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  3. Topaz MCP
Topaz MCP logo
Health: ActiveRecent health check succeeded.Last checked 9/7/2026, 12:16:11 AM

Topaz MCP

User RatingsBe the first to rate and review this MCP server!
View Repository6 GitHub StarsTotal stargazers on GitHub for the source repository (6 stars).Visit Website
image-enhancementupscalingtopaz-labsmultimedia

Enhances local or remote images through Topaz Labs models, with configurable output sizing and eight model choices.

Quick Install

Automated & IDE Setup

Copy the AI prompt to install this server into Claude Code, Cursor, or another agent โ€” or use 1-click editor setup below.

Add to CursorAdd to VS Code
Not yet automatically verified

This server is confirmed live โ€” we successfully called its tools/list endpoint directly (see the verified badge above). We haven't yet sandbox-tested the stdio install command below specifically, which is a separate, ongoing check.

Manual Client & Custom JSON ConfigExpand JSON โ–พ

Client Config & Setup

Choose your client or environment
Target File:~/Library/Application Support/Claude/claude_desktop_config.json
claude_desktop_config.json
{
  "mcpServers": {
    "topazlabs-topaz-mcp": {
      "command": "npx",
      "args": [
        "-y",
        "@topazlabs/mcp"
      ]
    }
  }
}

๐Ÿ’ก Paste the JSON block into your client's configuration file under mcpServers, then restart the application.

Install Tool Schemas (1) Directory Badge Claim listing Alternatives๐ŸŽฅ More in Multimedia Process

Overview

TopazLabs/topaz-mcp MCP server lets MCP-compatible AI assistants enhance images through the Topaz Labs API. Its `image-enhance` tool accepts a local file path or image URL, with optional output dimensions, scale, and model selection. It defaults to Standard V2 and upscales images below 2K width when no size is supplied. Reach for it when an agent needs cloud-based image upscaling, sharpening, denoising, or quality improvement; it does not support video.

Use cases

โ€ขUpscale photographs to a target size
โ€ขSharpen low-quality or compressed images
โ€ขRestore old or low-resolution photos
โ€ขEnhance digital art and renders

Key features

โ€ขEnhances images from local paths or URLs
โ€ขSupports eight Topaz Labs AI models
โ€ขAccepts exact dimensions, proportional sizing, or scale factors
โ€ขDefaults to Standard V2 with automatic 2K upscaling
โ€ขRuns over MCP stdio transport

Capabilities & Tool Schemas (1) ~279 tokensApproximate context cost of this serverโ€™s tool schemas (~4 chars/token), before any tool is called. Actual usage depends on your client and model.Verified live Verified liveCaptured by calling this serverโ€™s live tools/list endpoint.

Inspect callable tools, capabilities, and parameters exposed to AI agents by Topaz MCP.

image-enhance

Enhance an image using Topaz Labs AI. Upscales, sharpens, and improves quality. Accepts a local file path or URL. If the user shares an image in the conversation without providing a path, ask them for the file path or a URL to the original image.

How Topaz MCP works

What TopazLabs/topaz-mcp MCP server does

TopazLabs/topaz-mcp MCP server exposes Topaz Labs image enhancement through the Model Context Protocol. An assistant can submit a local image path or URL and receive an enhanced image. The available processing is image-only and runs through Topaz Labs' cloud API, so the source image is sent to that service.

The server supports eight models: Standard V2, Low Resolution V2, CGI, High Fidelity V2, Redefine, Recover 3, Standard MAX, and Wonder 2. These cover general photography, small or low-resolution images, digital art, high-quality source images, creative reinterpretation, old photographs, maximum-quality processing, and nature or portrait detail.

How it works

The MCP server uses stdio transport and registers the image-enhance tool. The required image input can be a filesystem path or URL. A request may also include a model and a size object. Size can specify exact width and height, only one dimension for proportional resizing, or a scale multiplier.

If no model is chosen, processing uses Standard V2. If no size is provided, images smaller than 2K are automatically upscaled to 2K width. Images shared directly in a chat are not sufficient by themselves; the assistant needs the original file path or a URL. Clients with filesystem access are therefore better suited to local-image workflows.

