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Code Review Analyst MCP
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Code Review Analyst MCP

An MCP server based on Gemini, providing code review, analysis, documentation generation, and logic verification functions, supporting 13 tools such as PR review, code smell detection, and complexity analysis.
Developer toolsArtificial intelligence chatbots#Code Review#AI Analysis#Documentation Generation#Logic Verification.TypeScript
2 points
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Overview

Installation

Content Details

Alternatives

What is Code Lens?

Code Lens is an intelligent code analysis server based on the Model Context Protocol (MCP). It leverages the powerful AI capabilities of Google Gemini to provide developers with automated code review, analysis, and documentation generation services. Whether you're reviewing a Pull Request, refactoring code, or need to understand complex code logic, Code Lens can provide professional analysis and suggestions.

How to use Code Lens?

Using Code Lens is very simple: First, configure the MCP server in your favorite development tool (such as VS Code, Cursor, etc.), and then call the various tools provided by Code Lens through the AI assistant. You can ask it to analyze code changes, detect potential issues, generate test plans, or directly ask any questions about the code.

Use Cases

Code Lens is particularly suitable for the following scenarios: 1. Code Review: Automatically analyze Pull Requests, identify risks, and provide merge suggestions. 2. Code Refactoring: Detect code smells and provide refactoring suggestions. 3. Documentation Generation: Automatically generate detailed documentation comments for code. 4. Logic Verification: Verify the correctness of algorithm logic. 5. Performance Analysis: Evaluate the time and space complexity of code.

Main Features

Intelligent PR Review
Automatically analyze code changes, evaluate the impact, detect API breaking changes, and provide a detailed review summary and merge suggestions.
In-depth Code Analysis
Conduct in-depth analysis of a single source code file, providing refactoring suggestions, code smell detection, documentation generation, and natural language Q&A capabilities.
Logic Verification
Use Gemini's code execution sandbox to verify the correctness of algorithm logic and ensure that the code works as expected.
Structured Output
All analysis results are returned in a standardized JSON format, facilitating programmatic processing and integration into other tools.
Internet Search
Integrate Google search functionality to obtain the latest technical documentation and API reference information.
Task Lifecycle Support
Support long-running tasks, providing progress updates, cancellation functionality, and result caching mechanisms.
Advantages
๐Ÿค– Intelligent Analysis: Based on the powerful AI capabilities of Google Gemini, providing professional code analysis
๐Ÿ”„ Automated Process: Automate the complete PR review process, saving manual review time
๐Ÿ“Š Structured Output: All results are in standard JSON format, facilitating integration and processing
๐Ÿ” In-depth Analysis: Support multiple dimensions from code smell detection to performance analysis
๐ŸŒ Internet Connectivity: Access the latest technical information and documentation
โšก Fast Response: Use the Gemini Flash model for fast analysis
Limitations
๐Ÿ”‘ API Key Required: You must configure a Google Gemini API key to use it
๐Ÿ“ Git Dependency: Code change analysis requires a Git environment
๐Ÿ’พ Memory Limitation: Analysis of large files or complex code may be limited by the model's context length
๐ŸŒ Network Dependency: A stable network connection is required to access the Gemini API
๐ŸŽฏ Specific Scenarios: Mainly focused on code analysis, not suitable for general text processing

How to Use

Get an API Key
Visit Google AI Studio to obtain a Gemini API key. This is a prerequisite for using Code Lens.
Configure Your Development Tool
Configure the MCP server in the development tool you are using. Here is an example of configuring VS Code:
Start Using
Call the tools provided by Code Lens in the AI assistant, such as analyzing code changes or reviewing a Pull Request.

Usage Examples

Pull Request Review
When a team member submits a Pull Request, use Code Lens to automatically review the changes, evaluate the risks, and provide merge suggestions.
Code Refactoring Assistance
When refactoring complex code, use Code Lens to identify code smells and provide refactoring suggestions.
Algorithm Logic Verification
When implementing complex algorithms, verify the correctness and performance of the logic.
Technical Research
When you need to learn about new technologies or APIs during development, use the internet search function.

Frequently Asked Questions

Is Code Lens free?
Which programming languages are supported?
Are the analysis results accurate?
How to handle large codebases?
How is data privacy protected?
Is private deployment supported?

Related Resources

GitHub Repository
Source code and issue tracking for Code Lens
npm Package
npm package page for Code Lens
Model Context Protocol Official Website
Official documentation and specifications for the MCP protocol
Google AI Studio
Obtain Gemini API keys and model information
Docker Image
Docker container image for Code Lens
VS Code MCP Documentation
Official guide for configuring the MCP server in VS Code

Installation

Copy the following command to your Client for configuration
{
  "mcpServers": {
    "code-lens": {
      "command": "npx",
      "args": ["-y", "@j0hanz/code-lens-mcp@latest"],
      "env": {
        "GEMINI_API_KEY": "your-api-key"
      }
    }
  }
}

{
  "augment.advanced": {
    "mcpServers": [
      {
        "id": "code-lens",
        "command": "npx",
        "args": ["-y", "@j0hanz/code-lens-mcp@latest"],
        "env": {
          "GEMINI_API_KEY": "your-api-key"
        }
      }
    ]
  }
}
Note: Your key is sensitive information, do not share it with anyone.

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