ADA Audits MCP Server

ADA-Audits

Automated Data Accessibility Audits for Python projects.

📌 Features

• Scans Python files and notebooks for data accessibility issues
• Detects missing docstrings, type hints, and accessibility standards
• Generates reports with actionable insights
• Integrates with CI/CD pipelines

🚀 Quick Start

Follow these steps to get started with ADA-Audits:

Step 1: Installation

Using pip:

# Clone the repository
git clone https://github.com/your-org/ada-audits.git
cd ada-audits

# Install in development mode
pip install -e .

Using Poetry:

# Clone the repository
git clone https://github.com/your-org/ada-audits.git
cd ada-audits

# Install dependencies with Poetry
poetry install

# Activate the virtual environment
poetry shell

Step 2: Create Configuration File

Create a .ada-audit.yml file in your project root:

# .ada-audit.yml - Minimal working configuration
targets:
  - src/
  - notebooks/

rules:
  - missing-docstring
  - missing-type-hint
  - accessibility-issue

output:
  format: markdown
  file: audit-report.md

Step 3: Run Your First Audit

Scan a single file:

ada-scan path/to/file.py

Expected output:

✓ Scanning: path/to/file.py
Found 3 issues:
  [WARNING] line 15: Missing docstring for function 'process_data'
  [WARNING] line 23: Missing type hint for parameter 'input_path'
  [ERROR]   line 45: Accessibility issue - missing alt text for image

Scan an entire directory:

ada-scan src/

Expected output:

✓ Scanning directory: src/
Found 12 files to analyze
  src/__init__.py .............. OK
  src/main.py .................. 2 issues
  src/utils.py ................. 5 issues
  src/processors/base.py ....... 1 issue
  src/processors/transform.py .. 4 issues

Summary: 12 issues found across 4 files

Generate a full report:

ada-audit --output report.md

Expected output:

✓ ADA Audit Report Generated
  Output: report.md
  Total files scanned: 12
  Issues found: 15
  Compliance score: 78%

📖 Usage

Command Line Interface

Configuration Reference

Full configuration options for .ada-audit.yml:

# Paths to scan
targets:
  - src/              # Python source files
  - notebooks/        # Jupyter notebooks
  - tests/            # Test files

# Rules to apply
rules:
  - missing-docstring      # Functions/classes without docstrings
  - missing-type-hint      # Parameters without type annotations
  - accessibility-issue    # Accessibility standard violations

# Output settings
output:
  format: markdown         # Options: markdown, json, html
  file: audit-report.md   # Output filename

# Optional: Exclude patterns
exclude:
  - "**/__pycache__/**"
  - "**/migrations/**"

🤝 Contributing

1. Fork the repository
2. Create a feature branch (git checkout -b feature/your-feature)
3. Commit your changes (git commit -m 'feat: add new rule [ranukita:xxxxx]')
4. Push to the branch (git push origin feature/your-feature)
5. Open a Pull Request

📄 License

This project is licensed under the MIT License - see the LICENSE file for details.