Setup and configuration

To run the TopazLabs/topaz-mcp MCP server, install it through npm when configuring an MCP client:

config.json
{
  "mcpServers": {
    "Topaz Labs": {
      "command": "npx",
      "args": ["-y", "@topazlabs/mcp"],
      "env": {
        "TOPAZ_API_KEY": "your-api-key"
      }
    }
  }
}

TOPAZ_API_KEY is required. The key is obtained from the Topaz Labs developer portal. The documented configuration uses stdio, which is supported by Claude Desktop, Cursor, Windsurf, and Cline. Claude Desktop's chat mode requires the user to provide paths manually because it does not provide filesystem access; the README recommends Claude Cowork for local files.

Tools and capabilities

The server exposes one tool:

  • image-enhance: Enhances an image using a Topaz Labs model. It can upscale, sharpen, and improve image quality from a local path or URL.

The tool's model choices include standard and generative options. Standard V2 is the default for general photos, while Low Resolution V2 targets tiny images and thumbnails. CGI is intended for digital art and renders; High Fidelity V2 is for high-quality sources requiring enlargement. Redefine, Recover 3, Standard MAX, and Wonder 2 provide generative processing for creative reinterpretation, older or low-resolution images, maximum quality, and nature photography or portraits respectively.

Limitations and notes

The TopazLabs/topaz-mcp MCP server requires a paid Topaz Labs API key and sends images to the Topaz Labs API for cloud processing. It does not enhance video. HTTP streaming transport is not currently supported, so clients that require a remote HTTP or web/mobile connection cannot use that transport with this server.

Read the full README โ†’View source on GitHub โ†’

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Adoption & maintenance

Factual signals from GitHub, npm, and our automated checks โ€” not a rating.

GitHub stars
6
Stargazers on the source repository.
npm downloads
232
Package downloads in the last 30 days.
Last commit
6mo ago
Most recent push to the default branch.
Tools exposed
1
Callable tools this server registers over MCP.
Directory activity
4 views
Config copies, upvotes, and views on AllMCPs.

Reviews

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Frequently Asked Questions about Topaz MCP

Configure an MCP client to run `npx -y @topazlabs/mcp` and set the required `TOPAZ_API_KEY` environment variable.

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Technical Specs & Signals

Category๐ŸŽฅMultimedia Process
PricingBring your own API key (usage-based cost)
More technical detailsExpand โ–พ
TransportSTDIO
RuntimeNode.js
AuthAPI key
LicenseMIT
ClientsClaude Desktop, Cursor, Windsurf, Cline / VS Code
Last updatedSep 4, 2026
8/9 checks healthy over the last 31d
Views4
Unique ViewsTotal visits recorded for this listing page on AllMCPs.
Installs0
Installs & Copy ActionsTotal times users copied install commands or configuration snippets for this server.
GitHub stars6
GitHub Star CountTotal stargazers on GitHub representing community popularity (6 stars).
Last commit6mo ago
Last Repository CommitThe most recent commit or push recorded for this server's GitHub repository.Last commit on Feb 16, 2026
npm downloads232/mo
Monthly npm DownloadsAverage monthly package installs recorded from npm registry statistics.
60Quality signal: Good ยท 60/100How this signal is calculated โ–พ
Server availabilityNot measured

Not scored for repo-hosted servers โ€” we can't reach the running server, only its GitHub page. Hosted MCP endpoints are health-checked live.

Verified ownership10/20
Documentation & tools30/30
Adoption & activity4/15
Community engagement1/10

A guidance signal from public completeness & health data โ€” not a user rating. New listings start lower and rise as they add docs, get verified, and grow adoption. Signals we can't observe for a listing are skipped, not counted against it.

Supply-chain signal

No high-severity advisories surfaced by our automated scan.

Critical 0High 0Medium 0Low 0

Scanned 16d ago via OSV.dev ยท @topazlabs/mcp (npm)

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