Compresto MCP Server: Real-Time Usage Statistics for AI Assistants

Overview: What is Compresto MCP Server?

The Compresto MCP (Model Context Protocol) server is a specialized tool that connects artificial intelligence assistants to real-time data about Compresto's user activities and operations. This server utilizes the Model Context Protocol, which standardizes the connectivity between AI systems and external tools or data sources, enhancing the capabilities of AI applications by providing them with actionable insights into how users interact with and benefit from Compresto.

🔧 Core Features & MCP Capabilities

The Compresto MCP server offers a range of features that leverage the Model Context Protocol to deliver valuable statistics about Compresto's usage. These include:

Real-Time Data Access: The server allows AI assistants to access current and dynamic data regarding user activities, ensuring that the information is up-to-date.
Tool Integration: By connecting with different tools and data sources through MCP, this server enhances the functionality of AI assistants by providing them with real-time statistics about Compresto's performance.

⚙️ MCP Architecture & Protocol Implementation

The architecture of the Compresto MCP server is designed to be compatible with a variety of MCP clients. It follows the Model Context Protocol (MCP) standards, ensuring seamless integration and consistent data interaction between the AI assistants and external tools. The protocol flow can be visualized as:

graph TD
    A[AI Application] -->|MCP Client| B[MCP Protocol]
    B --> C[MCP Server]
    C --> D[Data Source/Tool]
    style A fill:#e1f5fe
    style C fill:#f3e5f5
    style D fill:#e8f5e8

Compresto MCP Protocol Flow Diagram

This diagram illustrates the flow of data and interactions between an AI application, the MCP client, the server, and the Compresto data source. The AI application sends data requests through the MCP client, which then utilizes the Model Context Protocol to communicate with the Compresto MCP server. The server processes these requests and provides appropriate responses based on the requested information.

🚀 Getting Started with Installation

To set up the Compresto MCP server, follow these steps:

Clone the repository:

git clone https://github.com/dqhieu/compresto-mcp
cd compresto-mcp

Install dependencies:
```
npm install
```
Build the project:
```
npm run build
```

After installation, the Compresto MCP server is ready to be integrated into AI workflows.

💡 Key Use Cases in AI Workflows

The Compresto MCP server can be utilized in various AI workflows to provide real-time data insights. Here are two illustrative use cases:

Use Case 1: Automated Reporting

In an automated reporting application, the Compresto MCP server can generate reports based on user interactions with Compresto. For example:

Scenario: An AI assistant needs to compile a report summarizing new user registrations and file processing activities.
Implementation: The AI assistant sends requests to the Compresto MCP server for total users and processed files data, which are then compiled into a comprehensive report.

Use Case 2: Usage Analytics for Personalization

This use case involves using real-time data from the Compresto MCP server to personalize user experiences in an application. For example:

Scenario: A personal assistant needs to recommend file compression techniques based on recent user behavior.
Implementation: The AI assistant queries the Compresto MCP server for the total amount of files processed and size reduction, then uses this data to suggest optimal compression strategies.

🔌 Integration with MCP Clients

The Compresto MCP server supports integration with a range of MCP clients. Currently, it is fully compatible with the following:

MCP Clients: Claude Desktop, Continue, Cursor
Status: Full Support for real-time data interaction and tool requests.

For those clients that do not support full integrations, basic data access such as usage statistics can still be provided.

📊 Performance & Compatibility Matrix

The compatibility matrix details the support status of various MCP clients with the Compresto MCP server. This ensures that developers and users understand which clients are fully supported for seamless integration and tool requests.

MCP Client	Resources	Tools	Prompts	Status
Claude Desktop	✅	✅	✅	Full Support
Continue	✅	✅	✅	Full Support
Cursor	❌	✅	❌	Tools Only

🛠️ Advanced Configuration & Security

MCP Configuration Sample

To configure the Compresto MCP server, add the following to your MCP settings file:

{
  "mcpServers": {
    "compresto": {
      "command": "node",
      "args": [
        "/ABSOLUTE/PATH/TO/PARENT/FOLDER/compresto-mcp/build/index.js"
      ]
    }
  }
}

Security Considerations

API Keys: Ensure that API keys are securely managed and not hardcoded within the server or client projects.
Data Encryption: Use encryption for sensitive data transmitted between the AI assistants and Compresto MCP server.

❓ Frequently Asked Questions (FAQ)

Q: Can the Compresto MCP server be used with other APIs?
- A: Yes, but compatibility must be ensured based on MCP standards. Contact support if you need assistance.
Q: How often is data refreshed in real-time statistics?
- A: Data refreshes within a few seconds after any changes in user activity to ensure up-to-date information.
Q: Is the Compresto MCP server compatible with all AI assistants?
- A: While it supports compatibility with specific clients as detailed in the matrix, full compatibility can be achieved through client-side development for other assistants.
Q: What are the requirements for running this server?
- A: Node.js (v16 or higher) and npm/yarn are required to install dependencies and run the server.
Q: Can I modify the source code of Compresto MCP server without affecting its functionality?
- A: Modifying the code is possible within certain limits, but proper testing should be conducted to ensure no functional issues arise.

👨‍💻 Development & Contribution Guidelines

If you wish to contribute or develop with the Compresto MCP server, follow these guidelines:

Code of Conduct: Follow the project's Code of Conduct for a positive and respectful community.
Development Environment: Ensure Node.js (v16 or higher) is installed. Use npm or yarn to manage dependencies.
Running Tests: Run tests using npm test to ensure code quality.

🌐 MCP Ecosystem & Resources

The global MCP ecosystem includes various clients, servers, and tools that adhere to the Model Context Protocol standards. For more information on MCP and its usage, refer to the following resources:

By leveraging the Compresto MCP server, AI developers can significantly enhance their applications with real-time data insights from Compresto's extensive user base.

Compresto MCP