A Model Context Protocol server that analyzes Python code for structure, complexity, and dependencies.
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The mcp-code-analyzer is a Model Context Protocol server designed to analyze Python codebases. It provides detailed insights into code structure, complexity metrics, and dependency relationships, enabling developers to understand and improve their code quality. Integrated with AI models like Claude, it facilitates automated code review and contextual understanding within development environments. This server supports real-time code analysis, making it a valuable tool for continuous integration and development workflows.
Use This MCP server To
Analyze Python code structure for better readability Measure code complexity to identify refactoring needs Detect and map dependencies in Python projects Integrate automated code review in CI pipelines Provide real-time code insights in IDEs Support AI-assisted debugging and code comprehension
README
mcp-code-analyzer FAQ
How do I install the mcp-code-analyzer server?
You can install it by cloning the GitHub repository and following the setup instructions in the README, which typically involve installing dependencies and running the server locally.
Can the mcp-code-analyzer work with other programming languages?
Currently, it is specialized for Python code analysis, but the architecture allows for future extensions to other languages.
How does the mcp-code-analyzer integrate with AI models?
It connects with AI models like Claude, OpenAI, and Gemini to provide contextual analysis and insights based on the Python code it processes.
Is the mcp-code-analyzer suitable for large codebases?
Yes, it is designed to handle complex Python projects, analyzing structure and dependencies efficiently.
Can I use the mcp-code-analyzer in continuous integration workflows?
Absolutely, it can be integrated into CI pipelines to automate code quality checks and reviews.
Does the mcp-code-analyzer provide real-time feedback?
Yes, when integrated with compatible MCP hosts, it can deliver real-time analysis and suggestions during development.
What kind of complexity metrics does the mcp-code-analyzer provide?
It typically includes metrics like cyclomatic complexity, code length, and nesting depth to help identify problematic code areas.
Is the mcp-code-analyzer open source?
Yes, it is available on GitHub for community use and contributions.