TopazLabs/topaz-mcp
by Various
Topaz Labs MCP Server — AI image enhancement via Model Context Protocol
MCP
TopazLabs/topaz-mcp
Added 1 June 2026
Overview
A Model Context Protocol server that exposes Topaz Labs image enhancement models. It enables developers to integrate upscaling, denoising, and other image quality improvements into applications via standard MCP interfaces. The server communicates with locally installed Topaz Labs software to perform enhancements.
Best for
Best for
Developers needing to programmatically access Topaz Labs image enhancement within custom applications or automated workflows
Use cases
- Integrate Topaz Labs upscaling into photo editing tools
- Automate batch image denoising and enhancement pipelines
- Build custom image processing workflows with MCP-compatible clients
Notes
A Model Context Protocol server that exposes Topaz Labs image enhancement models. It enables developers to integrate upscaling, denoising, and other image quality improvements into applications via standard MCP interfaces. The server communicates with locally installed Topaz Labs software to perform enhancements.
3 stars on GitHub. Last updated 2026-02-16. Licensed MIT.
Use cases
- Integrate Topaz Labs upscaling into photo editing tools
- Automate batch image denoising and enhancement pipelines
- Build custom image processing workflows with MCP-compatible clients
Pros
- Leverages Topaz Labs models for high-quality image enhancement results
- Standard MCP interface simplifies integration with various clients and frameworks
- Supports a range of operations including upscaling, denoising, and sharpening
Cons
- Requires Topaz Labs software to be installed and licensed on a local machine
- Low community adoption as indicated by only 3 GitHub stars
- Processing speed depends on local GPU capabilities and Topaz Labs software performance
Indexed from awesome-mcp-servers-punkpeye and enriched against its public facts.
Pros
- Leverages Topaz Labs models for high-quality image enhancement results
- Standard MCP interface simplifies integration with various clients and frameworks
- Supports a range of operations including upscaling, denoising, and sharpening
Cons
- Requires Topaz Labs software to be installed and licensed on a local machine
- Low community adoption as indicated by only 3 GitHub stars
- Processing speed depends on local GPU capabilities and Topaz Labs software performance