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securityA
license-
qualityProvides Trivy security scanning capabilities through a standardized interface, allowing users to scan projects for vulnerabilities and automatically fix them by updating dependencies.
Last updated -
10
MIT License
Provides code review and security analysis specifically tailored for Django applications, including models, views, and Django-specific security best practices
Offers specialized code quality assessment for FastAPI applications, focusing on async patterns, data validation, and API security practices
Delivers comprehensive security auditing and code review for Flask applications, including route handlers, authentication patterns, and Flask-specific vulnerabilities
Provides comprehensive Python code analysis including PEP 8 compliance checking, security vulnerability detection, performance optimization suggestions, and code quality assessment
Performs security analysis and code quality review for SQLAlchemy code, focusing on query security, ORM patterns, and SQL injection prevention
Python Code Review MCP Agent 🐍🔍
A comprehensive Model Context Protocol (MCP) server designed specifically for backend developers working with Python. This agent provides detailed code quality and security analysis with consistent, actionable reporting.
🎯 Key Features
🔒 Security-First Analysis
SQL Injection Detection - String formatting, concatenation, f-strings
Command Injection Prevention - os.system(), subprocess with shell=True
Code Injection Scanning - eval(), exec() usage detection
Secrets Detection - Hardcoded passwords, API keys, tokens
Crypto Security - Weak random number generation, SSL issues
📊 Code Quality Assessment
PEP 8 Compliance - Naming conventions, style guidelines
Exception Handling - Bare except, broad exceptions
Performance Patterns - Inefficient loops, list operations
Import Management - Wildcard imports, multiple imports
Code Complexity - Function length, maintainability
📋 Detailed Reporting
Executive Summaries - Risk assessment, deployment readiness
Quality Scorecards - 0-100 scoring for quality and security
Severity Levels - Critical, High, Medium, Low prioritization
Actionable Suggestions - Specific fix recommendations
Comparison Reports - Before/after improvement tracking
🛠️ Available MCP Tools
1. review_python_code
Comprehensive analysis with detailed, summary, or security-focused reports.
{
"code": "your_python_code_here",
"filename": "optional_filename.py",
"reportType": "detailed" // "detailed", "summary", or "security"
}
2. security_audit
Focused security vulnerability scanning with threat analysis.
{
"code": "your_python_code_here",
"filename": "optional_filename.py"
}
3. analyze_code_quality
Deep code quality analysis with configurable focus areas.
{
"code": "your_python_code_here",
"filename": "optional_filename.py",
"includeStyle": true,
"includeMaintainability": true
}
4. compare_code_versions
Compare original vs. revised code to track improvements.
{
"originalCode": "original_version_here",
"revisedCode": "improved_version_here",
"filename": "optional_filename.py"
}
5. get_improvement_suggestions
Get targeted suggestions for specific areas of concern.
{
"code": "your_python_code_here",
"filename": "optional_filename.py",
"focusArea": "security" // "security", "quality", "performance", "style", "all"
}
🚀 Quick Start
Installation
npm install
npm run build
Running Tests
npm test
Starting the MCP Server
npm start
Running Demo
node dist/demo.js
⚙️ MCP Client Configuration
Add to your MCP client configuration:
{
"mcpServers": {
"python-code-review": {
"command": "node",
"args": ["/path/to/python_code_review_mcp/dist/index.js"]
}
}
}
📖 Usage Examples
Security Analysis
"Audit this Python Flask endpoint for security vulnerabilities"
@app.route('/user/<user_id>')
def get_user(user_id):
query = f"SELECT * FROM users WHERE id = {user_id}"
cursor.execute(query)
return cursor.fetchone()
Result: Detects SQL injection vulnerability, provides secure parameterized query solution.
Code Quality Review
"Review this data processing function for quality issues"
def process_data(items):
result = []
for i in range(len(items)):
result += [items[i].upper()]
return result
Result: Identifies performance issues, suggests enumerate() and list comprehensions.
Improvement Tracking
"Compare my original code with the improved version"
Result: Shows quality score improvements, security enhancements, and resolved issues.
🎯 Perfect for Backend Developers
🏗️ Framework Support
Django - Models, views, security best practices
Flask - Route handlers, authentication, security
FastAPI - Async patterns, data validation
SQLAlchemy - Query security, ORM patterns
🔧 Development Workflow
Pre-commit Analysis - Catch issues before they reach production
Code Review Assistant - Comprehensive analysis for pull requests
Security Auditing - Regular vulnerability assessments
Refactoring Guide - Systematic improvement tracking
📊 Quality Metrics
Security Score (0-100) - Vulnerability risk assessment
Quality Score (0-100) - Code quality measurement
Issue Density - Problems per 100 lines of code
Risk Level - Overall deployment readiness
🧪 Comprehensive Testing
40/40 Tests Passing - 100% test coverage
Security Detection - All major vulnerability types
Quality Analysis - PEP 8, best practices, performance
Report Generation - Multiple formats and detail levels
Edge Cases - Empty code, comments, mixed indentation
Real-World Examples - Flask apps, Django models, data processing
🔍 Detection Capabilities
🚨 Critical Security Issues
SQL injection vulnerabilities
Command injection risks
Code injection through eval/exec
Hardcoded secrets and credentials
⚠️ High Priority Issues
SSL verification disabled
Subprocess with shell=True
Broad exception handling
📋 Quality Improvements
PEP 8 naming conventions
Performance anti-patterns
Import organization
Documentation completeness
📈 Scoring System
Security Score Calculation
100: No security vulnerabilities detected
70-99: Minor security concerns
30-69: Moderate security risks
0-29: Critical security vulnerabilities
Quality Score Calculation
90-100: Excellent code quality
80-89: Good code quality
70-79: Fair code quality
60-69: Poor code quality
0-59: Critical quality issues
🎉 Production Ready
✅ Zero Dependencies - No external APIs required
✅ Fast Analysis - Local pattern matching
✅ Consistent Reports - Standardized output format
✅ TypeScript - Full type safety and IntelliSense
✅ Error Handling - Graceful failure and recovery
✅ MCP Standards - Compatible with all MCP clients
Transform your Python code review process with intelligent, automated analysis focused on the specific needs of backend developers! 🐍✨
hybrid server
The server is able to function both locally and remotely, depending on the configuration or use case.
Tools
Enables comprehensive security vulnerability scanning and code quality analysis for Python applications. Provides detailed reports with scoring, actionable suggestions, and comparison tracking specifically designed for backend developers working with frameworks like Django, Flask, and FastAPI.
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