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Codescene MCP Server

@codescene-oss

代码仓库

基本信息

分类

其他

传输方式

stdio

作者

codescene-oss

提交者

Asko Nõmm

关于 Codescene MCP Server

The CodeScene MCP Server exposes CodeScene’s Code Health analysis as local AI-friendly tools.

#codescene#code-health#ai-tools

Codescene MCP Server 配置

使用下面的配置,将此服务器添加到你的 MCP 客户端。

{
  "mcpServers": {
    "codescene": {
      "command": "docker",
      "args": [
        "run",
        "-i",
        "--rm",
        "-e",
        "CS_ACCESS_TOKEN",
        "codescene/codescene-mcp"
      ],
      "env": {
        "CS_ACCESS_TOKEN": "<YOUR_TOKEN>"
      }
    }
  }
}

Codescene MCP Server 工具

工具列表暂未提供

当前收录暂时没有可展示的工具列表，不代表服务没有工具。请查阅项目文档了解支持的能力。

工具是从 README 中自动提取的。维护者可以在 ## Tools 标题下列出工具,即可填充这部分内容。

概览

What is Codescene?

The Codescene MCP Server exposes CodeScene’s Code Health analysis as local AI-friendly tools. It runs in your local environment and lets AI assistants (such as GitHub Copilot, Cursor, and Claude code) request code health insights directly from your codebase, augmenting prompts with information about code quality, maintainability, and technical debt.

How to use Codescene?

Run the server via Docker with environment variables for your CodeScene access token and the path to your code. Configure it for your AI assistant (Claude Code, Codex CLI, GitHub Copilot, Kiro, VS Code, or Amazon Q CLI) using the provided setup instructions for either CodeScene Cloud or CodeScene On-prem.

Key features of Codescene

  • Exposes CodeScene’s Code Health analysis as local AI tools.
  • Runs in your local environment without external data transfer.
  • Supports both CodeScene Cloud and CodeScene On-prem.
  • Works with multiple AI assistants (Claude Code, Copilot, etc.).
  • Requires only Docker and an access token to configure.

Use cases of Codescene

  • AI assistants can request code quality,

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