Which integrations are available for this server?

Automated AI code review on GitHub pull requests, with line-level comments and suggestions. Triggers automated code reviews via GitHub Actions workflow when a pull request is created.

How do I use MCP-CodeReviewer?

1. Click on "Install Server". 2. Wait a few minutes for the server to deploy. Once ready, it will show a "Started" state. 3. In the chat, type @ followed by the MCP server name and your instructions, e.g., "@MCP-CodeReviewer review PR #12 for security and style issues" That's it! The server will respond to your query, and you can continue using it as needed. Here is a step-by-step guide with screenshots.

🔍 MCP-CodeReviewer

基于 MCP 协议的三层漏斗式 AI 代码审查引擎 通过确定性静态分析与动态模型路由，在保证审查深度的同时降低 70%+ 的 LLM Token 消耗。

Python 3.11+ MCP Protocol License: MIT

🏗️ 架构

PR 触发 → GitHub Actions
  → git diff (宿主机) → Docker 容器
    → ci_runner.py
      → 白名单代码提取 + 正则函数提取
      → RAG 规范检索 (独立降级)
      → 影响面雷达 ripgrep (独立降级)
      → Phase3 Prompt 拼装
      → LLM 审查 (deepseek-v4-flash)
      → 三级防御 L1/L2/L3 → GitHub 行级评论 (含 Suggestion)
      → ReviewMetrics 落盘 → upload-artifact

Related MCP server: open-code-review

🚀 快速开始

1. 安装

git clone <repo-url>
cd mcp-code-reviewer
pip install -r requirements.txt

2. Mock 模式（无需 API Key）

python orchestrator.py --mock

3. 真实审查

export DEEPSEEK_API_KEY=***
python orchestrator.py

4. 接入 GitHub PR

# 复制 workflow 到目标仓库
cp .github/workflows/ai-review.yml <target-repo>/.github/workflows/

# 配置 Secrets: DEEPSEEK_API_KEY
# 配置 Actions 权限: Read and write
# 创建 PR，自动触发审查

详见 DEPLOYMENT_GUIDE.md

📁 项目结构

├── mcp_server.py          # MCP Server (3 Tools)
├── orchestrator.py        # MCP Client + Prompt 工程
├── ci_runner.py           # CI/CD 桥梁 + 三级防御
├── rag_engine.py          # 轻量 RAG (SQLite)
├── impact_analyzer.py     # 影响面雷达 (ripgrep)
├── metrics.py             # ReviewMetrics 黑匣子
├── Dockerfile             # 生产级镜像
├── scripts/
│   └── aggregate_metrics.py  # Metrics 聚合分析
└── test_cases/            # 测试用例

🛡️ 三级防御

级别	方法	防护目标
L1	unidiff 行号映射 O(1) 精确匹配	防 LLM 幻觉原代码
L2	物理字符串切片提取缩进	防正则跨行漏洞
L3	AST 宽容预检 + 补 pass	防破坏性提交

校验失败不丢弃 issue → 降级为纯文本警告评论。

🧪 测试

python test_static_analysis.py     # 15 用例 ✅
python test_complexity_router.py   # 9 用例 ✅
python eval_quality.py             # LLM 质量评估 (30 bugs)

📊 可观测性

每次审查自动生成 review_metrics.json，包含 30+ 指标：

管线各阶段耗时 (RAG/雷达/LLM)
三级防御 L1/L2/L3 通过/失败计数
Suggestion 成功率
RAG 降级率

# 本地聚合分析
python scripts/aggregate_metrics.py ./downloaded_metrics/

🔧 技术栈

组件	技术
MCP Server	Python + mcp SDK + FastAPI
静态分析	ast.NodeVisitor
Diff 解析	unidiff
影响面分析	ripgrep
RAG	SQLite + numpy
LLM Gateway	litellm
容器化	Docker (python:3.11-slim)
CI/CD	GitHub Actions

📝 技术债

见 TECH_DEBT.md

License

MIT

This server cannot be installed

F

license - not found

-

quality - not tested

-

maintenance - not tested

How are these scores calculated?

Resources

GitHub Repository

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