Image Worker

Effortlessly resize, convert, optimize, and transform images with a single MCP server—then upload them directly to S3, Cloudflare R2, or Google Cloud Storage. Ideal for AI workflows, automation scripts, and developers who want seamless image handling in one tool.

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4 months ago

First Indexed

3 weeks ago

Catalog Refreshed

Documentation & install

Readme and setup notes from the catalogue, plus a client-ready config you can copy for your MCP host.

Installation

Add the following to your MCP client configuration file.

Configuration

View docs

{
  "mcpServers": {
    "boomlinkai-image-worker-mcp": {
      "command": "npx",
      "args": [
        "-y",
        "@boomlinkai/image-worker-mcp"
      ],
      "env": {
        "S3_BUCKET": "my-bucket",
        "S3_REGION": "us-east-1",
        "GCLOUD_BUCKET": "my-bucket",
        "AWS_ACCESS_KEY_ID": "AKIA...",
        "GCLOUD_PROJECT_ID": "my-project",
        "CLOUDFLARE_R2_BUCKET": "my-bucket",
        "AWS_SECRET_ACCESS_KEY": "secret...",
        "CLOUDFLARE_R2_ENDPOINT": "https://...",
        "CLOUDFLARE_R2_ACCESS_KEY_ID": "key...",
        "CLOUDFLARE_R2_SECRET_ACCESS_KEY": "secret..."
      }
    }
  }
}

You can use the Image Worker MCP Server to resize, convert, optimize, and upload images through a simple MCP interface. It’s designed to plug into AI assistants and automated workflows, handling image processing and cloud uploads with a minimal setup.

How to use

Plug the Image Worker MCP Server into your MCP client and start issuing image processing requests. Use the resize tool to adjust image dimensions and format, then the upload tool to send the result to your cloud storage service. The server speaks through stdio, so you can connect it directly from your AI tool, editor, or workflow runner without additional networking configuration.

How to install

Prerequisites: you need Node.js 18.x or higher installed on your system.

Install the MCP server globally using your package manager of choice, then start it via a quick run command.

Additional setup and usage notes

The MCP server supports several cloud providers for uploads. Configure credentials and bucket details using environment variables for the provider you choose.

Key environment variables you may set include credentials and bucket details for AWS S3, Cloudflare R2, and Google Cloud Storage. Be sure not to commit sensitive values to source control; use secret managers or local environment files.

Examples and workflow patterns

# Start the MCP server (no install required if you run it directly)
npx @boomlinkai/image-worker-mcp

# Resize an image using the MCP tool
# (This uses the image-worker MCP server via your MCP client)
{
  "tool_code": "use_mcp_tool",
  "tool_name": "resize_image",
  "server_name": "image-worker",
  "arguments": {
    "imageUrl": "https://example.com/original.jpg",
    "width": 800,
    "format": "webp",
    "outputPath": "./resized_image.webp"
  }
}

# Upload the processed image to S3
{
  "tool_code": "use_mcp_tool",
  "tool_name": "upload_image",
  "server_name": "image-worker",
  "arguments": {
    "imagePath": "./resized_image.webp",
    "service": "s3",
    "filename": "my-optimized-image",
    "folder": "website-assets"
  }
}

Available tools

resize_image

Resize and transform images using input options such as imagePath/imageUrl/base64Image, width, height, format, quality, and rotation. Returns the path or base64 of the processed image.

upload_image

Upload an image (by path/url/base64) to a cloud service such as S3, Cloudflare R2, or Google Cloud Storage. Accepts options like filename, folder, public access, and requires credentials via environment variables.

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