"Python code quality improvement and codebase diagram generation tools" matching MCP servers:

Provides deterministic Python code quality analysis using flake8, mypy, McCabe, and vulture, enabling LLMs to access real linting and type checking results.

Hybrid code quality analysis server combining fast logic-based checks with AI-powered deep analysis, offering tools for summaries, quick wins, and trend tracking.

Validates AI-generated Python: syntax, lint, security scan and deterministic repair.

Connects AI coding assistants to PyCharm's code quality inspections and optionally SonarQube for IDE, providing unified, de-duplicated code analysis results without uploading source code.

A Model Context Protocol (MCP) server designed to easily dump your codebase context into Large Language Models (LLMs).

Enables file reading with pagination and regex-based code search across a codebase using grep.

MCP server providing code review, auto-fix, test running, linting, formatting, and refactor suggestions for Claude Code.

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.

Provides comprehensive codebase analysis including project structure evaluation, cross-language duplicate detection, microservices validation, and configuration optimization with AI-powered pattern learning that generates actionable improvement reports.

An MCP server that acts as an AI mentor for any codebase using dual-layer indexing, enabling codebase initialization, tutorial generation, and semantic search.

Provides AI assistants with real-time visibility into your codebase's internal libraries, team patterns, naming conventions, and usage frequencies to generate code that matches your team's actual practices.

Zero-config MCP server that connects local codebases to AI assistants, providing secure project tree, regex search, file reading, and tech stack tools locally.

Provides a code graph querying and visualization MCP server, enabling users to search, trace, and describe code components, overlay diffs, and explore architecture through natural language.

A Docker-based MCP server providing codebase memory and search tools. It enables storing/retrieving memories, regex search of code, and file summarization for AI assistants.

Enables Claude-powered pre-push code review, blocking bad commits by analyzing diffs with Anthropic's models.

MCP server for local codebase memory: semantic indexing, hybrid search, and clean code analysis (static + LLM) with retrievable project notes, designed to run fully local on modest hardware.

Provides comprehensive code analysis through three MCP servers: static analysis for code quality and security, dependency analysis for package management and vulnerabilities, and complexity analysis for maintainability assessment across multiple programming languages.

Enables semantic code search across multiple repositories using AST-aware chunking and relationship tracking. Supports local LLM embeddings, real-time indexing, and cross-codebase dependency analysis through vector and graph databases.

An open-source AI-powered development assistant that connects Claude Desktop to your codebase via MCP, enabling semantic code search, AI-assisted editing, and persistent memory without additional subscriptions.

AST-aware codebase indexing with semantic search, exposed as an MCP server. Enables semantic search and file context retrieval across your codebase using natural language queries.