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 intelligent error detection and debugging capabilities across multiple programming languages with real-time monitoring of build, lint, runtime, console, and test errors. Offers AI-enhanced error analysis with automated resolution suggestions and context-aware debugging.
An installable MCP server that reviews diffs/PRs against a target repository's own coding conventions, learned via RAG over its code, docs, and lint config, citing specific file:line sources.
Integrates Google's Gemini AI models into Claude Code and other MCP clients to provide second opinions, code comparisons, and token counting. It supports streaming responses and multi-turn conversations directly within your existing AI development workflow.
MCP server providing automated code linting, rule explanations, and configuration templates for wemake-python-styleguide, with structured violation reports and offline rule database.
Exposes the 23 Gang of Four design patterns to AI coding agents for generation, canonical examples, AST-based detection, validation, and anti-pattern refactoring in Python codebases.
Enables deterministic static analysis of Python code, providing tools to inspect classes, functions, imports, dependencies, and more, without executing the code.
An MCP server that indexes a repository locally and provides keyword, semantic, hybrid, and SQL search tools, enabling coding agents to answer questions about the codebase efficiently without reading files one by one.
This MCP server provides direct access to ruff linting, formatting checks, and ty type-checking for Python projects, with token-efficient, structured output.
A local MCP server that provides semantic code search for Python codebases using tree-sitter for chunking and LanceDB for vector storage. It enables natural language queries to find relevant code snippets based on meaning rather than just text matching.
An MCP server that provides dynamic codebase context to Claude Code through tools like hybrid search, recent changes, and symbol definitions, enhancing AI-assisted coding with local RAG.