A Model Context Protocol server for deep codebase understanding of Python projects, focusing on data analysis and scientific computing. It provides architectural analysis, pattern detection, dependency mapping, test coverage analysis, and AI-optimized context generation.
A Model Context Protocol server that analyzes application codebases with real-time file watching, providing AI assistants like Claude with deep insights into project structure, code patterns, and architecture.
A Model Context Protocol server that extracts and analyzes Python code structures, focusing on import/export relationships between files to help LLMs understand code context.
A local, read-only MCP server that analyzes Python backend projects by providing tools to scan, map, and selectively read files, reducing token usage for AI clients.
A Model Context Protocol server that enables AI assistants like Claude to perform Python development tasks through file operations, code analysis, project management, and safe code execution.
A Model Context Protocol (MCP) server that enables AI applications to access and analyze local code repositories without manual uploads, providing file listing, content reading, code searching, and project structure analysis capabilities.
