Access academic grades from the Sakarya University SABIS system via automated web scraping.
A Model Context Protocol (MCP) Server for accessing academic grades from the Sakarya University SABIS (Student Information System). This server enables AI assistants and applications to securely retrieve student academic information through automated web scraping.
Clone the repository:
git clone https://github.com/your-username/sabis-mcp-server.git
cd sabis-mcp-server
Install dependencies:
npm install
Set up environment variables:
Create a .env
file in the root directory:
USERNAME=your_sabis_username
PASSWORD=your_sabis_password
Build the project:
npm run build
Variable | Description | Required |
---|---|---|
USERNAME | Your SABIS student ID/username | β Yes |
PASSWORD | Your SABIS account password | β Yes |
You have two options for configuring credentials with your MCP client:
Add the server to your MCP client configuration with credentials directly in the config:
{
"mcpServers": {
"sabis-mcp-server": {
"command": "node",
"args": [
"/path/to/sabis-mcp-server/build/index.js"
],
"env": {
"USERNAME": "your_student_number",
"PASSWORD": "your_password"
}
}
}
}
Alternatively, create a .env
file in the project directory and remove the env
property from the MCP configuration:
Create .env
file:
USERNAME=your_student_number
PASSWORD=your_password
MCP Configuration:
{
"mcpServers": {
"sabis-mcp-server": {
"command": "node",
"args": [
"/path/to/sabis-mcp-server/build/index.js"
]
}
}
}
π‘ Tip: Option 1 is more convenient for MCP clients like Cursor, while Option 2 is better for keeping credentials separate from configuration files.
Once configured, you can use the MCP server with compatible AI assistants:
get-grades
Retrieves academic grades from SABIS system.
Example Usage:
// Through MCP-enabled AI assistant
"Get my grades from SABIS"
Response Format:
Login successful! π
Academic Year: 2024 - Semester: Bahar
=== SWE310 - MOBΔ°L UYGULAMA GELΔ°ΕTΔ°RME ===
Grup: 1. ΓΔretim A Grubu
β’ Ara SΔ±nav (45%): 95
β’ Γdev (5%): 100
β’ Final (50%): 85
π Final Grade: AA
# Install dependencies
npm install
# Build the project
npm run build
# Test the server
node build/index.js
sabis-mcp-server/
βββ src/
β βββ index.ts # Main MCP server implementation
βββ build/ # Compiled JavaScript output
βββ package.json # Dependencies and scripts
βββ tsconfig.json # TypeScript configuration
βββ README.md # This file
@modelcontextprotocol/sdk
"Username and password are required"
USERNAME
and PASSWORD
are set.env
file exists and contains correct credentials"Login failed"
Browser/Puppeteer errors
sudo apt-get install -y libgbm-dev libnss3-dev libxss1 libasound2
get-grades
Authenticates with SABIS and retrieves academic grade information.
Parameters: None (uses environment variables)
Returns:
git checkout -b feature/amazing-feature
)git commit -m 'Add some amazing feature'
)git push origin feature/amazing-feature
)This project is licensed under the ISC License - see the LICENSE file for details.
This tool is for educational purposes and personal use only. Users are responsible for:
The developers are not responsible for any misuse or consequences arising from the use of this software.
Mehmet Hanifi ΕentΓΌrk
Note: This is an unofficial tool and is not affiliated with Sakarya University or the official SABIS system.
High-quality screenshot capture optimized for Claude Vision API. Automatically tiles full pages into 1072x1072 chunks (1.15 megapixels) with configurable viewports and wait strategies for dynamic content.
Extracts information from YouTube videos and channels using the YouTube Data API.
Retrieves transcripts from YouTube videos for content analysis and processing.
Fast, token-efficient web content extraction that converts websites to clean Markdown. Features Mozilla Readability, smart caching, polite crawling with robots.txt support, and concurrent fetching with minimal dependencies.
Fetches and converts website content to Markdown with AI-powered cleanup, OpenAPI support, and stealth browsing.
Integrate real-time Scrapeless Google SERP(Google Search, Google Flight, Google Map, Google Jobs....) results into your LLM applications. This server enables dynamic context retrieval for AI workflows, chatbots, and research tools.
An MCP server for advanced web crawling, content extraction, and AI-powered analysis using the crawl4ai library.
Remote browser automation using the BrowserCat API.
Control the Chrome browser for web automation using an AI model. Requires the MCP Chrome extension.
Use 3,000+ pre-built cloud tools to extract data from websites, e-commerce, social media, search engines, maps, and more