git-reviewer
Enables AI assistants to fetch GitHub pull request diffs and metadata, and post review comments directly through the MCP protocol.
README
🤖 Git-Reviewer MCP Server
Stop manually copying and pasting massive code diffs into your AI chat window.
Git-Reviewer is a lightweight, secure Model Context Protocol (MCP) server that connects LLM assistants (like Claude Desktop, Cursor, and Windsurf) directly to the GitHub API. It enables your AI to fetch pull request metadata and raw diff files autonomously, producing fast, context-aware, and highly accurate code reviews directly within your development workspace.
⚡ The Context Switching Problem (Solved)
flowchart LR
DEV[Developer] -->|Ask for PR review| AI[AI Assistant]
AI -->|MCP JSON-RPC| SERVER[Git-Reviewer MCP Server]
SERVER --> META[fetch_pr_metadata]
SERVER --> DIFF[fetch_pr_diff]
META -->|Authorized API call| GITHUB[GitHub REST API]
DIFF -->|Authorized API call| GITHUB
GITHUB --> DATA[PR title, author, state, description, and raw diff]
DATA --> SERVER
SERVER -->|Structured review context| AI
AI -->|Actionable review findings| DEV
AI -. Optional: publish line comment .-> COMMENT[post_pr_review_comment]
COMMENT -.-> GITHUB
Instead of manually navigating tabs, copying hundreds of lines of diff code, and hitting token limits, you can now simply type:
"Analyze the code changes in react/react PR #36818 and check for architectural issues."
Your assistant will query the server, read the raw diff, and deliver a structured code review instantly.
✨ Features
- 💨 High-Fidelity Diffs (
fetch_pr_diff): Fetches raw, line-by-line.diffcode changes, optimized for LLM comprehension. - 📋 Rich Context (
fetch_pr_metadata): Retrieves PR Title, Author, Description, and State to give the AI crucial background. - ✍️ Active Review Comments (
post_pr_review_comment): Allows the AI to write line-level feedback directly onto the PR from the chat interface. (Automatically resolves head commit SHA if omitted). - 🛡️ Secure Token Storage: Uses standard local
.envconfiguration. Your GitHub Personal Access Token is never committed or shared.
🚀 Installation & Local Setup
1. Clone & Initialize Environment
Set up a clean Python environment:
# Clone the repository
git clone https://github.com/Suchit-007/git-reviewer.git
cd git-reviewer
# Create and activate virtual environment
python -m venv .venv
# On Windows:
.venv\Scripts\activate
# On macOS/Linux:
source .venv/bin/activate
# Install required packages
pip install -r requirements.txt
2. Configure Environment Variables
Create a .env file in the root folder (or copy .env.example):
GITHUB_TOKEN=your_personal_access_token_here
Note: Using a token avoids GitHub API rate limiting on public repositories and enables reading from private repositories.
⚙️ IDE Integration
Claude Desktop
Add the configuration to your claude_desktop_config.json file:
- Windows:
%APPDATA%\Claude\claude_desktop_config.json - macOS:
~/Library/Application Support/Claude/claude_desktop_config.json
{
"mcpServers": {
"git-reviewer": {
"command": "python",
"args": [
"C:\\absolute\\path\\to\\git-reviewer\\src\\server.py"
],
"env": {
"GITHUB_TOKEN": "your_github_token_here"
}
}
}
}
Cursor
- Go to Settings -> Features -> MCP.
- Click + Add New MCP Server.
- Configure:
- Name:
git-reviewer - Type:
command - Command:
python C:\absolute\path\to\git-reviewer\src\server.py
- Name:
- Click Save.
🧪 Development & Testing
You can test the server locally using the MCP Inspector tool:
# Activate virtual environment
.venv\Scripts\activate
# Run the inspector
fastmcp dev inspector src/server.py
This opens a local developer interface at http://localhost:6274 to test the tools interactively.
📄 License
This project is open-source and licensed under the MIT License.
推荐服务器
Baidu Map
百度地图核心API现已全面兼容MCP协议,是国内首家兼容MCP协议的地图服务商。
Playwright MCP Server
一个模型上下文协议服务器,它使大型语言模型能够通过结构化的可访问性快照与网页进行交互,而无需视觉模型或屏幕截图。
Magic Component Platform (MCP)
一个由人工智能驱动的工具,可以从自然语言描述生成现代化的用户界面组件,并与流行的集成开发环境(IDE)集成,从而简化用户界面开发流程。
Audiense Insights MCP Server
通过模型上下文协议启用与 Audiense Insights 账户的交互,从而促进营销洞察和受众数据的提取和分析,包括人口统计信息、行为和影响者互动。
VeyraX
一个单一的 MCP 工具,连接你所有喜爱的工具:Gmail、日历以及其他 40 多个工具。
graphlit-mcp-server
模型上下文协议 (MCP) 服务器实现了 MCP 客户端与 Graphlit 服务之间的集成。 除了网络爬取之外,还可以将任何内容(从 Slack 到 Gmail 再到播客订阅源)导入到 Graphlit 项目中,然后从 MCP 客户端检索相关内容。
Kagi MCP Server
一个 MCP 服务器,集成了 Kagi 搜索功能和 Claude AI,使 Claude 能够在回答需要最新信息的问题时执行实时网络搜索。
e2b-mcp-server
使用 MCP 通过 e2b 运行代码。
Neon MCP Server
用于与 Neon 管理 API 和数据库交互的 MCP 服务器
Exa MCP Server
模型上下文协议(MCP)服务器允许像 Claude 这样的 AI 助手使用 Exa AI 搜索 API 进行网络搜索。这种设置允许 AI 模型以安全和受控的方式获取实时的网络信息。