In short: The CodeHealth MCP Server guides AI coding assistants using deterministic CodeHealth™ metrics so they can generate healthier code, refactor safely, and prevent technical debt.
The MCP Server connects AI tools to CodeScene’s CodeHealth™ analysis, allowing them to improve code based on objective signals about maintainability and change risk.
With the MCP Server, teams can safeguard AI-generated code, guide AI assistants toward meaningful refactoring based on objective feedback, simplify code reviews by enforcing maintainability standards, and build a business case for refactoring using built-in ROI calculations that translate code health improvements into measurable business outcomes.
Yes, the MCP server is designed to run in your local environment.
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.
Yes. The CodeHealth™ MCP Server works with any AI coding assistant, including IDE-native tools such as GitHub Copilot, Cursor, and Windsurf, as well as agents like Claude.
Because it follows the Model Context Protocol (MCP) standard, it is compatible with any LLM, model, or agentic workflow that supports MCP. This allows teams to integrate CodeHealth™ insights into their preferred AI development setup without being tied to a specific editor, agent, or model.
Yes, The CodeHealth MCP server is designed for agentic workflows and composable AI tooling, not tied to any single editor, assistant or model.
The paid plan costs €8 or $9 per month. Customers in the United States are billed in USD, while customers in all other regions are billed in EUR. A 10% discount is available with annual billing.
Yes. You can cancel your CodeHealth MCP Server subscription at any time. Your access will remain active until the end of the current billing period.
Getting started with the CodeHealth MCP Server is straightforward:
Set your token as the CS_ACCESS_TOKEN environment variable. This allows the MCP Server to access CodeHealth analysis.
Install the MCP Server as an executable (via Homebrew for Mac/Linux, Windows installer, or manual download) or run it using Docker.
Connect the MCP Server to your AI assistant by following the setup instructions for your environment.
Add the AGENTS.md file to your repository. This file defines how AI agents should use the MCP tools and enforces safeguards for AI-assisted coding.
