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Analyze local codebases for technical debt and code health, then use findings to prioritize refactoring, justify changes to stakeholders, identify high-risk test targets, route work to domain experts, and gate AI-generated code changes before commit or pull request.
npx claudepluginhub codescene-oss/codescene-mcp-server --plugin codesceneUse when the user wants to view, set, or troubleshoot CodeScene MCP configuration such as access tokens, on-prem URLs, ACE tokens, default projects, or SSL certificates.
Use when a user asks what Code Health means, how to interpret scores, or why Code Health matters in daily development.
Use when refactoring unhealthy code and needing Code Health findings to choose small safe steps and verify improvement.
Use when installing the CodeScene MCP Server binary or package, registering it in an AI assistant, or copying agent guidance files into a repository.
Use when a user asks for ROI, stakeholder justification, delivery impact, or defect-risk reduction from improving Code Health in a file.
Share bugs, ideas, or general feedback.
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Live codebase visualization and structural quality gate โ 14 health dimensions graded A-F, dependency analysis, and architecture governance via MCP
Analyze local repos for code health, complexity, test coverage gaps - multi-dimensional health analysis combining complexity + churn + coverage
DevOps patterns: CI debugging, tech debt detection, own all failures
Structured codebase health attributes with severity-based agent routing
Codebase exploration, refactoring, and quality analysis
AI-powered codebase modernization assessment - Interactive audit and quick scan skills to identify technical debt, anti-patterns, and quality issues from older AI-generated code
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.
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.
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.
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.
brew tap codescene-oss/codescene-mcp-server https://github.com/codescene-oss/codescene-mcp-server
brew install cs-mcp
Run this in PowerShell:
irm https://raw.githubusercontent.com/codescene-oss/codescene-mcp-server/main/install.ps1 | iex
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.
docker pull codescene/codescene-mcp
๐ Full installation & integration guide | Build the Docker image locally
[!TIP] Watch the demo video of the CodeScene MCP.