
AIYOGG_TINYPNG-MCP-SERVER
镜像://github.com/aiyogg/tinypng-mcp-server
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MCP server for TinyPNG
Usage
Use bun
or node
to run the server
- Install dependencies and build
pnpm i
pnpm build
- Edit the
mcp.json
file
{
"mcpServers": {
"tinypng": {
"command": "bun", // or "node"
"args": ["/path/to/tinypng-mcp-server/src/index.ts"], // or "dist/index.js"
"env": {
"TINYPNG_API_KEY": "your-tinypng-api-key"
}
}
}
}
Installing via Smithery
To install TinyPNG MCP Server for Claude Desktop automatically via Smithery:
npx -y @smithery/cli install @aiyogg/tinypng-mcp-server --client claude
Tools
- Compress local image
{
name: 'compress_local_image',
description: 'Compress a local image file',
inputSchema: {
type: 'object',
properties: {
imagePath: {
type: 'string',
description: 'The ABSOLUTE path to the image file to compress',
example: '/Users/user/Downloads/image.jpg',
},
outputPath: {
type: 'string',
description: 'The ABSOLUTE path to save the compressed image file',
example: '/Users/user/Downloads/image_compressed.jpg',
},
outputFormat: {
type: 'string',
description: 'The format to save the compressed image file',
enum: SUPPORTED_IMAGE_TYPES,
example: 'image/jpeg',
},
},
required: ['imagePath'],
},
}
- Compress remote image
{
name: 'compress_remote_image',
description: 'Compress a remote image file by giving the URL of the image',
inputSchema: {
type: 'object',
properties: {
imageUrl: {
type: 'string',
description: 'The URL of the image file to compress',
example: 'https://example.com/image.jpg',
},
outputPath: {
type: 'string',
description: 'The ABSOLUTE path to save the compressed image file',
example: '/Users/user/Downloads/image_compressed.jpg',
},
outputFormat: {
type: 'string',
description: 'The format to save the compressed image file',
enum: SUPPORTED_IMAGE_TYPES,
example: 'image/jpeg',
},
},
required: ['imageUrl'],
},
}
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Reviews

user_lp9cpcMS
I've been using the aiyogg_tinypng-mcp-server by MCP-Mirror, and it's an excellent tool for image compression. It's efficient and easy to integrate into various projects. Highly recommended for anyone looking to optimize image sizes without sacrificing quality. Check it out on GitHub!