ControlNet, style) → routed through ComfyUI

• Deterministic edits (crop, resize, adjustments, filters) → executed locally with Pillow (fast, no GPU)

• Layered document model → mirrors Photoshop's mental model with blend modes, masks, and undo history

Usage Examples

Generate and Edit

1. generate_image(prompt="a cat wearing sunglasses on a beach")
2. adjust(brightness=1.2, saturation=1.3)
3. apply_filter(name="sharpen")
4. export(path="output/cat.png")

Layer Compositing

1. open_image(path="background.jpg")
2. add_layer(name="overlay", source_path="overlay.png")
3. set_blend_mode(mode="multiply")
4. set_layer_opacity(opacity=0.7)
5. export(path="output/composite.png")

AI Edit Workflow

1. open_image(path="portrait.jpg")
2. img2img(prompt="change background to a forest at sunset")
3. undo  # if not satisfied
4. img2img(prompt="make the lighting warmer and softer")
5. adjust(contrast=1.1)
6. export(path="output/edited.jpg", format="JPG")

Inpainting Workflow

1. open_image(path="photo.jpg")
2. select_rect(x=100, y=50, width=200, height=150)
3. inpaint(prompt="a red rose bouquet")
4. export(path="output/inpainted.png")

Upscaling

1. open_image(path="small_photo.jpg")
2. upscale(model="4x_NMKD-Siax_200k.pth")
3. export(path="output/upscaled.png")

ControlNet Guided Generation

1. open_image(path="sketch.png")
2. controlnet_generate(prompt="a detailed cityscape", controlnet="canny", strength=0.8)
3. export(path="output/cityscape.png")

Style Transfer

1. open_image(path="photo.jpg")
2. style_transfer(prompt="the same scene", style_path="painting.jpg", strength=0.8)
3. export(path="output/styled.png")

Future Work

• SAM-based semantic selection (replace heuristic with real segmentation model)

• Batch processing / multi-session support

• Additional ComfyUI custom nodes integration