Photoshop MCP Server

Photoshop MCP Server

Enables AI clients to control Adobe Photoshop on macOS through AppleScript using the Model Context Protocol.

Category
Visit Server

README

Photoshop MCP Server (AppleScript)

A Model Context Protocol (MCP) server that enables AI clients to control Adobe Photoshop on macOS through AppleScript. This project adapts the architecture from adb-mcp using native macOS automation instead of a Node.js proxy and UXP plugin.

Features

  • Document Operations: List open documents, retrieve document metadata (dimensions, resolution, aspect ratio)
  • Layer Management: List layers with hierarchy, rename layers, toggle visibility, adjust opacity and blend modes
  • Layer Organization: Create new pixel layers, duplicate layers, delete layers, reorder layers (top/bottom/up/down)
  • Document Control: Save documents, flatten all layers
  • MCP Compatible: Works with any MCP-compatible AI client (Claude Desktop, OpenAI Agent SDK, etc.)

Requirements

  • macOS with AppleScript support
  • Adobe Photoshop 2026 or later
  • Python 3.10 or later
  • MCP-compatible client

Installation

1. Clone the repository

git clone https://github.com/<username>/photoshop-mcp.git
cd photoshop-mcp

2. Create virtual environment

python3 -m venv venv
source venv/bin/activate

3. Install dependencies

pip install mcp fastmcp

Configuration

Set the PHOTOSHOP_APPLICATION_NAME environment variable if your Photoshop installation has a different name:

export PHOTOSHOP_APPLICATION_NAME="Adobe Photoshop 2026"

Default value is Adobe Photoshop 2026.

Usage

Start the MCP server

python3 photoshop_mcp.py

The server communicates via stdio and exposes tools to MCP clients.

Available Tools

Tool Description
get_documents Returns a list of open Photoshop documents with name, path, and modified status
get_document_info Returns current document metadata: width, height, resolution, pixel aspect ratio
get_layers Returns all layers with id, name, type, visibility, opacity, blend mode, and nested children
set_layer_visibility Sets visibility of a layer by id
set_layer_properties Updates opacity, blend mode, and visibility for a layer
rename_layer Renames a layer by id
create_pixel_layer Creates a new art/pixel layer
duplicate_layer Duplicates a layer by id
delete_layer Deletes a layer by id
move_layer Moves a layer by id. Positions: TOP, BOTTOM, UP, DOWN
get_layer_bounds Returns pixel bounds of a layer
flatten_all_layers Flattens all layers into a single layer
save_document Saves the current document

Example Prompts

Once connected to an MCP client:

List all layers in the current Photoshop document.
Rename layer 3 to "Background - Final".
Set layer 5 to 50% opacity and multiply blend mode.
Create a new layer named "Adjustment Layer" with 80% opacity.

Architecture

AI Client <-> MCP Server (Python/FastMCP) <-> AppleScript <-> Adobe Photoshop

This implementation replaces the Node.js proxy server and UXP plugin architecture from the original adb-mcp with direct AppleScript execution, reducing complexity and external dependencies.

Project Structure

photoshop-mcp/
  photoshop_applescript.py  # AppleScript wrappers for Photoshop operations
  photoshop_mcp.py          # FastMCP server exposing tools
  pyproject.toml            # Project metadata and dependencies
  README.md                 # Documentation
  ROADMAP.md                # Development roadmap

Development

Running tests

python3 -c "
import sys
sys.path.insert(0, '.')
from photoshop_applescript import get_documents, get_layers
print(get_documents())
print(get_layers())
"

Adding new tools

  1. Add an AppleScript wrapper function in photoshop_applescript.py
  2. Expose it as an MCP tool in photoshop_mcp.py using the @mcp.tool() decorator

Roadmap

  • [x] Core layer editing (rename, visibility, opacity, blend mode)
  • [x] Layer creation, duplication, deletion, reordering
  • [x] Document info and document listing
  • [x] Layer bounds retrieval
  • [x] Save and flatten operations
  • [ ] Image export (PNG, JPG)
  • [ ] Layer image extraction
  • [ ] Place image into layer
  • [ ] Selection tools
  • [ ] Fill and delete selection
  • [ ] Adjustment layers
  • [ ] Text layers
  • [ ] Layer masks

License

MIT

Acknowledgments

Inspired by adb-mcp by Mike Chambers.

Recommended Servers

playwright-mcp

playwright-mcp

A Model Context Protocol server that enables LLMs to interact with web pages through structured accessibility snapshots without requiring vision models or screenshots.

Official
Featured
TypeScript
Magic Component Platform (MCP)

Magic Component Platform (MCP)

An AI-powered tool that generates modern UI components from natural language descriptions, integrating with popular IDEs to streamline UI development workflow.

Official
Featured
Local
TypeScript
Audiense Insights MCP Server

Audiense Insights MCP Server

Enables interaction with Audiense Insights accounts via the Model Context Protocol, facilitating the extraction and analysis of marketing insights and audience data including demographics, behavior, and influencer engagement.

Official
Featured
Local
TypeScript
VeyraX MCP

VeyraX MCP

Single MCP tool to connect all your favorite tools: Gmail, Calendar and 40 more.

Official
Featured
Local
graphlit-mcp-server

graphlit-mcp-server

The Model Context Protocol (MCP) Server enables integration between MCP clients and the Graphlit service. Ingest anything from Slack to Gmail to podcast feeds, in addition to web crawling, into a Graphlit project - and then retrieve relevant contents from the MCP client.

Official
Featured
TypeScript
Kagi MCP Server

Kagi MCP Server

An MCP server that integrates Kagi search capabilities with Claude AI, enabling Claude to perform real-time web searches when answering questions that require up-to-date information.

Official
Featured
Python
Neon Database

Neon Database

MCP server for interacting with Neon Management API and databases

Official
Featured
E2B

E2B

Using MCP to run code via e2b.

Official
Featured
Exa Search

Exa Search

A Model Context Protocol (MCP) server lets AI assistants like Claude use the Exa AI Search API for web searches. This setup allows AI models to get real-time web information in a safe and controlled way.

Official
Featured
Qdrant Server

Qdrant Server

This repository is an example of how to create a MCP server for Qdrant, a vector search engine.

Official
Featured