Multi Model Review
🐍 🍎 🪟 🐧 - Parallel multi-model code review, security analysis, and AI debate with ChatGPT, Claude, and Gemini. Orchestrates multiple LLMs for compare, consensus, and OWASP Top 10 security checks.
What is Multi Model Review?
Multi Model Review is a Model Context Protocol (MCP) server that allows AI assistants like Claude, Cursor, and VS Code to 🐍 🍎 🪟 🐧 - parallel multi-model code review, security analysis, and ai debate with chatgpt, claude, and gemini. orchestrates multiple llms for compare, consensus, and owasp top 10 security checks.
🐍 🍎 🪟 🐧 - Parallel multi-model code review, security analysis, and AI debate with ChatGPT, Claude, and Gemini. Orchestrates multiple LLMs for compare, consensus, and OWASP Top 10 security checks.
This server falls under the Coding Agents category on MCPgee, the world's largest MCP server directory with 33,000+ servers.
Features
- 🐍 🍎 🪟 🐧 - Parallel multi-model code review, security analysi
Use Cases
Maintainer
Works with
Installation
PIP
pip install multi-mcpManual Installation
pip install multi-mcpConfiguration
Configuration Details
claude_desktop_config.json
Performance
Response Metrics
Resource Usage
How to Set Up and Use Multi Model Review
Multi-MCP is a Python MCP server that orchestrates parallel code review, architectural comparison, and AI debate across multiple large language models — ChatGPT, Claude, and Gemini — from within a single AI assistant session. It exposes four core tools (chat, codereview, compare, debate) and includes OWASP Top 10 security checking as part of its code review workflow. Engineering teams and AI researchers use it to get consensus-driven second opinions on code quality, architecture decisions, and security vulnerabilities without manually querying multiple AI services.
Prerequisites
- Python 3.11 or higher with uv package manager
- At least one API key: OPENAI_API_KEY, ANTHROPIC_API_KEY, or GEMINI_API_KEY
- Claude Desktop or Claude Code as the MCP client
- Git to clone the repository
Clone the repository
Clone the multi_mcp repository to a local directory.
git clone https://github.com/religa/multi_mcp.git
cd multi_mcpInstall dependencies using make (recommended)
The make install target installs dependencies, generates an .env file, and optionally auto-configures Claude Code or OpenCode.
make installAlternative manual setup
If you prefer manual control, sync dependencies with uv and copy the example env file.
uv sync
cp .env.example .envAdd API keys to .env
Edit the .env file and add at least one provider API key. Multiple keys enable cross-model comparison.
OPENAI_API_KEY=your_openai_key
ANTHROPIC_API_KEY=your_anthropic_key
GEMINI_API_KEY=your_gemini_key
# Optional
OPENROUTER_API_KEY=your_openrouter_keyRegister with Claude Code or Claude Desktop
Add the server to ~/.claude.json (Claude Code) or claude_desktop_config.json (Claude Desktop). Use the absolute path to the venv Python binary.
{
"mcpServers": {
"multi": {
"type": "stdio",
"command": "/absolute/path/to/multi_mcp/.venv/bin/python",
"args": ["-m", "multi_mcp.server"]
}
}
}Multi Model Review Examples
Client configuration
Claude Code configuration using the virtual environment Python binary to run the multi_mcp server module.
{
"mcpServers": {
"multi": {
"type": "stdio",
"command": "/home/user/multi_mcp/.venv/bin/python",
"args": ["-m", "multi_mcp.server"],
"env": {
"OPENAI_API_KEY": "your_openai_key",
"ANTHROPIC_API_KEY": "your_anthropic_key",
"GEMINI_API_KEY": "your_gemini_key"
}
}
}
}Prompts to try
Multi-model orchestration prompts using the four core tools.
- "multi codereview this authentication module for OWASP Top 10 vulnerabilities using gemini and gpt-4o."
- "multi compare the best approach to database connection pooling in Node.js across Claude and GPT."
- "multi debate whether microservices or a modular monolith is better for our current team size."
- "multi chat with Gemini about the trade-offs of using Redis for session management in this project."Troubleshooting Multi Model Review
make install fails or the venv Python path is wrong after installation
Run uv sync manually then locate the venv with find . -name python -path '*/.venv/*'. Use that absolute path in the MCP config command field.
Only one model responds instead of multiple models running in parallel
The server uses only providers with valid API keys in .env. Confirm all desired keys are present and that the .env file is in the multi_mcp project root directory, not a parent directory.
Code review results don't include OWASP checks
OWASP Top 10 checking is included in the codereview tool by default. Ensure you are calling the codereview tool specifically (not chat) and that the code file path provided is accessible from the server's working directory.
Frequently Asked Questions about Multi Model Review
What is Multi Model Review?
Multi Model Review is a Model Context Protocol (MCP) server that 🐍 🍎 🪟 🐧 - parallel multi-model code review, security analysis, and ai debate with chatgpt, claude, and gemini. orchestrates multiple llms for compare, consensus, and owasp top 10 security checks. It connects AI assistants to external tools and data sources through a standardized interface.
How do I install Multi Model Review?
Install via pip with: pip install multi-mcp. Then configure your AI client to connect to this MCP server.
Which AI clients work with Multi Model Review?
Multi Model Review works with all major MCP-compatible AI clients including Claude Desktop, Claude Code, Cursor, VS Code (GitHub Copilot), Windsurf, and Cline.
Is Multi Model Review free to use?
Yes, Multi Model Review is open source and available under the MIT license. You can use it freely in both personal and commercial projects.
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Quick Config Preview
Add this to your claude_desktop_config.json or .cursor/mcp.json
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