Tinypng MCP Server
TinyPNG's MCP server provides local and remote image compression functions
rating : 2 points
downloads : 4.9K
What is the TinyPNG MCP Server?
The TinyPNG MCP Server is a tool that can compress images and integrates with front - end applications through the MCP protocol. It can compress local or remote image files and return the results to users.How to use the TinyPNG MCP Server?
Users can compress images by installing and configuring the server. It supports image compression in multiple formats, such as JPEG and PNG.Applicable Scenarios
Suitable for scenarios that require fast image compression, such as website optimization and pre - upload image processing.Main Features
Local Image Compression
Supports compressing images stored locally to improve loading speed and reduce storage space usage.
Remote Image Compression
Can retrieve and compress images from the Internet without downloading them locally.
Support for Multiple Formats
Supports common image formats, such as JPEG and PNG.
Advantages
Compress images quickly to improve performance
Support multiple image formats, flexible and practical
Easy to integrate into existing systems
Limitations
Requires an API key to use
Only supports specific image formats
May require certain technical settings
How to Use
Install Dependencies
Run the command in the terminal to install project dependencies.
Build the Project
Use the command to build the project in preparation for running.
Configure the API Key
Edit the mcp.json file and fill in your TinyPNG API key.
Start the Server
Use the bun or node command to run the server.
Usage Examples
Compress a Local Image
A user wants to compress a locally saved image file for faster upload to a website.
Compress a Remote Image
A user wants to compress an image retrieved from the network without first downloading it locally.
Frequently Asked Questions
What do I need to use this server?
Why wasn't my image compressed?
Which image formats are supported?
Related Resources
TinyPNG Official Documentation
Learn detailed information about the TinyPNG API.
Smithery Installation Guide
Learn how to install the MCP server through Smithery.
GitHub Repository
View the project's source code and contribution instructions.

Notion Api MCP
Certified
A Python-based MCP Server that provides advanced to-do list management and content organization functions through the Notion API, enabling seamless integration between AI models and Notion.
Python
15.0K
4.5 points

Gitlab MCP Server
Certified
The GitLab MCP server is a project based on the Model Context Protocol that provides a comprehensive toolset for interacting with GitLab accounts, including code review, merge request management, CI/CD configuration, and other functions.
TypeScript
17.1K
4.3 points

Duckduckgo MCP Server
Certified
The DuckDuckGo Search MCP Server provides web search and content scraping services for LLMs such as Claude.
Python
46.8K
4.3 points

Markdownify MCP
Markdownify is a multi-functional file conversion service that supports converting multiple formats such as PDFs, images, audio, and web page content into Markdown format.
TypeScript
25.1K
5 points

Unity
Certified
UnityMCP is a Unity editor plugin that implements the Model Context Protocol (MCP), providing seamless integration between Unity and AI assistants, including real - time state monitoring, remote command execution, and log functions.
C#
19.6K
5 points

Figma Context MCP
Framelink Figma MCP Server is a server that provides access to Figma design data for AI programming tools (such as Cursor). By simplifying the Figma API response, it helps AI more accurately achieve one - click conversion from design to code.
TypeScript
46.9K
4.5 points

Gmail MCP Server
A Gmail automatic authentication MCP server designed for Claude Desktop, supporting Gmail management through natural language interaction, including complete functions such as sending emails, label management, and batch operations.
TypeScript
15.2K
4.5 points

Context7
Context7 MCP is a service that provides real-time, version-specific documentation and code examples for AI programming assistants. It is directly integrated into prompts through the Model Context Protocol to solve the problem of LLMs using outdated information.
TypeScript
65.0K
4.7 points
