Adobe Photoshop Controller
Enables direct control of Adobe Photoshop through natural language commands for manipulating layers, text, images, and effects wit
The PsMCP-MCP Server for Photoshop enables AI assistants to directly control Adobe Photoshop through a rich set of tools built with win32com. Developed by Chandrahas455, this Python implementation provides capabilities for manipulating layers, text, images, and effects in Photoshop documents through natural language commands. The server exposes over 30 tools for operations like opening/saving PSD files, creating and editing text layers, applying filters, managing layer properties, and exporting in various formats. It integrates with Gemini AI through a Gradio interface for a seamless user experience, making it particularly valuable for designers who want to automate Photoshop tasks or control their workflow through conversational AI without switching contexts.
Source
Repository: https://github.com/chandrahas455/psmcp-mcp-server-for-photoshop
Maintain Adobe Photoshop Controller?
Let people know it's listed here — add the badge (live metrics, light/dark aware) or a plain link to your README or docs.
[Adobe Photoshop Controller on getagentictools](https://getagentictools.com/mcp/chandrahas455-psmcp-mcp-server-for-photoshop?ref=badge) Related mcp
Aider Multi-Coder Provides a bridge between Aider pair programming tool and AI models, enabling parallel execution of multiple coding tasks with con
Caiyun Weather Integrates with Caiyun Weather API to provide real-time weather data and forecasts based on geographic coordinates or location nam
Claude Enhancements Extends Claude's capabilities with modular utility servers for greeting users, counting files, saving conversations, and managing
Figma Integrates with the Figma API to enable interaction with design files and projects, facilitating automated design tasks and AI-ass
CanICode by let-sunny Analyze Figma designs for development and AI readiness with 39 rules, scoring, and HTML reports.
Prolog Reasoner SWI-Prolog execution for LLMs to delegate combinatorial reasoning and constraint satisfaction problems.