Image Tools MCP
Retrieve image dimensions and compress images from URLs or local files using Tinify and Figma APIs.
Image Tools MCP
A Model Context Protocol (MCP) service for retrieving image dimensions and compressing images, supporting both URL and local file sources.
Features
- Retrieve image dimensions from URLs
- Get image dimensions from local files
- Compress images from URLs using TinyPNG API
- Compress local images using TinyPNG API
- Convert images to different formats (webp, jpeg/jpg, png)
- Returns width, height, type, MIME type, and compression information
Example Results


download from figma url and compress

Usage
Using as an MCP Service
This service provides five tool functions:
get_image_size- Get dimensions of remote imagesget_local_image_size- Get dimensions of local imagescompress_image_from_url- Compress remote images using TinyPNG APIcompress_local_image- Compress local images using TinyPNG APIfigma- Fetch image links from Figma API and compress them using TinyPNG API
Client Integration
To use this MCP service, you need to connect to it from an MCP client. Here are examples of how to integrate with different clients:
Usage
{
"mcpServers": {
"image-tools": {
"command": "npx",
"args": ["image-tools-mcp"],
"env": {
"TINIFY_API_KEY": "<YOUR_TINIFY_API_KEY>",
"FIGMA_API_TOKEN": "<YOUR_FIGMA_API_TOKEN>"
}
}
}
}
Using with MCP Client Library
import { McpClient } from "@modelcontextprotocol/client";
// Initialize the client
const client = new McpClient({
transport: "stdio" // or other transport options
});
// Connect to the server
await client.connect();
// Get image dimensions from URL
const urlResult = await client.callTool("get_image_size", {
options: {
imageUrl: "https://example.com/image.jpg"
}
});
console.log(JSON.parse(urlResult.content[0].text));
// Output: { width: 800, height: 600, type: "jpg", mime: "image/jpeg" }
// Get image dimensions from local file
const localResult = await client.callTool("get_local_image_size", {
options: {
imagePath: "D:/path/to/image.png"
}
});
console.log(JSON.parse(localResult.content[0].text));
// Output: { width: 1024, height: 768, type: "png", mime: "image/png", path: "D:/path/to/image.png" }
// Compress image from URL
const compressUrlResult = await client.callTool("compress_image_from_url", {
options: {
imageUrl: "https://example.com/image.jpg",
outputFormat: "webp" // Optional: convert to webp, jpeg/jpg, or png
}
});
console.log(JSON.parse(compressUrlResult.content[0].text));
// Output: { originalSize: 102400, compressedSize: 51200, compressionRatio: "50.00%", tempFilePath: "/tmp/compressed_1615456789.webp", format: "webp" }
// Compress local image
const compressLocalResult = await client.callTool("compress_local_image", {
options: {
imagePath: "D:/path/to/image.png",
outputPath: "D:/path/to/compressed.webp", // Optional
outputFormat: "image/webp" // Optional: convert to image/webp, image/jpeg, or image/png
}
});
console.log(JSON.parse(compressLocalResult.content[0].text));
// Output: { originalSize: 102400, compressedSize: 51200, compressionRatio: "50.00%", outputPath: "D:/path/to/compressed.webp", format: "webp" }
// Fetch image links from Figma API
const figmaResult = await client.callTool("figma", {
options: {
figmaUrl: "https://www.figma.com/file/XXXXXXX"
}
});
console.log(JSON.parse(figmaResult.content[0].text));
// Output: { imageLinks: ["https://example.com/image1.jpg", "https://example.com/image2.jpg"] }
### Tool Schemas
#### get_image_size
```typescript
{
options: {
imageUrl: string // URL of the image to retrieve dimensions for
}
}
get_local_image_size
{
options: {
imagePath: string; // Absolute path to the local image file
}
}
compress_image_from_url
{
options: {
imageUrl: string // URL of the image to compress
outputFormat?: "image/webp" | "image/jpeg" | "image/jpg" | "image/png" // Optional output format
}
}
compress_local_image
{
options: {
imagePath: string // Absolute path to the local image file
outputPath?: string // Optional absolute path for the compressed output image
outputFormat?: "image/webp" | "image/jpeg" | "image/jpg" | "image/png" // Optional output format
}
}
figma
{
options: {
figmaUrl: string; // URL of the Figma file to fetch image links from
}
}
Changelog
- 2025-05-12: Updated Figma API to support additional parameters, including 2x image scaling.
Technical Implementation
This project is built on the following libraries:
- probe-image-size - For image dimension detection
- tinify - For image compression via the TinyPNG API
- figma-api - For fetching image links from Figma API
Environment Variables
TINIFY_API_KEY- Required for image compression functionality. Get your API key from TinyPNG- When not provided, the compression tools (
compress_image_from_urlandcompress_local_image) will not be registered
- When not provided, the compression tools (
FIGMA_API_TOKEN- Required for fetching image links from Figma API. Get your API token from Figma- When not provided, the Figma tool (
figma) will not be registered
- When not provided, the Figma tool (
Note: The basic image dimension tools (get_image_size and get_local_image_size) are always available regardless of API keys.
License
MIT
Server Terkait
Scout Monitoring MCP
sponsorPut performance and error data directly in the hands of your AI assistant.
Alpha Vantage MCP Server
sponsorAccess financial market data: realtime & historical stock, ETF, options, forex, crypto, commodities, fundamentals, technical indicators, & more
Revit MCP
Interact with Autodesk Revit using the MCP protocol. This server provides AI tools and requires the corresponding Revit plugin to function.
MCP Server Template
A template for creating MCP servers using Python.
R.A.P.I.D.
A local MCP server providing powerful code analysis and search capabilities for software projects.
OpenAPI Schema Explorer
Token-efficient access to OpenAPI/Swagger specs via MCP Resources
BoostSecurity
BoostSecurity MCP acts as a safeguard preventing agents from adding vulnerable packages into projects. It analyzes every package an AI agent introduces, flags unsafe dependencies, and recommends secure, maintained alternatives to keep projects protected.
mcp-doctor
Diagnose, secure, and benchmark your MCP servers
Interactive Feedback MCP
Provides interactive user feedback and command execution for AI-assisted development.
Code Runner MCP
Execute JavaScript and Python code in a secure sandbox. Supports Deno for JS/TS and Pyodide for Python, with configurable permissions.
Replicate Minimax Image-01
Generate images using the minimax/image-01 model on Replicate.
llm-context
Share code context with LLMs via Model Context Protocol or clipboard.