经 AI Skill Hub 精选评估,代码健康分析 获评「推荐使用」。这款MCP工具在功能完整性、社区活跃度和易用性方面表现出色,AI 评分 7.5 分,适合有一定技术背景的用户使用。
代码健康分析 是一款遵循 MCP(Model Context Protocol)标准协议的 AI 工具扩展。通过 MCP 协议,它可以让 Claude、Cursor 等主流 AI 客户端直接访问和操作外部工具、数据源和服务,实现 AI 能力的无缝扩展。无论是文件操作、数据库查询还是 API 调用,都可以通过自然语言在 AI 对话中直接触发,极大提升生产效率。
代码健康分析 是一款遵循 MCP(Model Context Protocol)标准协议的 AI 工具扩展。通过 MCP 协议,它可以让 Claude、Cursor 等主流 AI 客户端直接访问和操作外部工具、数据源和服务,实现 AI 能力的无缝扩展。无论是文件操作、数据库查询还是 API 调用,都可以通过自然语言在 AI 对话中直接触发,极大提升生产效率。
# 方式一:通过 Claude Code CLI 一键安装
claude skill install https://github.com/codescene-oss/codescene-mcp-server
# 方式二:手动配置 claude_desktop_config.json
{
"mcpServers": {
"------": {
"command": "npx",
"args": ["-y", "codescene-mcp-server"]
}
}
}
# 配置文件位置
# macOS: ~/Library/Application Support/Claude/claude_desktop_config.json
# Windows: %APPDATA%/Claude/claude_desktop_config.json
# 安装后在 Claude 对话中直接使用 # 示例: 用户: 请帮我用 代码健康分析 执行以下任务... Claude: [自动调用 代码健康分析 MCP 工具处理请求] # 查看可用工具列表 # 在 Claude 中输入:"列出所有可用的 MCP 工具"
// claude_desktop_config.json 配置示例
{
"mcpServers": {
"______": {
"command": "npx",
"args": ["-y", "codescene-mcp-server"],
"env": {
// "API_KEY": "your-api-key-here"
}
}
}
}
// 保存后重启 Claude Desktop 生效
The CodeScene MCP Server exposes CodeScene's Code Health analysis as local AI-friendly tools.
This server is designed to run in your local environment and lets AI assistants (like GitHub Copilot, Cursor, Claude code, etc.) request meaningful Code Health insights directly from your codebase. The Code Health insights augment the AI prompts with rich content around code quality issues, maintainability problems, and technical debt in general.
The repository also includes a downloadable set of public agent skills in skills/ for teams that want to reuse CodeScene MCP workflows in their own agentic pipelines.
Want AI to perform the setup? Start with skills/installing-and-activating-codescene-mcp/SKILL.md.
Choose the installation method that works best for your platform.
<details> <summary><b>NPM / npx (macOS, Linux, Windows)</b></summary>
Run the MCP server directly with npx (no install needed):
npx @codescene/codehealth-mcp
Or install globally:
npm install -g @codescene/codehealth-mcp
The first run automatically downloads the correct platform-specific binary for your system and caches it for future use. Requires Node.js 18 or later.
📖 Full installation & integration guide
</details>
<details> <summary><b>Claude Code</b></summary>
Add the CodeScene marketplace and install the plugin:
/plugin marketplace add codescene-oss/codescene-mcp-server
/plugin install codescene@codescene
This installs the MCP server and Code Health skills. Requires Node.js 18 or later.
</details>
<details> <summary><b>Claude Desktop</b></summary>
Download the MCP bundle from the latest release page:
codehealth-mcp-{version}.mcpbThen open the .mcpb file with Claude Desktop to install the MCP server.
</details>
<details> <summary><b>Homebrew (macOS / Linux)</b></summary>
brew tap codescene-oss/codescene-mcp-server https://github.com/codescene-oss/codescene-mcp-server
brew trust codescene-oss/codescene-mcp-server
brew install cs-mcp
📖 Full installation & integration guide
</details>
<details> <summary><b>Windows</b></summary>
Run this in PowerShell:
irm https://raw.githubusercontent.com/codescene-oss/codescene-mcp-server/main/install.ps1 | iex
📖 Full installation & integration guide
</details>
<details> <summary><b>Manual Download</b></summary>
Download the latest binary for your platform from the GitHub Releases page:
cs-mcp-macos-aarch64.zip (Apple Silicon) or cs-mcp-macos-amd64 (Intel)cs-mcp-linux-aarch64.zip or cs-mcp-linux-amd64cs-mcp-windows-amd64.exeAfter downloading, make it executable and optionally add it to your PATH:
chmod +x cs-mcp-*
mv cs-mcp-* /usr/local/bin/cs-mcp
You can also build a static executable from source.
</details>
<details> <summary><b>Docker</b></summary>
docker pull codescene/codescene-mcp
📖 Full installation & integration guide | Build the Docker image locally
</details>
---
The MCP server is written in Rust. To build from source:
cargo build --release
The binary is produced at target/release/cs-mcp.
