by praneybehl
Get structured & freeform code reviews with code quality analysis tools powered by OpenAI, Google & Anthropic. Supports
β 28
GitHub stars
Performs automated code reviews on git diffs using AI models from OpenAI, Google, and Anthropic. Analyzes staged changes, branch differences, or changes from HEAD with project context.
Claude Code Review is a community-built MCP server published by praneybehl that provides AI assistants with tools and capabilities via the Model Context Protocol. Get structured & freeform code reviews with code quality analysis tools powered by OpenAI, Google & Anthropic. Supports It is categorized under ai ml, developer tools.
You can install Claude Code Review in your AI client of choice. Use the install panel on this page to get one-click setup for Cursor, Claude Desktop, VS Code, and other MCP-compatible clients. This server runs locally on your machine via the stdio transport.
MIT
Claude Code Review is released under the MIT license. This is a permissive open-source license, meaning you can freely use, modify, and distribute the software.
Add new capabilities to Claude beyond text generation
Example
Access external data sources, execute code, interact with tools and services
Transform Claude from chatbot to action-taking agent
Provide Claude with access to relevant context and data
Example
Load project documentation, access knowledge bases, query databases
Get more accurate, context-aware responses
Automate multi-step workflows combining AI and external tools
Example
Research β Summarize β Create document β Send notification
Complete complex tasks end-to-end without manual steps
Share your MCP server with the developer community
Claude Code Review reduced integration guesswork β categories and install configs on the listing matched the upstream repo.
Claude Code Review has been reliable for tool-calling workflows; the MCP profile page is a good permalink for internal docs.
Claude Code Review has been reliable for tool-calling workflows; the MCP profile page is a good permalink for internal docs.
Claude Code Review reduced integration guesswork β categories and install configs on the listing matched the upstream repo.
Claude Code Review is a well-scoped MCP server in the explainx.ai directory β install snippets and categories matched our Claude Code setup.
We wired Claude Code Review into a staging workspace; the listingβs GitHub and npm pointers saved time versus hunting across READMEs.
Claude Code Review is among the better-indexed MCP projects we tried; the explainx.ai summary tracks the official description.
We evaluated Claude Code Review against two servers with overlapping tools; this profile had the clearer scope statement.
Claude Code Review reduced integration guesswork β categories and install configs on the listing matched the upstream repo.
Useful MCP listing: Claude Code Review is the kind of server we cite when onboarding engineers to host + tool permissions.
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Version: 1.0.0
An MCP (Model Context Protocol) server that provides a powerful tool to perform code reviews using various Large Language Models (LLMs). This server is designed to be seamlessly integrated with AI coding assistants like Anthropic's Claude Code, Cursor, Windsurf, or other MCP-compatible clients.
Note: This tool was initially created for Claude Code but has since been expanded to support other AI IDEs and Claude Desktop. See the integration guides for Claude Code, Cursor, and Windsurf.
It analyzes git diff output for staged changes, differences from HEAD, or differences between branches, providing contextualized reviews based on your task description and project details.
npx for immediate use.git commands.GOOGLE_API_KEY for Google models.OPENAI_API_KEY for OpenAI models.ANTHROPIC_API_KEY for Anthropic models.
These can be set globally in your environment or, conveniently, in a .env file placed in the root of the project you are currently reviewing. The server will automatically try to load it.The primary way to use this server is with npx, which ensures you're always using the latest version without needing a global installation.
npxNavigate to Your Project: Open your terminal and change to the root directory of the Git repository you want to review.
cd /path/to/your-git-project
Run the MCP Server: Execute the following command:
npx -y @vibesnipe/code-review-mcp
This command will download (if not already cached) and run the @vibesnipe/code-review-mcp server. You should see output in your terminal similar to:
[MCP Server] Code Reviewer MCP Server is running via stdio and connected to transport.
The server is now running and waiting for an MCP client (like Claude Code, Cursor, or Windsurf) to connect.
To install code-review-mcp for Claude Desktop automatically via Smithery:
npx -y @smithery/cli install @praneybehl/code-review-mcp --client claude
Once the claude-code-review-mcp server is running (ideally via npx from your project's root):
Add as an MCP Server in Claude Code:
In a separate terminal where Claude Code is running (or will be run), configure it to use this MCP server.
The command to run the server (as used by Claude Code) would be code-review-mcp if installed globally and in PATH, or the npx ... command if you prefer Claude Code to always fetch it.
To add it to Claude Code:
claude mcp add code-reviewer -s <user|local> -e GOOGLE_API_KEY="key" -- code-review-mcp
If you want Claude Code to use npx (which is a good practice to ensure version consistency if you don't install globally):
claude mcp add code-reviewer -s <user|local> -e GOOGLE_API_KEY="key" -- npx -y @vibesnipe/code-review-mcp
This tells Claude Code how to launch the MCP server when the "code-reviewer" toolset is requested. This configuration can be project-specific (saved in .claude/.mcp.json in your project) or user-specific (global Claude Code settings).
