# 1. Clone and setup (1 minute)
git clone https://github.com/williamzujkowski/mcp-standards-server.git
cd mcp-standards-server
python -m venv venv && source venv/bin/activate

# 2. Install core dependencies (2 minutes)
pip install -e .

# 3. Verify CLI installation (30 seconds)
python -m src.cli.main --help
python -m src.cli.main status

# 4. Test MCP server functionality (1 minute)
python -m src  # Should load 31 standards and initialize MCP server

# 5. Check available standards (30 seconds)
python -m src.cli.main cache --list  # View cached standards

# Install the latest release
pip install mcp-standards-server

# Or install with specific feature sets:
pip install "mcp-standards-server[full]"         # All features including web API
pip install "mcp-standards-server[test]"         # Testing tools only
pip install "mcp-standards-server[dev]"          # Development tools
pip install "mcp-standards-server[performance]"  # Performance monitoring tools

# Clone the repository
git clone https://github.com/williamzujkowski/mcp-standards-server.git
cd mcp-standards-server

# Create and activate virtual environment (recommended)
python -m venv venv
source venv/bin/activate  # On Windows: venv\Scripts\activate

# Install in development mode
pip install -e .

# Or install with specific feature sets:
pip install -e ".[full]"         # All features including web API
pip install -e ".[test]"         # Testing tools only
pip install -e ".[dev]"          # Development tools (linting, formatting)
pip install -e ".[performance]"  # Performance monitoring tools

# Install all development dependencies
pip install -e ".[dev,test,performance,visualization,full]"

# Install Redis (optional but recommended for caching)
# macOS: 
brew install redis
brew services start redis

# Ubuntu/Debian:
sudo apt-get update
sudo apt-get install redis-server
sudo systemctl start redis-server

# Windows (using WSL2):
wsl --install  # If not already installed
# Then follow Ubuntu instructions inside WSL

# Or use Docker:
docker run -d -p 6379:6379 redis:alpine

# Run basic tests to verify core functionality
pytest tests/unit/core/standards/test_rule_engine.py -v

# Check if the project is properly installed
python -c "import src; print('Installation successful')"

# Note: The CLI command (mcp-standards) requires the package to be installed
# in the current environment. If you see import errors, ensure you've run:
# pip install -e .

from pathlib import Path
from src.core.standards.rule_engine import RuleEngine

# Load the rule engine
rules_path = Path("data/standards/meta/standard-selection-rules.json")
engine = RuleEngine(rules_path)

# Define your project context
context = {
    "project_type": "web_application",
    "framework": "react",
    "language": "javascript",
    "requirements": ["accessibility", "performance"]
}

# Get applicable standards
result = engine.evaluate(context)
print(f"Selected standards: {result['resolved_standards']}")

# Start the MCP server (stdio mode for tool integration)
python -m src

# Or use the CLI
mcp-standards --help

# Start MCP server with specific options
mcp-standards serve --stdio         # For direct tool integration
mcp-standards serve --port 3000     # HTTP server mode
mcp-standards serve --daemon        # Run as background service

# Start the web UI (requires separate setup)
cd web && ./start.sh

# Example: Using with MCP client
import mcp

# Connect to the MCP server
async with mcp.Client("stdio://python -m src") as client:
    # Get applicable standards for a project
    result = await client.call_tool(
        "get_applicable_standards",
        context={
            "project_type": "web_application",
            "framework": "react",
            "requirements": ["accessibility", "security"]
        }
    )
    
    # Validate code against standards
    validation = await client.call_tool(
        "validate_against_standard",
        code_path="./src",
        standard_id="react-18-patterns"
    )
    
    # Search for specific guidance
    search_results = await client.call_tool(
        "search_standards",
        query="authentication best practices",
        limit=5
    )

