Skip to main content
Glama

Compresto MCP

by dqhieu
README.md1.97 kB
# Compresto MCP A Model Context Protocol (MCP) server for Compresto, providing AI assistants with real-time data about Compresto's usage statistics. <a href="https://glama.ai/mcp/servers/@dqhieu/compresto-mcp"> <img width="380" height="200" src="https://glama.ai/mcp/servers/@dqhieu/compresto-mcp/badge" alt="Compresto MCP server" /> </a> ## What is Compresto? Compresto is a file compression app that helps users reduce file sizes. This MCP server allows AI assistants to access current statistics about Compresto's usage. ## What is MCP? The Model Context Protocol (MCP) is a standard that connects AI systems with external tools and data sources. This MCP server extends AI capabilities by providing access to Compresto's usage statistics. ## Installation ```bash git clone https://github.com/dqhieu/compresto-mcp cd compresto-mcp npm install npm run build ``` ## Manual Configuration Add the following to your MCP settings file ```json { "mcpServers": { "compresto": { "command": "node", "args": [ "/ABSOLUTE/PATH/TO/PARENT/FOLDER/compresto-mcp/build/index.js" ] } } } ``` When integrated with compatible AI assistants, this MCP server provides real-time data about Compresto's usage. ## Available Tools The Compresto MCP server provides the following tools: ### get-total-users Returns the total number of Compresto users. Example response: `12345` ### get-total-processed-files Returns the total number of files processed by Compresto. Example response: `Processed 67890 files` ### get-total-size-reduced Returns the total amount of file size reduced by Compresto. Example response: `Reduced 1234567890 bytes` ## Development ### Prerequisites - Node.js (v16 or higher) - npm or yarn ### Project Structure - `src/index.ts` - Main entry point containing MCP server implementation - `package.json` - Project dependencies and scripts - `tsconfig.json` - TypeScript configuration ## License MIT License

MCP directory API

We provide all the information about MCP servers via our MCP API.

curl -X GET 'https://glama.ai/api/mcp/v1/servers/dqhieu/compresto-mcp'

If you have feedback or need assistance with the MCP directory API, please join our Discord server