Compresto MCP
# 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 LicenseTDQS
Scored across 3 tools
Each tool has a clearly distinct purpose: one retrieves processed file count, another gets size reduction data, and the third provides user count. There is no overlap in functionality, making it easy for an agent to select the correct tool without confusion.
All tool names follow a consistent verb_noun pattern with hyphens (e.g., get-total-processed-files, get-total-size-reduced, get-total-users). This uniformity enhances readability and predictability across the tool set.
With only 3 tools, the set feels thin for a server named 'Compresto MCP', which might imply broader functionality. However, the tools are well-scoped for reporting metrics, so it's borderline but not severely lacking.
The tools only provide read-only metrics (get operations) with no ability to perform actions like processing files, managing users, or configuring settings. This creates significant gaps for a server that might be expected to handle file processing or user management tasks.