Ensia Mcp Server — independently scanned and version-tracked by SaferSkills.
SaferSkills independently audited Ensia Mcp Server (Agent Skill) and scored it 100/100 (green). The audit ran 55 deterministic rules across Security, Supply Chain, Maintenance, Transparency, and Community; it found 0 high-severity and 0 lower-severity findings. The full rule-by-rule trace and per-finding evidence are below. Free, methodology-open.
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The primary manifest — the file an agent reads to learn what this artifact does.
A powerful Model Context Protocol (MCP) server that provides intelligent access to your Google Drive-based academic structure. This server allows AI assistants like Claude to navigate, search, and analyze your academic materials organized in cycles, semesters, and modules.
The MCP Academic Structure Server transforms your Google Drive academic folders into an intelligent, searchable knowledge base that AI assistants can interact with. It provides:
MCP-ENSIA/
├── src/
│ ├── clients/
│ │ └── drive_client.py # Enhanced Google Drive API client
│ ├── core/
│ │ ├── academic_structure.py # Main academic processor
│ │ ├── cycle_manager.py # Cycle processing logic
│ │ ├── semester_manager.py # Semester processing logic
│ │ ├── module_manager.py # Module processing logic
│ │ └── category_manager.py # Category processing logic
│ ├── models/
│ │ ├── academic_models.py # Data models for academic structure
│ │ └── search_models.py # Search-related models
│ ├── services/
│ │ ├── search_service.py # Search functionality
│ │ ├── navigation_service.py # Navigation services
│ │ └── comparison_service.py # Module comparison services
│ ├── utils/
│ │ └── validation_utils.py # Validation utilities
│ ├── server.py # Main MCP server
├── config/
│ ├── .env # Environment variables
│ ├── credentials.json # Google Drive credentials (user-specific)
│ └── token.json # OAuth token (auto-generated)
├── tests/ # Comprehensive test suite
├── requirements.txt # Python dependencies
└── README.md # This file| Tool | Description | Parameters |
|---|---|---|
get_academic_overview | Complete overview with statistics | max_depth (optional) |
search_academic_content | Search across academic structure | query, scope, filters |
navigate_to_path | Navigate to specific academic path | path |
list_cycles | List all academic cycles | None |
list_semesters | List semesters in a cycle | cycle |
list_modules | List modules in a semester | cycle, semester |
compare_modules | Compare two modules | module1_path, module2_path |
find_modules_by_subject | Find modules by subject | subject, exact_match |
get_structure_overview | Detailed structure information | None |
validate_path | Validate academic path format | path |
git clone <repository-url>
cd MCP-ENSIApip install -r requirements.txt# Test imports and basic functionality
python -c "
import sys
sys.path.append('src')
from src.clients.drive_client import EnhancedGoogleDriveClient
from src.core.academic_structure import AcademicStructureProcessor
print('All imports successful!')
"# Start the MCP server
python -m src.serverAdd to your Claude Desktop MCP configuration:
{
"mcpServers": {
"academic-structure": {
"command": "python",
"args": ["-m", "src.server"],
"cwd": "/path/to/MCP-ENSIA",
"env": {
"PYTHONPATH": "/path/to/MCP-ENSIA"
}
}
}
}Once integrated, you can ask Claude:
"Get an overview of my academic structure"
"List all my academic cycles"
"Show me modules in First Superior Cycle, Semester 1"
"Search for automata theory content"
"Navigate to 3. First Superior Cycle/Semester 1/Theory of Computation"
"Compare Mathematics I from different semesters"
"Find all modules that teach machine learning"# Install test dependencies
pip install pytest pytest-asyncio pytest-mock pytest-cov
# Run all tests
pytest tests/ -v
# Run with coverage
pytest tests/ --cov=src --cov-report=html
# Run specific test categories
pytest tests/test_imports.py -v # Import tests
pytest tests/unit/ -v # Unit tests
pytest tests/integration/ -v # Integration testsThis project is licensed under the MIT License - see the LICENSE file for details.
This project was made possible thanks to ETC club for the Google Drive content that they collected under Ensia Hub.
For questions, issues, or contributions:
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