Code Review MCP Server

AI-powered code review MCP server for automated pull request analysis.

Features

• Code Review: Automated PR review with actionable feedback
• Security Analysis: Identify security vulnerabilities in code
• Improvement Suggestions: Get code quality improvement recommendations
• MCP Compatible: Works with any MCP client (Claude, Cursor, etc.)

Installation

npm install -g code-review-mcp

Setup

1. Set your OpenAI API key:

export OPENAI_API_KEY="your-api-key-here"

2. Configure in your MCP client:

Claude Desktop

Add to claude_desktop_config.json:

{
  "mcpServers": {
    "code-review": {
      "command": "node",
      "args": ["/path/to/code-review-mcp/index.js"],
      "env": {
        "OPENAI_API_KEY": "your-api-key-here"
      }
    }
  }
}

Cursor

Add to .cursor/mcp.json:

{
  "mcpServers": {
    "code-review": {
      "command": "node",
      "args": ["/path/to/code-review-mcp/index.js"],
      "env": {
        "OPENAI_API_KEY": "your-api-key-here"
      }
    }
  }
}

Available Tools

1. review_code

Review code changes and provide feedback.

Parameters:

• diff (required): The code diff to review
• context (optional): Additional context about the changes

Example:

{
  "diff": "--- a/file.js\n+++ b/file.js\n@@ -1,3 +1,5 @@\n+// New function\n+function add(a, b) {\n+  return a + b;\n+}",
  "context": "Added new utility function for arithmetic operations"
}

2. analyze_security

Analyze code for security vulnerabilities.

Parameters:

• code (required): The code to analyze
• language (optional): Programming language

Example:

{
  "code": "const query = `SELECT * FROM users WHERE id = ${userId}`;",
  "language": "javascript"
}

3. suggest_improvements

Suggest code quality improvements.

Parameters:

• code (required): The code to analyze
• focus (optional): Focus area (performance, readability, best_practices, all)

Example:

{
  "code": "function processData(data) { return data.filter(x => x).map(x => x * 2); }",
  "focus": "performance"
}

Usage with AI Agents

This MCP server can be used by AI agents to automatically review code:

// Example: AI agent using the MCP server
const review = await mcpClient.callTool({
  name: "review_code",
  arguments: {
    diff: prDiff,
    context: "Feature: user authentication"
  }
});

console.log(review.content[0].text);

Enterprise Features

For enterprise use cases, contact us for:

• Custom review rules and guidelines
• Integration with CI/CD pipelines
• Team-specific coding standards
• Priority support
• On-premise deployment

License

MIT

Author

ContentForge Press

Support

• GitHub Issues: https://github.com/contentforge-press/code-review-mcp/issues
• Email: [email protected]

CLI mode (CI-friendly)

Run a one-shot review without an MCP client:

# Review a diff file
reviewpilot-mcp --review pr.diff

# With context
reviewpilot-mcp --review pr.diff --context "PR #123: auth feature"

# Security scan a source file
reviewpilot-mcp --security src/app.js --language javascript

GitHub Actions automatic PR review

Copy examples/github-action/reviewpilot.yml to .github/workflows/. Every PR gets an automated review comment.

Configuration

| Variable | Required | Default | Purpose | |----------|----------|---------|---------| | OPENAI_API_KEY | yes | — | API key | | OPENAI_BASE_URL | no | OpenAI | Any OpenAI-compatible endpoint (gateways, local servers) | | REVIEW_MODEL | no | gpt-4o-mini | Model used for review |

Use a local or cheaper model by pointing OPENAI_BASE_URL and REVIEW_MODEL at an OpenAI-compatible server.