npm install -g claude-code-review-mcp

# Set environment variables separately
export OPENAI_API_KEY=<key>
npx -y claude-code-review-mcp

# Or use inline environment setting
OPENAI_API_KEY=<key> npx -y claude-code-review-mcp

# Or with Google API key
GOOGLE_API_KEY=<key> npx -y claude-code-review-mcp

# Or with Anthropic API key
ANTHROPIC_API_KEY=<key> npx -y claude-code-review-mcp

# Or use multiple API keys for more model options
OPENAI_API_KEY=<key> GOOGLE_API_KEY=<key> ANTHROPIC_API_KEY=<key> npx -y claude-code-review-mcp

# Use environment variables properly (recommended approach)
claude mcp add code-review -s user -e OPENAI_API_KEY=<key> -e GOOGLE_API_KEY=<key> -e ANTHROPIC_API_KEY=<key> -- npx -y claude-code-review-mcp

# Alternative: Export the variables before adding the MCP
export OPENAI_API_KEY=<key>
export GOOGLE_API_KEY=<key>
export ANTHROPIC_API_KEY=<key>
claude mcp add code-review -s user -- npx -y claude-code-review-mcp

I'll review your code using alternative LLM models. Model to use: $ARGUMENTS

mkdir -p .claude/commands

# Create the list-review-models.md file
cat > .claude/commands/list-review-models.md << 'EOF'
I'll check which alternative code review models are available through our MCP server.

First, I'll use the MCP server to list all available models for code review.
After that, I'll present the models in a clear table format with:
- Model ID (what you'll use when requesting a review)
- Provider (OpenAI or Google)
- Description (size and capabilities)
- Speed (relative performance)

This will help you choose the right model for your code review needs.
EOF

# Create the review-with.md file
cat > .claude/commands/review-with.md << 'EOF'
I'll review the code I've just worked on using an alternative LLM model to provide a second opinion.

First, I'll identify the code changes or file you want reviewed. If you don't specify a file, I'll look at recent changes.

Then, I'll send this code to be reviewed by the specified model through our MCP server.

Available models (run /project:list-review-models to see all options):
- OpenAI models (if configured): "gpt-4.1", "o4-mini", "o3-mini"
- Google models (if configured): "gemini-2.5-pro-preview-05-06", "gemini-2.5-flash-preview-04-17"

Model to use (leave blank for default): $ARGUMENTS
EOF

# Create the structured-review.md file
cat > .claude/commands/structured-review.md << 'EOF'
I'll perform a structured code review using an alternative LLM model.

This review will be organized into clear sections:
1. Overall summary
2. Code quality assessment (strengths and weaknesses)
3. Potential bugs with severity ratings (Low/Medium/High)
4. Specific improvement suggestions
5. Security considerations (if applicable)

If you don't specify a model, I'll use the default available model.

Model to use (optional): $ARGUMENTS
EOF

# Create the freeform-review.md file
cat > .claude/commands/freeform-review.md << 'EOF'
I'll provide a conversational, narrative-style code review using an alternative LLM model.

This will be a more holistic assessment of your code with flowing paragraphs rather than structured categories. This style works well for:
- General impressions
- High-level feedback
- More nuanced commentary on code style and approach

If you don't specify a model, I'll use the default available model.

Model to use (optional): $ARGUMENTS
EOF

# Create the review-file.md file
cat > .claude/commands/review-file.md << 'EOF'
I'll review a specific file using an alternative LLM model.

Please provide the file path to review and optionally the model to use.
Format: [file_path] [model_name]

For example:
- "src/utils.js gemini-2.5-pro-preview-05-06" - Reviews utils.js with Gemini Pro
- "lib/auth.ts" - Reviews auth.ts with the default model

Input: $ARGUMENTS
EOF

# Create security review command
cat > .claude/commands/security-review.md << 'EOF'
I'll perform a security-focused code review using an alternative LLM model.

This review will specifically examine:
- Potential security vulnerabilities
- Input validation issues
- Authentication/authorization flaws
- Data protection concerns
- Injection vulnerabilities
- Secure coding best practices

If you don't specify a model, I'll use a model recommended for security analysis.

Model to use (optional): $ARGUMENTS
EOF

# Create performance review command
cat > .claude/commands/performance-review.md << 'EOF'
I'll perform a performance-focused code review using an alternative LLM model.

