Codescene
What is CodeScene MCP Server?
CodeScene MCP Server exposes CodeScene’s Code Health analysis as local AI-friendly tools, allowing AI assistants to request insights directly from your codebase.
How to use CodeScene MCP Server?
To use the CodeScene MCP Server, set up your environment with the necessary access tokens and mount paths, then run the server using Docker commands provided in the documentation.
Key features of CodeScene MCP Server?
- Provides Code Health insights to AI tools.
- Supports both Cloud and On-prem configurations.
- Allows integration with various AI coding assistants like GitHub Copilot.
Use cases of CodeScene MCP Server?
- Safeguarding AI-generated code by flagging maintainability issues.
- Guiding targeted refactoring by providing insights into design problems.
- Enhancing AI-driven summaries and diagnostics based on real-world code challenges.
FAQ from CodeScene MCP Server?
-
How do I configure the MCP for multiple repos? You can have a separate MCP configuration per project or mount a root directory for all projects.
-
Why do we mount a directory in Docker? To avoid token limit issues and ensure safe access to files, we read from a mounted directory instead of passing file contents directly.
-
What is
CS_MOUNT_PATH? It is the absolute path to the directory whose code you want to analyze with CodeScene.
Server Config
{
"mcpServers": {
"codescene": {
"command": "docker",
"args": [
"run",
"-i",
"--rm",
"-e",
"CS_ACCESS_TOKEN",
"codescene/codescene-mcp"
],
"env": {
"CS_ACCESS_TOKEN": "<YOUR_TOKEN>"
}
}
}
}Recommend Servers
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