Multi-Model Code Review and Analysis MCP Server for Claude Code
Project description
Quantum Code
Enterprise-Grade Multi-Model Code Analysis MCP Server
Quantum Code is a production-ready AI orchestration platform that seamlessly integrates with Claude Code CLI to deliver comprehensive code review, security analysis, and multi-agent consensus using multiple large language models simultaneously. Built for modern development teams requiring automated code quality assurance.
๐ Key Features
Core Capabilities
- ๐ Automated Code Review - Comprehensive analysis with OWASP Top 10 security validation
- ๐ฌ Intelligent Chat - Context-aware development assistance with repository understanding
- ๐ Multi-Model Comparison - Parallel execution across different AI providers
- ๐ญ Consensus Engine - Multi-agent debate with independent analysis and critique
- ๐ก๏ธ Security First - Built-in vulnerability detection and code quality assurance
Model Support
- ๐ค Multi-Provider Integration - OpenAI GPT, Anthropic Claude, Google Gemini, OpenRouter
- ๐ฅ๏ธ Hybrid Execution - Seamless mixing of CLI and API-based models
- ๐ท๏ธ Smart Aliasing - Intuitive model shortcuts (
mini,sonnet,gemini) - ๐งต Context Persistence - Thread-safe conversation management across review sessions
Enterprise Features
- โก High Performance - Async architecture with parallel model execution
- ๐ง Configurable - Flexible model selection and parameter tuning
- ๐ Analytics - Token usage tracking and performance metrics
- ๐ Secure - Isolated execution environments and credential management
๐ Quick Start
Installation
pip install quantum-code
Basic Usage
# Start the MCP server
quantum-server
# Or use CLI for direct code review
quantum src/ --model gemini-3
# Get help
quantum --help
Claude Code Integration
Add to ~/.claude.json:
{
"mcpServers": {
"quantum": {
"command": "quantum-server"
}
}
}
๐ Performance & Architecture
Performance Metrics
| Capability | Performance | Benchmark |
|---|---|---|
| Multi-Model Execution | โก 3 models in ~10s | 3x faster than sequential |
| Async Processing | ๐ Non-blocking I/O | Python asyncio framework |
| Context Management | ๐พ Thread-safe persistence | Across review sessions |
| Response Optimization | ๐ Minimal latency | Only slowest model time |
System Architecture
โโโโโโโโโโโโโโโโโโโ โโโโโโโโโโโโโโโโโโโโ โโโโโโโโโโโโโโโโโโโ
โ Claude Code โโโโโถโ Quantum Code โโโโโถโ AI Providers โ
โ Client โ โ MCP Server โ โ (GPT, Claude, โ
โโโโโโโโโโโโโโโโโโโ โโโโโโโโโโโโโโโโโโโโ โ Gemini, etc.) โ
โ โโโโโโโโโโโโโโโโโโโ
โผ
โโโโโโโโโโโโโโโโโโโโ
โ Analysis Tools โ
โ โข Code Review โ
โ โข Security Scan โ
โ โข Chat Assistant โ
โ โข Model Compare โ
โโโโโโโโโโโโโโโโโโโโ
๐ค Supported Models
API Models
- OpenAI:
gpt-5-mini,gpt-5.2,gpt-5.1-codex - Anthropic:
claude-haiku-4.5,claude-sonnet-4.5,claude-opus-4.5 - Google:
gemini-2.5-pro,gemini-3-flash,gemini-3-pro - Azure OpenAI:
azure-gpt-5-mini - AWS Bedrock:
bedrock-claude-4-5-sonnet
CLI Models
- Gemini CLI:
gemini-cli(alias:gem-cli) - Codex CLI:
codex-cli(alias:cx-cli) - Claude CLI:
claude-cli(alias:cl-cli)
๐ง Configuration
Environment Variables
# API Keys (at least one required)
OPENAI_API_KEY=sk-...
ANTHROPIC_API_KEY=sk-ant-...
GEMINI_API_KEY=...
# Model Settings
DEFAULT_MODEL=gemini-3
DEFAULT_MODEL_LIST=codex,gemini-3,sonnet
DEFAULT_TEMPERATURE=0.2
# Server Settings
LOG_LEVEL=INFO
MAX_FILES_PER_REVIEW=100
MAX_FILE_SIZE_KB=50
Model Configuration
Create ~/.quantum_code/config.yaml:
version: "1.0"
models:
my-custom-model:
litellm_model: openai/gpt-4o
aliases:
- custom
notes: "My custom GPT-4o configuration"
๐ Usage Examples
Code Review
# Review with specific model
quantum src/ --model sonnet
# Multi-model analysis
quantum src/ --models codex,gemini-3,sonnet
Interactive Chat
# Chat with repository context
quantum chat "How does the authentication work?"
Model Comparison
# Compare different approaches
quantum compare "Best state management for React app?"
๐ก๏ธ Security & Quality
- OWASP Top 10 Analysis - Automated security vulnerability detection
- Performance Patterns - Code efficiency and optimization suggestions
- Architecture Review - Design pattern and structural analysis
- Multi-Model Consensus - Cross-validation from different AI perspectives
๐ Workflow Modes
| Mode | Description | Use Case |
|---|---|---|
| codereview | Systematic code analysis | Code quality, security, performance |
| chat | Interactive development help | Questions, explanations, guidance |
| compare | Multi-model comparison | Architecture decisions, approach evaluation |
| debate | Consensus building | Complex decisions, validation |
๐ Architecture
Core Components
- FastMCP Server - Model Context Protocol implementation
- LiteLLM Integration - Unified API for 100+ LLM providers
- Async Processing - Concurrent model execution
- Context Management - Thread-safe request scoping
- Artifact Storage - File output management
Design Principles
- DRY (Don't Repeat Yourself) - Single source of truth for schemas
- Type Safety - Full Pydantic validation
- Async-First - All I/O operations are asynchronous
- Factory Pattern - Auto-generated MCP tools from schemas
๐ค Contributing
We welcome contributions! See our GitHub repository for:
- Development setup instructions
- Code standards and guidelines
- Testing procedures
- Pull request process
๐ License
MIT License - see LICENSE file for details.
๐จโ๐ป Author
Nishant Gaurav - Codewithevilxd
๐ Links
- Homepage: https://github.com/Codewithevilxd/quantum-code
- PyPI: https://pypi.org/project/quantum-code/
- Issues: https://github.com/Codewithevilxd/quantum-code/issues
Quantum Code - Multi-Model AI Orchestration for Superior Code Analysis
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