Use Smart Slash Commands in Claude Code:
Create custom slash command files in your project's .claude/commands/ directory to easily invoke the review tool. The package includes several example commands in the examples/claude-commands/ directory that you can copy to your project.
These improved slash commands don't require you to manually specify task descriptions or project context - they leverage Claude Code's existing knowledge of your project and the current task you're working on.
Example invocation using a slash command in Claude Code:
claude > /project:review-staged-claude
No additional arguments needed! Claude will understand what you're currently working on and use that as context for the review.
For commands that require arguments (like review-branch-custom-gemini.md which uses a custom branch name), you can pass them directly after the command:
claude > /project:review-branch-custom-gemini main
This will pass "main" as the $ARGUMENTS_BASE_BRANCH parameter.
Cursor is a popular AI-powered IDE based on VS Code that supports MCP servers. Here's how to integrate the code review MCP server with Cursor:
Configure Cursor's Rules for Code Review:
Create or open the .cursor/rules/project.mdc file in your project and add the following section:
## Slash Commands
/review-staged: Use the perform_code_review tool from the code-reviewer MCP server to review staged changes. Use anthropic provider with claude-3-7-sonnet-20250219 model. Base the task description on our current conversation context and focus on code quality and best practices.
/review-head: Use the perform_code_review tool from the code-reviewer MCP server to review all uncommitted changes (HEAD). Use openai provider with o3 model. Base the task description on our current conversation context and focus on code quality and best practices.
/review-security: Use the perform_code_review tool from the code-reviewer MCP server to review staged changes. Use anthropic provider with claude-3-5-sonnet-20241022 model. Base the task description on our current conversation context and specifically focus on security vulnerabilities, input validation, and secure coding practices.
Add the MCP Server in Cursor:
"code-reviewer": {
"command": "npx",
"args": ["-y", "@vibesnipe/code-review-mcp"],
"env": {
"GOOGLE_API_KEY": "your-google-api-key",
"OPENAI_API_KEY": "your-openai-api-key",
"ANTHROPIC_API_KEY": "your-anthropic-api-key"
}
}
Using the Commands:
In Cursor's AI chat interface, you can now simply type:
/review-staged
And Cursor will use the claude-code-review-mcp server to perform a code review of your staged changes.
Windsurf (formerly Codeium) is another advanced AI IDE that supports custom workflows via slash commands. Here's how to integrate with Windsurf:
Configure the MCP Server in Windsurf:
"code-reviewer": {
"command": "npx",
"args": ["-y", "@vibesnipe/code-review-mcp"],
"env": {
"GOOGLE_API_KEY": "your-google-api-key",
"OPENAI_API_KEY": "your-openai-api-key",
"ANTHROPIC_API_KEY": "your-anthropic-api-key"
}
}
Create Workflows for Code Review:
Windsurf supports workflows that can be invoked via slash commands. Create a file in .windsurf/workflows/review-staged.md:
# Review Staged Changes
Perform a code review on the currently staged changes in the repository.
## Step 1
Use the perform_code_review tool from the code-reviewer MCP server with the following parameters:
{ "target": "staged", "llmProvider": "anthropic", "modelName": "claude-3-7-sonnet-20250219", "taskDescription": "The task I am currently working on in this codebase", "reviewFocus": "General code quality, security best practices, and performance considerations", "projectContext": "This project is being developed in Windsurf. Please review the code carefully for any issues." }
Similarly, create workflows for other review types as needed.
Using the Workflows:
In Windsurf's Cascade interface, you can invoke these workflows with:
/review-staged
Windsurf will then execute the workflow, which will use the claude-code-review-mcp server to perform the code review.
perform_code_reviewDescription: Performs a code review using a specified Large Language Model on git changes within the current Git repository. This tool must be run from the root directory of the repository being reviewed.
Input Schema (Parameters):
The tool expects parameters matching the CodeReviewToolParamsSchema:
target (enum: 'staged', 'HEAD', 'branch_diff'):
Specifies the set of changes to review.
'staged': Reviews only the changes currently staged for commit.'HEAD': Reviews uncommitted changes (both staged and unstaged) against the last commit.'branch_diff': ReviewsPrerequisites
Time Estimate
15-60 minutes depending on server complexity
Steps
Troubleshooting
β Do
β Don't
π‘ Pro Tips
Architecture
Model Context Protocol standardizes how AI hosts (Claude, Cursor) communicate with external tools and data sources through server implementations.
Protocols
Compatibility
β Use when
Use when you need Claude to access external data, execute actions, or integrate with tools. Best for extending AI capabilities beyond conversation.
β Avoid when
Avoid when native integrations exist (use official APIs directly), for real-time critical systems, or when security/compliance requires zero external dependencies.