Code Review Mcp — independently scanned and version-tracked by SaferSkills.
SaferSkills independently audited Code Review Mcp (Agent Skill) and scored it 100/100 (green). The audit ran 55 deterministic rules across Security, Supply Chain, Maintenance, Transparency, and Community; it found 0 high-severity and 0 lower-severity findings. The full rule-by-rule trace and per-finding evidence are below. Free, methodology-open.
Findings & checks · 0 flagged
Every scanned point with the score it earned and what moved between them.
First recorded scan — no prior version to compare against.
The primary manifest — the file an agent reads to learn what this artifact does.
A Model Context Protocol (MCP) server that performs comprehensive code reviews using multiple AI models (O3, Gemini, Claude Opus) and consolidates the results with GPT-4.
git clone <repository-url>
cd code_review_mcppip install -r requirements.txtpip install -e .You'll need API keys from:
Choose one of these two methods to provide your API keys:
cp .env.template .env
# Edit .env and add your API keys{
"mcpServers": {
"code-review": {
"command": "python",
"args": ["-m", "code_review_mcp.server"]
}
}
}Add API keys directly to your Claude Code MCP settings:
{
"mcpServers": {
"code-review": {
"command": "python",
"args": ["-m", "code_review_mcp.server"],
"env": {
"OPENAI_API_KEY": "your-openai-key",
"GOOGLE_API_KEY": "your-google-key",
"ANTHROPIC_API_KEY": "your-anthropic-key",
"HUGGINGFACE_API_KEY": "your-huggingface-key"
}
}
}
}The server provides one tool:
multi_model_code_reviewPerforms comprehensive code review using multiple AI models.
Parameters:
code (required): The source code to reviewdescription (required): Author's description of the code's purposelanguage (optional): Programming language (default: auto-detect)Example usage in Claude:
Please review this Python function using the multi_model_code_review tool:
Code:
def calculate_average(numbers):
total = 0
for num in numbers:
total += num
return total / len(numbers)
Description: This function calculates the average of a list of numbers.This tool can be slow (30-60 seconds) due to:
The server includes robust error handling:
~30 seconds. Free. No account. Every finding cites a rule and a line of evidence.