This review will specifically examine:
- Algorithm efficiency
- Memory usage
- Unnecessary computations
- Loop optimizations
- Data structure choices
- Caching opportunities
- Async/parallel processing considerations

If you don't specify a model, I'll use a model that's good at performance analysis.

Model to use (optional): $ARGUMENTS
EOF

# Create the project-review.md file
cat > .claude/commands/project-review.md << 'EOF'
I'll perform a comprehensive code review with full project context using an alternative LLM model.

This review will:
1. Analyze the code structure and organization
2. Consider related files and dependencies
3. Evaluate consistency with project patterns
4. Assess integration with existing components
5. Check alignment with project architecture

I'll gather project context, including directory structure and related files, to ensure a thorough, context-aware review.

Format: [file_to_review] [model_name]
Example: "src/components/Button.jsx gemini-2.5-pro-preview-05-06"

Input: $ARGUMENTS
EOF

# Create the diff-review.md file
cat > .claude/commands/diff-review.md << 'EOF'
I'll review the changes you've made to a file using an alternative LLM model.

This will:
1. Identify what was changed between versions
2. Evaluate if the changes address the intended purpose
3. Check for any new issues introduced
4. Suggest potential improvements to the changes

I'll need to know which file to examine. If you've been working on a file with Claude Code, I'll automatically find the changes.

Model to use (optional): $ARGUMENTS
EOF

/project:list-review-models
/project:review-with gemini-2.5-pro-preview-05-06
/project:structured-review o4-mini
/project:security-review
/project:review-file src/utils.js gemini-2.5-flash-preview-04-17

# Start with OpenAI API key (using exports, recommended)
export OPENAI_API_KEY=<key>
npx -y claude-code-review-mcp

# Or with inline environment variables
OPENAI_API_KEY=<key> npx -y claude-code-review-mcp

# Start with Google Gemini API key
export GOOGLE_API_KEY=<key>
npx -y claude-code-review-mcp

# Start with Anthropic Claude API key
export ANTHROPIC_API_KEY=<key>
npx -y claude-code-review-mcp

# Use multiple API keys for more model options
export OPENAI_API_KEY=<key>
export GOOGLE_API_KEY=<key>
export ANTHROPIC_API_KEY=<key>
npx -y claude-code-review-mcp

# Use custom port and host
export OPENAI_API_KEY=<key>
export PORT=8080 
export HOST=0.0.0.0
npx -y claude-code-review-mcp

{
  code: string;  // Required: The code to review
  filename?: string;  // Optional: The filename with extension
  language?: string;  // Optional: Programming language
  model: string;  // Required: Model ID to use for review
  projectContext?: {  // Optional: Additional context
    projectStructure?: string;  // Directory structure
    relatedFiles?: Array<{  // Related code files
      name: string;  // Filename with path
      language?: string;  // File language
      content: string;  // File content
    }>;
    commitMessage?: string;  // Purpose of changes
    dependencies?: Record<string, string>;  // Project dependencies
  }
}

{
  review?: {  // Present on success
    summary: string;  // Overall assessment
    quality: {
      strengths: string[];  // Good aspects
      weaknesses: string[];  // Areas for improvement
    };
    bugs: Array<{
      description: string;  // Issue description
      severity: "Low" | "Medium" | "High";  // Impact level
      suggestion: string;  // How to fix
    }>;
    improvements: string[];  // Enhancement suggestions
    securityIssues?: string[];  // Security concerns if any
  };
  modelUsed: string;  // Human-readable model name
  error?: string;  // Present on error
  availableModels?: Record<string, string>;  // Present on error or listModels
}

{
  reviewText?: string;  // Present on success
  modelUsed: string;  // Human-readable model name
  error?: string;  // Present on error
  availableModels?: Record<string, string>;  // Present on error or listModels
}

{
  availableModels: Record<string, string>;  // Model ID to name mapping
  modelUsed: string;  // Always "None" for this tool
}

claude mcp add code-review -s user npx -y claude-code-review-mcp

/code-review:reviewCodeStructured --model o4-mini

"claude-code-review-mcp": {
  "command": "npx",
  "args": ["-y", "claude-code-review-mcp"],
  "env": {
    "OPENAI_API_KEY": "your-openai-key",
    "GOOGLE_API_KEY": "your-google-key",
    "ANTHROPIC_API_KEY": "your-anthropic-key"
  }
}

# Install dependencies
npm install

# Start in development mode
npm run dev

# Build for production
npm run build

# Start in production mode
npm run start