For more details, see:
[!TIP] Watch the demo video of the CodeScene MCP.
[!NOTE] CodeScene MCP comes with a set of example prompts, agent guidance files to capture the key use cases, and a downloadable set of public skills. Copy the agent guidance that matches your license — AGENTS-full.md for CodeScene Core users or AGENTS-standalone.md for standalone users — and any relevant skills to your own repository.
With the CodeScene MCP Server in place, your AI tools can:
<details>
<summary>Do I need a CodeScene account to use the MCP?</summary>
The full feature set — including hotspots, technical debt goals, and code ownership — requires a CodeScene subscription. Use your CodeScene instance to create the CS_ACCESS_TOKEN which activates the MCP. The MCP supports both CodeScene Cloud and CodeScene on-prem.
For local Code Health analysis without a CodeScene subscription, you can use the standalone CodeScene Code Health MCP.
</details>
<details>
<summary>How does the MCP Server keep my code private and secure?</summary>
The CodeScene MCP Server runs fully locally. All analysis — including Code Health scoring, delta reviews, and business-case calculations — is performed on your machine, against your local repository. No source code or analysis data is sent to cloud providers, LLM vendors, or any external service.
Analysis results (e.g. hotspots and technical debt goals) are fetched via REST from your own CodeScene account using a secure token.
For complete details, please see CodeScene's full privacy and security documentation.
</details>
<details>
<summary>Can I use any LLM as the backbone for CodeScene MCP?</summary>
CodeScene MCP can work with any model your AI assistant supports, but we strongly recommend choosing a frontier model when your assistant offers a model selector (as in tools like GitHub Copilot).
Frontier models -- such as Claude Sonnet -- deliver far better rule adherence and refactoring quality, while legacy models like GPT-4.1 often struggle with MCP constraints. For a consistent, high-quality experience, select the newest available model.
</details>
<details>
<summary>I have multiple repos — how do I configure the MCP?</summary>
Since you have to provide a mount path for Docker, you can either have a MCP configuration per project (in VS Code that would be a .vscode/mcp.json file per project, for example) or you can mount a root directory within which all your projects are and then just use that one configuration instead.
</details>
<details>
<summary>Why does IntelliJ give a wrong path to the MCP server?</summary>
In our testing we've seen that IntelliJ's AI Assistant sometimes gives a wrong path to the CodeScene MCP server. From what we can tell, it seems to have nothing to do with the MCP server itself, but rather with IntelliJ's AI Assistant, which seems to hallucinate parts of the path some of the time. We're still investigating this issue and will update this section once we have more information.
</details>
<details>
<summary>How do I configure custom SSL certificates?</summary>
If your organization uses an internal CA (Certificate Authority), set the REQUESTS_CA_BUNDLE environment variable to point to your CA certificate file (PEM format). The MCP server automatically configures SSL — you only need to set it once.
The MCP also supports SSL_CERT_FILE and CURL_CA_BUNDLE as alternatives.
For detailed configuration examples (including Docker certificate mounting), see Configuration Options — SSL/TLS.
</details>
<details>
<summary>How do I disable the version update check?</summary>
The MCP server periodically checks GitHub for newer releases and shows a "VERSION UPDATE AVAILABLE" banner when your version is outdated. This check runs in the background and never blocks tool responses, but in network-restricted environments you may want to disable it entirely.
Set the CS_DISABLE_VERSION_CHECK environment variable to any non-empty value (e.g. 1). For setup details, see Configuration Options — Version Check.
</details>
该工具使用 NOASSERTION 协议,商用场景请仔细阅读协议条款,必要时咨询法律意见。
AI Skill Hub 为第三方内容聚合平台,本页面信息基于公开数据整理,不对工具功能和质量作任何法律背书。
建议在沙箱或测试环境中充分验证后,再部署至生产环境,并做好必要的安全评估。
📄 NOASSERTION — 请查阅原始协议条款了解具体使用限制。
AI Skill Hub 点评:代码健康分析 的核心功能完整,质量良好。对于Claude Desktop / Claude Code 用户来说,这是一个值得纳入个人工具库的选择。建议先在非生产环境试用,再逐步推广。
| 原始名称 | codescene-mcp-server |
| 原始描述 | 开源MCP工具:The CodeScene MCP Server exposes CodeScene’s Code Health analysis as local AI-fr。⭐49 · Rust |
| Topics | 代码分析AIRust |
| GitHub | https://github.com/codescene-oss/codescene-mcp-server |
| License | NOASSERTION |
| 语言 | Rust |
收录时间:2026-06-10 · 更新时间:2026-06-10 · License:NOASSERTION · AI Skill Hub 不对第三方内容的准确性作法律背书。
选择 Agent 类型,复制安装指令后粘贴到对应客户端