mcp-english-school

lazarousgr/mcp-english-school

3.1

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An MCP server designed for educational data preparation, integrating Claude AI with REST services.

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English School MCP Server

An MCP (Model Context Protocol) server designed to consume custom REST services for data preparation in educational contexts. Project is intended for educational purpose only.

Overview

This MCP server acts as a bridge between Claude AI and various REST services, enabling efficient data preparation and processing workflows for English school application. The server provides tools that can be consumed by Claude through the MCP protocol, allowing for seamless integration of external services and data sources.

Features

  • REST Service Integration: Consumes and integrates with custom REST APIs
  • Data Preparation Tools: Specialized tools for educational data processing
  • FastMCP Framework: Built on FastMCP for robust and scalable service delivery

Prerequisites

  • Python 3.8 or higher
  • uv (Python package manager)
  • ngrok (for exposing local server)
  • Claude CLI

Installation

  1. Clone the repository:

    git clone <repository-url>
cd mcp-english-school

  2. Initialize UV and install dependencies:

    uv init
uv add fastmcp python-dotenv starlette

  3. Set up environment variables:

    cp .env.example .env
# Edit .env file with your configuration

Configuration

The server uses environment variables for configuration. Create a .env file in the project root:

LOG_LEVEL=INFO
HOST=127.0.0.1
PORT=8000

Environment Variables

  • LOG_LEVEL: Logging level (DEBUG, INFO, WARNING, ERROR, CRITICAL)
  • HOST: Server host address (default: 127.0.0.1)
  • PORT: Server port (default: 8000)

Running the MCP Server

Local Development

  1. Start the MCP server:

    uv run main.py

  2. Verify the server is running: The server will start on http://127.0.0.1:8000 by default.

Setting up ngrok (Linux)

Installation

  1. Using npm (Recommended if you have Node.js): 
     npm install -g ngrok

Running ngrok

  1. Expose your local MCP server:

    ngrok http 8000

  2. Note the public URL: ngrok will display a public URL (e.g., https://abc123.ngrok.io) that forwards to your local server.

Connecting Claude CLI to MCP Server

Installation of Claude CLI

  1. Install Claude CLI: 
    npm install -g @anthropic-ai/claude-cli

MCP Server Configuration

  1. Create MCP configuration file (~/.config/claude/mcp_servers.json): 
    claude mcp add --transport http mcp_name ngrok_url/mcp

Available Tools

Core Tools

  • health_check: Verify server status
  • echo: Echo back input messages for testing

Development

Project Structure

mcp-english-school/
├── main.py              # Main MCP server application
├── logging_utils.py     # Colored logging utilities
├── .env                 # Environment configuration
├── .env.example         # Example environment file
└── README.md            # This file