argus
AI code review MCP server with Zero-Trust approach. Multi-model support, caching, multilingual. Works with Windsurf & Claude Desktop
claude mcp add --transport stdio lokafinnsw-argus-mcp /absolute/path/to/argus-mcp/venv/bin/python /absolute/path/to/argus-mcp/server_v2.py \ --env GLM_API_KEY="your_glm_api_key" \ --env DEFAULT_MODEL="glm-4.7" \ --env OPENROUTER_API_KEY="your_openrouter_api_key"
How to use
Argus MCP provides AI-powered code review with a zero-trust approach. It orchestrates multiple AI models (such as GLM 4.7, Gemini 3 Flash Preview, and MiniMax M2.1) to inspect code and produce structured feedback categorized as Must Fix, Should Fix, and Suggestions. With language-aware checks, security reviews (OWASP), and architecture evaluations, Argus supports single-file, git-diff, and multi-file review modes. To use it, run the MCP server via your environment and connect from any MCP client (Windsurf, Claude Desktop, Cursor, or other MCP-compatible tools). The tool automatically determines the appropriate review scope based on your IDE context and the files under consideration, returning a detailed, actionable report.
Key capabilities include:
- Zero-Trust code review that prioritizes security and correctness
- Mode selection (Single File, Git Diff, Multiple Files) based on context
- Language-specific checks for Python, JavaScript, TypeScript, and more (10+ languages)
- Smart retry and model fallback to ensure robust results
- Caching of results to speed up repeated checks
- Clear output formatting with exact file references and remediation steps
How to install
Prerequisites:
- Python 3.11+ installed
- A Python virtual environment workflow (venv) or similar
- Git available to clone the repository
- API keys for GLM and OpenRouter (as required by configuration)
Step-by-step installation:
- Clone the repository and set up a virtual environment
git clone https://github.com/lokafinnsw/argus-mcp.git
cd argus-mcp
python3 -m venv venv
source venv/bin/activate # On Windows: venv\Scripts\activate
- Install dependencies
pip install -r requirements.txt
- Create and configure environment variables
cp .env.example .env
Edit .env to include your API keys (GLM_API_KEY, OPENROUTER_API_KEY) and default model (DEFAULT_MODEL).
- Run the Argus MCP server
python server_v2.py
- Connect via an MCP client (Windsurf, Claude Desktop, Cursor) using the configured mcp_config.json path, typically pointing to "/absolute/path/to/argus-mcp/venv/bin/python" with the server script as an argument.
Additional notes
Tips and notes:
- Ensure the absolute installation path is correctly referenced in your MCP client configurations (replace /absolute/path/to/argus-mcp).
- Store API keys securely in the .env file and add it to your .gitignore.
- If you encounter model timeouts or rate limits, leverage Argus' multi-model fallback and caching to reduce latency.
- When updating dependencies or models, re-run installation steps and verify client reloads (Windsurf, Claude Desktop, Cursor).
- For troubleshooting, check server_v2.py logs and environment variable loading errors; verify that the Python virtual environment is active when launching.
Related MCP Servers
Mantic.sh
A structural code search engine for Al agents.
cursor-rust-tools
A MCP server to allow the LLM in Cursor to access Rust Analyzer, Crate Docs and Cargo Commands.
ls
List MCP Server configurations in your system used by AI applications like Cursor, Claude Desktop, VS Code and others
memory
A MCP (Model Context Protocol) server providing long-term memory for LLMs
shodan
Shodan MCP server for Claude, Cursor & VS Code. 20 tools for passive reconnaissance, CVE/CPE intelligence, DNS analysis, and device search. 4 tools work free without an API key. OSINT and vulnerability research from your IDE.
mcp -nodejs-api-docs
MCP Server for Node.js API documentation