alisaitteke/photoshop-mcp

Description and use

**Brief Summary**
alisaitteke/photoshop-mcp is an open‑source Model Context Protocol (MCP) server that lets AI assistants invoke more than 50 Photoshop‑related tools for design, image editing, and workflow automation. Written in TypeScript, it provides a clean API/SDK/CLI surface so developers can bridge generative AI agents with real Photoshop capabilities.

**Value**

• **Standardized AI‑to‑tool bridge:** By exposing Photoshop functions through MCP, the project eliminates the need for custom, ad‑hoc integrations, letting any MCP‑compatible AI (e.g., ChatGPT, Claude, or custom agents) control Photoshop directly.
• **Rich toolset:** Over 50 built‑in commands cover common design tasks (layer manipulation, filters, batch processing, asset export, etc.), accelerating prototyping and reducing manual effort.
• **Extensible backend:** The TypeScript codebase makes it easy to add new Photoshop actions or wrap third‑party plugins, future‑proofing the integration stack.

**Practical Adoption Path**

1. **Prototype:** Clone the repo, run the Docker‑compose or npm start script, and point your AI assistant to the MCP endpoint. Use the provided CLI to test individual commands (e.g., mcp run applyFilter --args ...).
2. **Integrate:** Wrap the MCP client in your existing AI orchestration layer (LangChain, LlamaIndex, etc.) and map high‑level intents to the corresponding Photoshop tools.
3. **Secure & Deploy:** Harden the server with API keys or OAuth, containerize it, and deploy to a Kubernetes or serverless environment.
4. **Scale:** Leverage the built‑in logging and metrics to monitor usage, and add custom actions for organization‑specific workflows (e.g., brand‑compliant asset generation).

**Production Readiness**

• **Activity & Community:** 121 stars, recent commits (last updated 2026‑06‑23), and a modest but active fork base indicate healthy maintenance.
• **Technical Maturity:** Implemented in TypeScript with clear API/SDK/CLI interfaces, comprehensive topic tags, and a well‑documented MCP schema, making it straightforward to evaluate and integrate.
• **Risk Profile:** No major metadata or licensing red flags have been identified, though a final security audit and maintainer confirmation are advisable before mission‑critical use. Overall, the project is positioned as a strong OSS candidate for pilots and can be hardened for production deployments with standard DevSecOps practices.

Use in a workflow

alisaitteke/photoshop-mcp helps connect AI assistants to real tools and data through a standard protocol.

• connect AI agents to tools
• ship Model Context Protocol servers
• standardize integrations

Limitations and review notes

High for an OSS candidate: recent activity, adoption, and ecosystem signals are strong enough for a serious pilot.