How does CodeHealth MCP keep my code private?

All analysis runs locally on your machine. No source code or analysis data is sent to cloud services, LLM providers, or external servers. Only code health results are fetched from your CodeScene account via a secure token.

Which AI assistants does CodeHealth MCP support?

It supports any MCP-compatible AI assistant, including Claude Code, GitHub Copilot (via VS Code), and others. Integration guides are provided for popular setups.

Do I need a CodeScene license to use the MCP server?

Yes, a CodeScene account and an access token are required. The server can be used in standalone mode with limited features, but a CodeScene ACE license unlocks full functionality such as multi-language analysis and business-case reports.

What programming languages are supported?

CodeScene supports a wide range of languages including JavaScript, TypeScript, Python, Java, C#, Go, Rust, and many more. The MCP server inherits this language support.

Can I use any LLM with CodeHealth MCP?

As long as the LLM is accessible through an MCP-compatible interface, you can use it. The server is designed to be LLM-agnostic, but works best with assistants that support tool integration like Claude or Copilot.

CodeHealth MCP Server by CodeScene

Keep AI-generated code healthy and maintainable

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CodeHealth MCP Server by CodeScene preview

What is CodeHealth MCP Server by CodeScene

CodeHealth MCP Server by CodeScene is a local tool that integrates with AI coding assistants to ensure generated code is maintainable and production-ready. It provides deterministic CodeHealth feedback, flagging risks such as complexity and technical debt, and guides AI agents to refactor toward clear quality targets. Running entirely on your machine, it keeps your code private while making legacy systems more AI-friendly.

Key Features

Local execution: all analysis performed on your machine, no code sent to cloud

Deterministic code health scoring and delta reviews

Seamless integration with AI assistants like Claude Code, GitHub Copilot, and VS Code via MCP protocol

Multi-language support and business-case calculations for refactoring

Agent guidance files and example prompts for common use cases

Use Cases

Developers using AI coding assistants to ensure generated code avoids technical debt and remains maintainable
Engineering managers aiming to reduce code complexity and measure technical debt in their codebase
Teams refactoring legacy systems with AI help, using concrete health targets to guide improvements
AI tool vendors seeking to improve code generation quality by grounding their models in real code health data
Startups rapidly building AI features while maintaining code quality and avoiding future maintenance costs

Why do startups need this tool?

Startups rely on AI coding assistants to ship fast, but unchecked code generation can quickly accumulate technical debt. CodeHealth MCP Server provides immediate, deterministic feedback to keep codebase healthy, enabling rapid iteration without sacrificing maintainability. By running locally, it also ensures strict control over proprietary code—critical for startups with intellectual property concerns.