# Copy the kickstart prompt for any LLM
cat kickstart.md

# Check for updates
mcp-standards sync --check

# Perform synchronization
mcp-standards sync

# Force sync all files (ignore cache)
mcp-standards sync --force

# View sync status
mcp-standards status

# Manage cache
mcp-standards cache --list
mcp-standards cache --clear

# List available templates
mcp-standards generate list-templates

# Generate a new standard interactively
mcp-standards generate --interactive

# Generate from a specific template
mcp-standards generate --template standards/technical.j2 --title "My New Standard"

# Generate domain-specific standard
mcp-standards generate --domain ai_ml --title "ML Pipeline Standards"

# Validate an existing standard
mcp-standards generate validate path/to/standard.md

# Start the web UI
cd web
./start.sh

# Or run components separately:
# Backend API
cd web/backend
pip install -r requirements.txt
python main.py

# Frontend
cd web/frontend
npm install
npm start

# Query standards based on project context
mcp-standards query --project-type web --framework react --language javascript

# Validate code against standards
mcp-standards validate src/ --format json --severity warning

# Auto-fix code issues (preview mode)
mcp-standards validate src/ --fix --dry-run

# Configuration management
mcp-standards config --init        # Initialize configuration
mcp-standards config --show        # Display current config
mcp-standards config --validate    # Validate config file

{
  "id": "react-web-app",
  "name": "React Web Application Standards",
  "priority": 10,
  "conditions": {
    "logic": "AND",
    "conditions": [
      {
        "field": "project_type",
        "operator": "equals",
        "value": "web_application"
      },
      {
        "field": "framework",
        "operator": "in",
        "value": ["react", "next.js", "gatsby"]
      }
    ]
  },
  "standards": [
    "react-18-patterns",
    "javascript-es2025",
    "frontend-accessibility"
  ],
  "tags": ["frontend", "react", "web"]
}

mcp-standards-server/
├── src/
│   ├── core/
│   │   ├── mcp/              # MCP server implementation
│   │   ├── standards/        # Standards engine & storage
│   │   └── cache/            # Redis caching layer
│   ├── analyzers/            # Language-specific analyzers
│   ├── generators/           # Standards generation system
│   └── cli/                  # CLI interface
├── web/                      # React/TypeScript UI (separate app)
│   ├── frontend/            # React application
│   └── backend/             # FastAPI backend
├── data/
│   └── standards/            # 25 comprehensive standards
│       ├── meta/            # Rule engine configuration
│       └── cache/           # Local file cache
├── templates/                # Standard generation templates
├── tests/                    # Comprehensive test suite
├── benchmarks/              # Performance benchmarking
└── docs/                    # Documentation

# Run all tests
pytest

# Run with coverage
pytest --cov=src --cov-report=term-missing

# Run specific test categories
pytest tests/unit/          # Unit tests only
pytest tests/integration/   # Integration tests
pytest tests/e2e/          # End-to-end tests

# Run specific test file
pytest tests/unit/core/standards/test_rule_engine.py

# Run performance tests
python run_performance_tests.py

# Run tests in parallel (faster)
python run_tests_parallel.py

# Clone the repository
git clone https://github.com/williamzujkowski/mcp-standards-server.git
cd mcp-standards-server

# Create virtual environment
python -m venv venv
source venv/bin/activate  # On Windows: venv\Scripts\activate

# Install in development mode with all dependencies
pip install -e ".[dev,test,performance,visualization,full]"

# Install pre-commit hooks (if available)
pre-commit install

# Run all benchmarks
python benchmarks/run_benchmarks.py

# Run specific benchmark suites
python benchmarks/analyzer_performance.py
python benchmarks/semantic_search_benchmark.py
python benchmarks/token_optimization_benchmark.py

# Generate performance reports
python benchmarks/run_benchmarks.py --report

# Example GitHub Actions workflow
- name: Validate Standards
  run: |
    pip install mcp-standards-server
    mcp-standards validate . --format sarif --output results.sarif
    
- name: Upload SARIF results
  uses: github/codeql-action/upload-sarif@v2
  with:
    sarif_file: results.sarif